Name: Flask for Beginners
Price: 26.99 GBP
Availability: InStock

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			<h2>Learning Outcomes
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										<span>Learn what Python programming is and its basic data types</span>
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										<span>Know the fundamentals of Python operators</span>
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										<span>Deepen your understanding of control flow part - 1 and control flow part - 2</span>
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										<span>Enhance your idea of user input and error handling</span>
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										<span>Get acquainted with Python scripting and libraries</span>
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										<span>Get an introduction to OPP and learn the advanced OPP</span>
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			<h2>Description </h2>		</div>
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				<p><span>According to a statistic, Python is one of the most demanding jobs in the UK, which offers a salary of almost </span><span>£60,000 to programmers who are skilled in Pythons. This demand opens up many opportunities for freshers and experts in various IT fields. So, if you are from a programming background or wish to start your career in the relevant field, gain adequate skills in Python and shine in your future career with the help of the Python Programming: Beginner to Experts course.</span></p><p><span>Our immersive Python Programming: Beginner to Experts course will help you gain a thorough understanding of what Python is all about and in which sectors it's mostly used. Moreover, this course will provide you with knowledge of basic data types. In addition, you will learn about Python operators, user input and error handling and many more. While progressing through your study, you can also get to learn about Python scripting and libraries. It will also introduce you to the primary and advanced levels of OPP.</span></p><p><span>However, after completing this comprehensive course, you will immediately receive a CPD- Certificate of achievement, which will not only help you boost your confidence but also put some weight on your resume. So, enrol and begin your journey now!</span></p>					</div>
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			<h2>Certificate of Achievement </h2>		</div>
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				<p><span>After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post. </span></p>					</div>
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			<h2>Method of Assessment 
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				<p><span>After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly.</span></p>					</div>
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			<h2>Career path</h2>		</div>
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				<p><span>We designed this course with the aim of increasing your expertise in Python so that you can pursue your career in the relevant field. Such as - </span></p>					</div>
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										<span>Web Developer</span>
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										<span>Software Engineer</span>
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										<span>Data Scientist</span>
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										<span>Machine Learning Engineer</span>
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										<span>Data Analyst</span>
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Janets

Python Programming: Beginner To Expert

General Admission

<strong>In this course, we will start with extremely basic concepts such as learning the programming language fundamentals and other supporting libraries. Then we will proceed with the core topics with the help of real-world datasets to gain a complete understanding of deep learning using Python and Keras.</strong>
        <p>The artificial intelligence domain is divided broadly into deep learning and machine learning. In fact, deep learning is machine learning itself but deep learning with its deep neural networks and algorithms tries to learn high-level features from data without human intervention. That makes deep learning the base of all future self-intelligent systems.

This course begins with going over the basics of Python and then quickly moves on to important libraries of Python that are critical to data analysis and visualizations, such as NumPy, Pandas, and Matplotlib. After the basics, we will then install the deep learning libraries-Theano and TensorFlow-and the API for dealing with these called Keras.

Then, before we jump into deep learning, we will have an elaborate theory session about the basic structure of artificial neuron and neural networks, and about activation functions, loss functions, and optimizers.

Furthermore, we will create deep learning multi-layer neural network models for a text-based dataset and then convolutional neural networks for an image-based dataset.

You will also learn how the basic CNN layers such as the convolution layer, the pooling layer, and the fully connected layer work. Then, we will use different techniques to improve the quality of a model and perform optimization using image augmentation.

By the end of this course, you will have a complete understanding of deep learning and will be able to implement these skills in your own projects.

The complete code bundle for this course is available at https://github.com/PacktPublishing/Deep-Learning-using-Keras---A-Complete-and-Compact-Guide-for-Beginners</p>
        <h2>What You Will Learn</h2><p>Learn the basics of Python programming<br>Use different Python libraries such as NumPy, Matplotlib, and Pandas<br>Understand the basic structure of artificial neurons and neural networks<br>Explore activation functions, loss functions, and optimizers<br>Create deep learning multi-layer neural network models for a text-based dataset<br>Create convolutional neural networks for an image-based dataset</p>
        <h2>Audience</h2><p>This course is designed for beginners who want to learn basic to advanced deep learning and have basic computer knowledge.</p>
        <h2>Approach</h2><p>This course is a combination of theory and practical videos where we will understand the basics of Python programming, Python libraries, and deep learning concepts, and then use different datasets to understand deep learning using Keras.</p>
        <h2>Key Features</h2><p>Perform exploratory data analysis of the loaded data and prepare the data for giving it into the deep learning model * Learn how basic CNN layers such as the convolution layer, the pooling layer, and the fully connected layer work * Learn to use Google Colab to enhance parallel processing with VGGNet and ResNet models</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Deep-Learning-using-Keras---A-Complete-and-Compact-Guide-for-Beginners</p>
        <h2>About the Author</h2><h3>Abhilash Nelson</h3><p>Abhilash Nelson is a pioneering, talented, and security-oriented Android/iOS mobile and PHP/Python web application developer with more than 8 years of IT experience involving designing, implementing, integrating, testing, and supporting impactful web and mobile applications. He has a master's degree in computer science and engineering and has PHP/Python programming experience, which is an added advantage for server-based Android and iOS client applications. Abhilash is currently a senior solution architect managing projects from start to finish to ensure high quality and innovative and functional design.</p>
        <h2>Course Outline</h2><h4>1. Course Introduction and Table of Contents</h4><p></p><br><h4>2. Introduction to AI and Machine Learning</h4><p></p><br><h4>3. Introduction to Deep learning and Neural Networks</h4><p></p><br><h4>4. Setting up Computer - Installing Anaconda</h4><p></p><br><h4>5. Python Basics</h4><p></p><br><h4>6. Numpy Basics</h4><p></p><br><h4>7. Matplotlib Basics</h4><p></p><br><h4>8. Pandas Basics</h4><p></p><br><h4>9. Installing Deep Learning Libraries</h4><p></p><br><h4>10. Basic Structure of Artificial Neuron and Neural Network</h4><p></p><br><h4>11. Activation Functions Introduction</h4><p></p><br><h4>12. Popular Types of Activation Functions</h4><p></p><br><h4>13. Popular Types of Loss Functions</h4><p></p><br><h4>14. Popular Optimizers</h4><p></p><br><h4>15. Popular Neural Network Types</h4><p></p><br><h4>16. King County House Sales Regression Model - Step 1 Fetch and Load Dataset</h4><p></p><br><h4>17. Step 2 and 3 EDA and Data Preparation</h4><p></p><br><h4>18. Step 4 Defining the Keras Model</h4><p></p><br><h4>19. Step 5 and 6 Compile and Fit Model</h4><p></p><br><h4>20. Step 7 Visualize Training and Metrics</h4><p></p><br><h4>21. Step 8 Prediction Using the Model</h4><p></p><br><h4>22. Heart Disease Binary Classification Model - Introduction</h4><p></p><br><h4>23. Step 1 - Fetch and Load Data</h4><p></p><br><h4>24. Step 2 and 3 - EDA and Data Preparation</h4><p></p><br><h4>25. Step 4 - Defining the model</h4><p></p><br><h4>26. Step 5 - Compile Fit and Plot the Model</h4><p></p><br><h4>27. Step 5 - Predicting Heart Disease using Model</h4><p></p><br><h4>28. Redwine Quality MultiClass Classification Model - Introduction</h4><p></p><br><h4>29. Step1 - Fetch and Load Data</h4><p></p><br><h4>30. Step 2 - EDA and Data Visualization</h4><p></p><br><h4>31. Step 3 - Defining the Model</h4><p></p><br><h4>32. Step 4 - Compile Fit and Plot the Model</h4><p></p><br><h4>33. Step 5 - Predicting Wine Quality using Model</h4><p></p><br><h4>34. Serialize and Save Trained Model for Later Use</h4><p></p><br><h4>35. Digital Image Basics</h4><p></p><br><h4>36. Basic Image Processing using Keras Functions</h4><p></p><br><h4>37. Keras Single Image Augmentation</h4><p></p><br><h4>38. Keras Directory Image Augmentation</h4><p></p><br><h4>39. Keras Data Frame Augmentation</h4><p></p><br><h4>40. CNN Basics</h4><p></p><br><h4>41. Stride, Padding and Flattening Concepts of CNN</h4><p></p><br><h4>42. Flowers CNN Image Classification Model - Fetch Load and Prepare Data</h4><p></p><br><h4>43. Flowers Classification CNN - Create Test and Train Folders</h4><p></p><br><h4>44. Flowers Classification CNN - Defining the Model</h4><p></p><br><h4>45. Flowers Classification CNN - Training and Visualization</h4><p></p><br><h4>46. Flowers Classification CNN - Save Model for Later Use</h4><p></p><br><h4>47. Flowers Classification CNN - Load Saved Model  and Predict</h4><p></p><br><h4>48. Flowers Classification CNN - Optimization Techniques - Introduction</h4><p></p><br><h4>49. Flowers Classification CNN - Dropout Regularization</h4><p></p><br><h4>50. Flowers Classification CNN - Padding and Filter Optimization</h4><p></p><br><h4>51. Flowers Classification CNN - Augmentation Optimization</h4><p></p><br><h4>52. Hyper Parameter Tuning</h4><p></p><br><h4>53. Transfer Learning using Pretrained Models - VGG Introduction</h4><p></p><br><h4>54. VGG16 and VGG19 prediction</h4><p></p><br><h4>55. ResNet50 Prediction</h4><p></p><br><h4>56. VGG16 Transfer Learning Training Flowers Dataset</h4><p></p><br><h4>57. VGG16 Transfer Learning Flower Prediction</h4><p></p><br><h4>58. VGG16 Transfer Learning using Google Colab GPU - Preparing and Uploading Dataset</h4><p></p><br><h4>59. VGG16 Transfer Learning using Google Colab GPU - Training and Prediction</h4><p></p><br><h4>60. VGG19 Transfer Learning using Google Colab GPU - Training and Prediction</h4><p></p><br><h4>61. ResNet-50 Transfer Learning using Google Colab GPU - Training and Prediction</h4><p></p>

Packt

Keras

Computer Vision

Python

Pandas

Deep Learning

In this course, we will start with extremely basic concepts such as learning the programming language fundamentals and other supporting libraries. Then we will proceed with the core topics with the help of real-world datasets to gain a complete understanding of deep learning using Python and Keras.

Deep Learning Using Keras - A Complete and Compact Guide for Beginners

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					<div><p>Python has steadily ascended the ranks in the tech world, becoming the go-to language for Data Science and Machine Learning pursuits. Its versatility and ease of use make it an optimal choice for those aspiring to delve into the intricate realms of data analysis and algorithm development. By integrating Python into the curriculum, this course ensures that learners are not only familiar with the language but also proficient in its application to Data Science and Machine Learning tasks.</p><p>Data Science, on the other hand, stands as the backbone of today's analytical advancements. With the ever-growing quantum of data, there's a dire need for professionals who can sift through this data deluge and extract meaningful insights. This course simplifies complex topics, making it easier for learners to grasp the intricate mechanics of data manipulation, processing, and analysis. By emphasizing Python's role in Data Science, the course underscores its significance in modern-day data operations.</p><p>Lastly, Machine Learning represents the pinnacle of automated data analysis. With the power of Python and the methodologies of Data Science, Machine Learning enables systems to learn from data and make decisions. This course elucidates these concepts, teaching learners to design, implement, and test Machine Learning algorithms. The synergy of Python, Data Science, and Machine Learning in this curriculum ensures that, by the end, learners are well-equipped to tackle any data challenge that comes their way.</p></div>
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			<h2><b> Learning outcome</b></h2>		</div>
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										<span>Acquire in-depth knowledge of Data Science techniques using Python.</span>
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										<span>Analyze and visualize data with Python libraries like Pandas and Matplotlib.</span>
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										<span>Evaluate and compare Machine Learning algorithms for optimum results.</span>
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										<span>Develop real-time prediction models using trained datasets.</span>
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			<h2> <b>Why should I take this course?</b></h2>		</div>
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										<span>Stay ahead in the rapidly growing field of Data Science and Machine Learning.</span>
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										<span>Enhance career opportunities in the tech and data sectors.</span>
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										<span>Learn to use Python, a leading programming language in Data Science.</span>
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										<span>Address real-world business challenges using data analysis.</span>
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										<span>Achieve proficiency in handling and visualizing large datasets.</span>
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			<h2> <b>Career Path</b></h2>		</div>
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										<span>Python Data Analyst</span>
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										<span>Data Visualization Expert</span>
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			<h2> <b>Requirements</b></h2>		</div>
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										<span>Eagerness to learn Data Science and Machine Learning.</span>
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										<span>A computer with internet access.</span>
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Skill Up

Master Data Science and Machine Learning with Python to transform data-driven decisions in businesses.

Data Science & Machine Learning with Python

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				<p><span>Register on the Python Data Science today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career.</span></p><p><span>The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials.</span></p><p><span>Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion.</span></p><p><span>The Python Data Science is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones.</span></p><p><span>The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly!</span></p><h5><b>What You Get With The Python Data Science</b></h5><ul><li><span>Receive a e-certificate upon successful completion of the course</span></li><li><span>Get taught by experienced, professional instructors</span></li><li><span>Study at a time and pace that suits your learning style</span></li><li><span>Get instant feedback on assessments </span></li><li><span>24/7 help and advice via email or live chat</span></li><li><span>Get full tutor support on weekdays (Monday to Friday)</span></li></ul>					</div>
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			<h2>Course Design</h2>		</div>
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				<div id="course-home"><div><p><span>The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.</span></p><p><span>You are taught through a combination of</span></p><ul><li><span>Video lessons</span></li><li><span>Online study materials</span></li></ul></div></div>					</div>
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			<h2>Certification</h2>		</div>
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				<p><span>After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post.</span></p>					</div>
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			<h2>Who Is This Course For:</h2>		</div>
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				<p><span>The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.</span></p>					</div>
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			<h2>Requirements:</h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<p><span>The online training is open to all students and has no formal entry requirements. To study the Python Data Science, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.</span></p>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
									</div>
			</div>
					</div><div>
				<h3>Course Content</h3>

<div id="course_curriculum">
<table width="100%">				<tbody><tr>
					<td colspan="4">Unit 01: Introduction to Python Data Science</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Introduction to Python Data Science</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Environment Setup</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 02: Data Cleaning Packages</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Numpy package for calculations</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Panda package for Data cleaning</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 03: Data Visualization packages</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Matplotlib Data Visualization Part 1</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Matplotlib Data Visualization Part 2</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
				</tbody></table></div>

			</div>
			<h2>Frequently Asked Questions</h2>
                        <div>
                            <div>
                                <span>
                                    Are there any prerequisites for taking the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        There are no specific prerequisites for this course, nor
                                        are there any formal entry requirements. All you need is
                                        an internet connection, a good understanding of English
                                        and a passion for learning for this course.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Can I access the course at any time, or is there a set
                                    schedule?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        You have the flexibility to access the course at any time
                                        that suits your schedule. Our courses are self-paced,
                                        allowing you to study at your own pace and convenience.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    How long will I have access to the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        For this course, you will have access to the course
                                        materials for 1 year only. This means you can review the
                                        content as often as you like within the year, even after
                                        you've completed the course. However, if you buy Lifetime
                                        Access for the course, you will be able to access the
                                        course for a lifetime.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Is there a certificate of completion provided after
                                    completing the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        Yes, upon successfully completing the course, you will
                                        receive a certificate of completion. This certificate can
                                        be a valuable addition to your professional portfolio and
                                        can be shared on your various social networks.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Can I switch courses or get a refund if I'm not satisfied
                                    with the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        We want you to have a positive learning experience. If
                                        you're not satisfied with the course, you can request a
                                        course transfer or refund within 14 days of the initial
                                        purchase.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    How do I track my progress in the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        Our platform provides tracking tools and progress
                                        indicators for each course. You can monitor your progress,
                                        completed lessons, and assessments through your learner
                                        dashboard for the course.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    What if I have technical issues or difficulties with the
                                    course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        If you encounter technical issues or content-related
                                        difficulties with the course, our support team is
                                        available to assist you. You can reach out to them for
                                        prompt resolution.
                                    </p>
                                </div>
                            </div>
                        </div>

Data Science

Professional Skills Course (PSC)

Python Data Science

NextGen Learning

Diploma in Python Programming Course

<p>Unlock the world of programming excellence with our '<strong>Diploma in Python Programming</strong>' course. In this dynamic learning journey, you'll delve into the fundamental concepts of Python and emerge as a proficient Python programmer. Whether you're a novice or have some prior coding experience, this course caters to all levels of learners. You'll start with the basics, gradually working your way up to complex Python operations, data structures, and even creating a fun Rock, Paper, and Scissors project. By the end of this course, you'll have a strong grip on Python, be able to write user functions, handle exceptions, explore databases, and much more. Take your first step towards becoming a skilled Python programmer and discover the endless possibilities this versatile language offers.</p>
<p><strong>Learning Outcomes</strong></p>
<ul>
<li>Master the foundational concepts of Python programming.</li>
<li>Develop essential skills in working with strings, dates, and files using Python.</li>
<li>Create user functions, handle exceptions, and install packages.</li>
<li>Explore database management using SQLite and interact with the operating system.</li>
<li>Gain the knowledge and confidence to run Python programs in different environments, including Jupyter Notebook.</li>
</ul>
<h3><b>Why choose this Python Programming<span> Diploma</span>?</b></h3>
<ol>
<li>Unlimited access to the course for a lifetime.</li>
<li>Opportunity to earn a certificate accredited by the <b>CPD Quality Standards</b> and <b>CIQ </b>after completing this course.</li>
<li>Structured lesson planning in line with industry standards.</li>
<li>Immerse yourself in innovative and captivating course materials and activities.</li>
<li>Assessments designed to evaluate advanced cognitive abilities and skill proficiency.</li>
<li>Flexibility to complete the Course at your own pace, on your own schedule.</li>
<li>Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience.</li>
<li>Unlock career resources for CV improvement, interview readiness, and job success.</li>
</ol>
<h3><b>Who is this </b><b>Python Programming<span> Diploma </span></b><b></b><b>for?</b></h3>
<ul>
<li>Aspiring programmers looking to kickstart their coding journey.</li>
<li>Professionals seeking to expand their skill set and explore Python.</li>
<li>Students aiming to excel in programming and computer science.</li>
<li>Anyone curious about the power and versatility of Python as a programming language.</li>
</ul>
<h3><b>Career path</b></h3>
<ul>
<li><strong>Python Programmer</strong>: £25,000 - £70,000</li>
<li><strong>Data Analyst</strong>: £30,000 - £60,000</li>
<li><strong>Web Developer</strong>: £25,000 - £50,000</li>
<li><strong>Software Engineer</strong>: £35,000 - £80,000</li>
<li><strong>Machine Learning Engineer</strong>: £40,000 - £90,000</li>
<li><strong>Data Scientist</strong>: £40,000 - £70,000</li>
</ul>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>Diploma in Python Programming</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning. This </span><b>Diploma in Python Programming</b><span> was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.</span></p>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8.</span></p><div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4">Unit 01: Introduction to Python Programming</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Course Introduction</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 02: Getting Started with Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Software Installation</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Hello World Program</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 03: Input and Output</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 04: Calculating Average of 5 Numbers</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 03: Conditional Branching with Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: If Loop In Python</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Program Using If Else part 1</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 03: Program Using If Else part 2</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 04: Program for Calculator</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 05: Program Using For Loop</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 06: For Table</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 07: For loop and Mathematical Operator in Python</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 08: Factorial of Number Using Python</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 09: Program Using While</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 10: While Loop Example</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 11: Tasks for Practice</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 04: Importing external/internal library in python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Importing Library in Python</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 05: Project Rock Paper and Scissors</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Rock Paper and Scissor Game</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 06: Strings Operation in Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Program Using String part 1</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Program using String 2</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 03: Program Using String 3</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 04: Program Using String part 4</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 07: Date and time in Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Use of Date and Time part 1</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Use of Date and Time part 2</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 08: File Handling, read and write using Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: File Handling Part 1</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: File Handling Part 2</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 09: Data Storage Structures, Tuple, List and Dictionary</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Tuple in Python Part 1</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Tuple in Python Part 2</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 03: Using Lists part 1</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 04: Using List part 2</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 05: Using Lists part 3</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 06: Using Lists part 4</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 07: Using Lists part 5</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 08: Use of Dictionary Part 1</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 09: Use of Dictionary Part 2</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 10: Use of Dictionary Part 3</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 11: Use of Dictionary Part 4</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 10: Writing user functions in Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Function in Python Part 1</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Function in Python Part 2</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 03: Function in Python Part 3</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 04: Function in Python Part 4</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 05: Function in Python Part 5</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 11: Sending mail</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Send Email</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 12: Import Tricks in Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Import Study part 1</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Import Study part 2</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 13: Import Operating System and Platform</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Importing OS</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Import Platform</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 14: Exceptions handling in python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Exception in Python part 1</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Exception in Python part 2</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 03: Exception in Python part 3</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 15: Installing Packages and Scheduling In Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Installing Packages using built in package manager</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Scheduler in Python</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 16: Data Base In Python using sqlite</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Data Base 1</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Data Base 2</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 03: Data Base 3</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 04: Data base 4</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 05: Data Base 5</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 17: Running Program from Command Prompt and jupyter Notebook</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: IDE_1</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: IDE_2</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 18: Conclusion</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Conclusion</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Resources</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Resources - Diploma in Python Programming</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Assignment</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assignment - Diploma in Python Programming</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Recommended Materials</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Workbook - Diploma in Python Programming</td>
					<td> </td>
					<td><span><i></i> 05:14:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Studyhub UK

Diploma in Python Programming

<strong>This course will teach you how to work with object recognition using a predefined dataset and how to create a custom dataset. The course will also teach you to train the You Only Look Once (YOLO) model to build a coronavirus detection model.</strong>
        <p>Object detection is the most commonly used application of computer vision, which also helps the computer recognize and classify objects inside an image. This video course will help you learn Python-based object recognition methods and develop custom object detection models.

The course begins with an introduction to the You Only Look Once (YOLO) object detection system, Python programming, and Convolutional Neural Networks (CNNs). You will learn object detection by installing Anaconda on your computer and the OpenCV library in Python. Next, you will learn to perform object detection and recognition on a single object in an image and on a real-time webcam video using YOLO pre-trained model and Common Objects in Context (COCO) dataset.

Moving ahead, you will learn the pros and cons of using a pre-trained dataset model and a custom dataset trained model. In addition, you will get an overview of the free GPU offered by Google Colab. Toward the end, you will learn to create a custom dataset and train a darknet YOLO model to detect coronavirus from an electron microscope image or video output.

By the end of this video course, you will develop the skills required to build object recognition models using predefined and custom datasets.</p>
        <h2>What You Will Learn</h2><p>Become familiar with Python and OpenCV libraries<br>Perform object recognition using a predefined dataset<br>Create a custom dataset and train the You Only Look Once (YOLO) model<br>Use the YOLO model on a single image for object detection<br>Try the YOLO model for object detection from a real-time webcam video<br>Create a full-fledged flawless coronavirus detection model</p>
        <h2>Audience</h2><p>If you are a beginner, a developer, or a computer vision enthusiast who wants to develop models for object recognition using Python, then this course is for you. A basic understanding of Python and object recognition is recommended, but not mandatory, to quickly understand the concepts explained.</p>
        <h2>Approach</h2><p>This video course will help you get started with the object recognition techniques using engaging activities and exercises. You will also learn how to use the You Only Look Once (YOLO) model with Python to detect objects in images and videos.</p>
        <h2>Key Features</h2><p>Get started with the You Only Look Once (YOLO) object detection method * Build models to recognize objects in images and real-time webcam videos * Learn how to prepare custom datasets to build your own coronavirus detection model</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Computer-Vision-YOLO-Custom-Object-Detection-with-Colab-GPU</p>
        <h2>About the Author</h2><h3>Abhilash Nelson </h3><p>Abhilash Nelson is a pioneering, talented, and security-oriented Android/iOS mobile and PHP/Python web application developer with more than eight years of IT experience involving designing, implementing, integrating, testing, and supporting impactful web and mobile applications. He has a master's degree in computer science and engineering and has PHP/Python programming experience, which is an added advantage for server-based Android and iOS client applications. Abhilash is currently a senior solution architect managing projects from start to finish to ensure high quality and innovative and functional design.</p>
        <h2>Course Outline</h2><h4>1. Course Introduction and Table of Contents</h4><p>This section provides a brief overview of the course and discusses the learning objectives.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course Introduction and Table of Contents</p><p style='margin: 0'>This video gives you an idea of the course and explains the concepts you are going to learn in this section.</p></td></tr></tbody></table><br><h4>2. Introduction to You Only Look Once (YOLO) Object Detection</h4><p>This section introduces the concept of YOLO object detection in computer vision.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to You Only Look Once (YOLO) Object Detection</p><p style='margin: 0'>This video introduces you to the concept and scope of YOLO object detection.</p></td></tr></tbody></table><br><h4>3. Environment Setup - Installing Anaconda</h4><p>This section explains how to install Anaconda and set up the environment required to run YOLO.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Environment Setup - Installing Anaconda</p><p style='margin: 0'>This video demonstrates how to set up the environment by installing Anaconda.</p></td></tr></tbody></table><br><h4>4. Python Basics</h4><p>This section provides a recap on the basic concepts of Python before getting into the details of the course.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Assignment</p><p style='margin: 0'>This video illustrates an assignment on Python.</p></td></tr><tr><td style='padding: 15px;'><p>2. Flow Control</p><p style='margin: 0'>This video discusses flow control in Python.</p></td></tr><tr><td style='padding: 15px;'><p>3. Data Structures</p><p style='margin: 0'>This video discusses the data structures in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Functions</p><p style='margin: 0'>This video discusses the various functions in Python.</p></td></tr></tbody></table><br><h4>5. Installing OpenCV Library</h4><p>This section explains how to install the OpenCV library.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Installing OpenCV Library</p><p style='margin: 0'>This video demonstrates how to install the OpenCV library.</p></td></tr></tbody></table><br><h4>6. Introduction to Convolutional Neural Networks (CNNs)</h4><p>This section introduces you to CNNs.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to Convolutional Neural Networks (CNNs)</p><p style='margin: 0'>This video introduces you to CNN, its working, and the different steps involved.</p></td></tr></tbody></table><br><h4>7. You Only Look Once (YOLO) Pre-Trained Object Detection from Image</h4><p>This section explains how to detect objects from images using pre-trained datasets.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once (YOLO) Pre-Trained Object Detection from an Image - Part 1</p><p style='margin: 0'>This video is the first part of the four-part video that explains how to detect an object from an image using a pre-trained YOLO dataset.</p></td></tr><tr><td style='padding: 15px;'><p>2. You Only Look Once (YOLO) Pre-Trained Object Detection from an Image - Part 2</p><p style='margin: 0'>This video is the second part of the four-part video that explains how to detect an object from an image using a pre-trained YOLO dataset.</p></td></tr><tr><td style='padding: 15px;'><p>3. You Only Look Once (YOLO) Pre-Trained Object Detection from an Image - Part 3</p><p style='margin: 0'>This video is the third part of the four-part video that explains how to detect an object from an image using a pre-trained YOLO dataset.</p></td></tr><tr><td style='padding: 15px;'><p>4. You Only Look Once (YOLO) Pre-Trained Object Detection from an Image - Part 4</p><p style='margin: 0'>This video is the fourth part of the four-part video that explains how to detect an object from an image using a pre-trained YOLO dataset.</p></td></tr></tbody></table><br><h4>8. You Only Look Once (YOLO) Pre-Trained Object Detection from an Image - Non-Maximum Suppression (NMS)</h4><p>This section explains how to detect objects from images using a pre-trained YOLO dataset.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once (YOLO) Pre-Trained Object Detection from an Image - Non-Maximum Suppression (NMS) - Part 1</p><p style='margin: 0'>This video is the first part of the two-part video that explains the technique of NMS used to prevent instances where YOLO returns more than one successful detection for a single object in an image.</p></td></tr><tr><td style='padding: 15px;'><p>2. You Only Look Once (YOLO) Pre-Trained Object Detection from an Image - Non-Maximum Suppression (NMS) - Part 2</p><p style='margin: 0'>This video is the second part of the two-part video that explains how you can use NMS to prevent instances where YOLO returns more than one successful detection for a single object in an image.</p></td></tr></tbody></table><br><h4>9. You Only Look Once (YOLO) Pre-Trained Object Detection from a Real-Time Webcam Video</h4><p>This section explains how to detect an object from a real-time webcam video using a pre-trained YOLO dataset.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once (YOLO) Pre-Trained Object Detection from a Real-Time Webcam Video</p><p style='margin: 0'>This video explains how to detect objects from a real-time webcam video in YOLO using a pre-trained dataset.</p></td></tr></tbody></table><br><h4>10. You Only Look Once (YOLO) Pre-Trained Object Detection from a Pre-Saved Video</h4><p>This section explains how to detect an object from a pre-saved video using a pre-trained YOLO dataset.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once (YOLO) Pre-Trained Object Detection from a Pre-Saved Video</p><p style='margin: 0'>This video explains how to detect an object from a pre-saved video using a pre-trained YOLO dataset.</p></td></tr></tbody></table><br><h4>11. Introduction to the Custom-Trained You Only Look Once (YOLO) Model</h4><p>This section introduces you to the custom-trained YOLO model.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to the Custom-Trained You Only Look Once (YOLO) Model</p><p style='margin: 0'>This video provides a brief introduction on creating and implementing a custom-trained YOLO model.</p></td></tr></tbody></table><br><h4>12. YOLOv4 Custom Training Phase 1 - Preparing Darknet</h4><p>This section introduces the concept of weights in YOLO and also explains how to use Darknet.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once v4 (YOLOv4) Introduction and Downloading Weights</p><p style='margin: 0'>This video introduces you to YOLOv4 and explains how to download the weights of YOLOv4.</p></td></tr><tr><td style='padding: 15px;'><p>2. You Only Look Once v4 (YOLOv4) Preparing Darknet</p><p style='margin: 0'>This video demonstrates how to prepare a Darknet to train a YOLO model.</p></td></tr></tbody></table><br><h4>13. You Only Look Once v4 (YOLOv4) Custom Training Phase 2 - Data Collection</h4><p>This section discusses the data collection process required to use YOLO.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Collection - Part 1</p><p style='margin: 0'>This video is the first part of the two-part video that explains how to collect the required data to train the YOLO model.</p></td></tr><tr><td style='padding: 15px;'><p>2. Data Collection - Part 2</p><p style='margin: 0'>This video is the second part of the two-part video that explains how to collect the required data to train the YOLO model.</p></td></tr></tbody></table><br><h4>14. You Only Look Once v4 (YOLOv4) Custom Training Phase 2 - Image Labelling</h4><p>This section explains how images are labeled in YOLOv4.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Image Labelling - Part 1</p><p style='margin: 0'>This video is the first part of the two-part video that explains how to label images to train a customized YOLO model.</p></td></tr><tr><td style='padding: 15px;'><p>2. Image Labelling - Part 2</p><p style='margin: 0'>This video is the second part of the two-part video that explains how to label images to train a customized YOLO model.</p></td></tr></tbody></table><br><h4>15. You Only Look Once v4 (YOLOv4) Custom Training Phase 2 - Train Test Split</h4><p>This section discusses the concept of train test split in YOLO.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once v4 (YOLOv4) Custom Training Phase 2 - Train Test Split</p><p style='margin: 0'>This video explains the concept of train test split while training a custom YOLO model.</p></td></tr></tbody></table><br><h4>16. You Only Look Once v4 (YOLOv4) Custom Training Phase 2 - Data Preparation</h4><p>This section explains how to prepare the data required to train the YOLO model.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Preparation - Part 1</p><p style='margin: 0'>This video explains the process of data preparation.</p></td></tr><tr><td style='padding: 15px;'><p>2. Data Preparation - Part 2</p><p style='margin: 0'>This video further explains the process of data preparation.</p></td></tr></tbody></table><br><h4>17. You Only Look Once v4 (YOLOv4) Custom Training Phase 3 - Data Sync</h4><p>This section explains how to sync the data required to train the YOLO model.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Preparing Files Sync to Drive</p><p style='margin: 0'>This video demonstrates how to prepare files to sync with Google Drive.</p></td></tr><tr><td style='padding: 15px;'><p>2. Connecting Colab and Drive</p><p style='margin: 0'>This video demonstrates how to back up folders in Google Drive to run in Colab.</p></td></tr></tbody></table><br><h4>18. You Only Look Once v4 (YOLOv4) Custom Training Phase 4 - Compile and Test Darknet</h4><p>This section explains how to compile the data required to train the YOLO model and test Darknet.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Compile and Test Darknet - Part 1</p><p style='margin: 0'>This video is the first part that explains how to compile data and test Darknet.</p></td></tr><tr><td style='padding: 15px;'><p>2. Compile and Test Darknet - Part 2</p><p style='margin: 0'>This video is the second part that explains how to compile data and test Darknet.</p></td></tr><tr><td style='padding: 15px;'><p>3. Compile and Test Darknet - Part 3</p><p style='margin: 0'>This video is the third part that explains how to compile data and test Darknet.</p></td></tr></tbody></table><br><h4>19. You Only Look Once v4 (YOLOv4) Custom Training Phase 5 - Chart and Training Progress Analysis</h4><p>This section discusses how to chart and analyze the progress of dataset training.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once v4 (YOLOv4) Custom Training Phase 5 - Chart and Training Progress Analysis</p><p style='margin: 0'>This video explains how to chart the progress analysis while training a YOLO dataset.</p></td></tr></tbody></table><br><h4>20. You Only Look Once v4 (YOLOv4) Custom Training Phase 5 - Finalizing Training Download Weights</h4><p>This section explains how to finalize the YOLOv4 dataset and download the weights.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once v4 (YOLOv4) Custom Training Phase 5 - Finalizing Training Download Weights</p><p style='margin: 0'>This video explains how to finalize the training weights for a YOLO model.</p></td></tr></tbody></table><br><h4>21. Colab GPU Usage Limit Issue</h4><p>This section discusses the issue posed by the usage limit of Colab GPU.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Colab GPU Usage Limit Issue</p><p style='margin: 0'>This video explains the Colab GPU usage limit issue faced while working with the Google GPU service.</p></td></tr></tbody></table><br><h4>22. OpenCV Upgrade for You Only Look Once v4 (YOLOv4)</h4><p>This section explains how to upgrade OpenCV so that it can be used with YOLOv4.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. OpenCV Upgrade for You Only Look Once v4 (YOLOv4)</p><p style='margin: 0'>This video explains how to upgrade OpenCV to match the version of YOLOv4.</p></td></tr></tbody></table><br><h4>23. You Only Look Once v4 (YOLOv4) Pre-Trained Object Recognition from an Image and a Video</h4><p>This section explains how objects are recognized from images and videos using a pre-trained YOLOv4 dataset.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once v4 (YOLOv4) Pre-Trained Object Recognition from an Image and a Video</p><p style='margin: 0'>This video explains how to detect coronavirus from an image and a video using a pre-trained YOLOv4 dataset.</p></td></tr></tbody></table><br><h4>24. You Only Look Once v4 (YOLOv4) Custom Coronavirus Detection from an Image</h4><p>This section explains how to detect an image of coronavirus in YOLO.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once v4 (YOLOv4) Custom Coronavirus Detection from an Image</p><p style='margin: 0'>This video explains how to detect coronavirus from an image using a custom trained YOLOv4 dataset.</p></td></tr></tbody></table><br><h4>25. You Only Look Once v4 (YOLOv4) Custom Coronavirus Detection from a Video</h4><p>This section demonstrates how to detect coronavirus from a video.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. You Only Look Once v4 (YOLOv4) Custom Coronavirus Detection from a Video</p><p style='margin: 0'>This video explains how to detect coronavirus from a video using a custom-trained YOLOv4 dataset.</p></td></tr></tbody></table><br><h4>26. Other Sample Real-World Case Studies</h4><p>This section focuses on other real-world case studies using YOLO for better comprehension of the concept.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Other Sample Real-World Case Studies</p><p style='margin: 0'>This video illustrates examples of real-world case studies for object detection.</p></td></tr></tbody></table>

This course will teach you how to work with object recognition using a predefined dataset and how to create a custom dataset. The course will also teach you to train the You Only Look Once (YOLO) model to build a coronavirus detection model.

Computer Vision: YOLO Custom Object Detection with Colab GPU

<p>Get ready for an exceptional online learning experience with the <strong>Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security </strong>bundle! This carefully curated collection of<strong> 20 premium courses</strong> is designed to cater to a variety of interests and disciplines. Dive into a sea of knowledge and skills, tailoring your learning journey to suit your unique aspirations.</p><p>The Python &amp; Data Science package is dynamic, blending the expertise of industry professionals with the flexibility of digital learning. It offers the perfect balance of foundational understanding and advanced insights. Whether you're looking to break into a new field or deepen your existing knowledge, the Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Securitypackage has something for everyone.</p><p>As part of the Python &amp; Data Science package, you will receive complimentary PDF certificates for all courses in this bundle at no extra cost. Equip yourself with the Python &amp; Data Science bundle to confidently navigate your career path or personal development journey. Enrol today and start your career growth!</p><p><strong>This Bundle Comprises the Following </strong><strong>Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security  </strong><strong>CPD-accredited courses:</strong></p><ul><li><strong>Course 01: </strong>Python Programming: Beginner To Expert</li><li><strong>Course 02:</strong> Data Science &amp; Machine Learning with Python</li><li><strong>Course 03: </strong>Coding with Python 3</li><li><strong>Course 04: </strong>Introduction to Coding With HTML, CSS, &amp; Javascript</li><li><strong>Course 05: </strong>Python for Spatial Analysis in ArcGIS</li><li><strong>Course 06: </strong>Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li><strong>Course 07: </strong>Business Intelligence and Data Mining</li><li><strong>Course 08: </strong>SQL for Data Science, Data Analytics and Data Visualization</li><li><strong>Course 09: </strong>Python Data Science with Numpy, Pandas and Matplotlib</li><li><strong>Course 10: </strong>Cloud Computing / CompTIA Cloud+ (CV0-002)</li><li><strong>Course 11: </strong>Cyber Security Awareness Training</li><li><strong>Course 12:</strong> Learn Ethical Hacking From A-Z: Beginner To Expert</li><li><strong>Course 13: </strong>Easy to Advanced Data Structures</li><li><strong>Course 14: </strong>R Programming for Data Science</li><li><strong>Course 15: </strong>GDPR UK Training</li><li><strong>Course 16: </strong>Career Development Plan Fundamentals</li><li><strong>Course 17: </strong>CV Writing and Job Searching</li><li><strong>Course 18: </strong>Learn to Level Up Your Leadership</li><li><strong>Course 19: </strong>Networking Skills for Personal Success</li><li><strong>Course 20: </strong>Ace Your Presentations: Public Speaking Masterclass</li></ul><p><strong>What will make you stand out?</strong></p><p>Upon completion of this online Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security bundle, you will gain the following:</p><ul><li>CPD QS Accredited Proficiency with this Python &amp; Data Science bundle</li><li>After successfully completing the Python &amp; Data Science bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities.</li><li>Lifetime access to the whole collection of learning materials of this Python &amp; Data Science bundle</li><li>The online test with immediate results</li><li>You can study and complete the Python &amp; Data Science bundle at your own pace.</li><li>Study for the Python &amp; Data Science bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p>Each course in this Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This Python &amp; Data Science bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development.</p><p>Embrace the future of learning with the Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security , a rich anthology of 30 diverse courses. Our experts handpick each course in the Python &amp; Data Science bundle to ensure a wide spectrum of learning opportunities. This Python &amp; Data Science bundle will take you on a unique and enriching educational journey.</p><p>The Python &amp; Data Science bundle encapsulates our mission to provide quality, accessible education for all. Whether you are just starting your career, looking to switch industries, or hoping to enhance your professional skill set, the Python &amp; Data Science bundle offers you the flexibility and convenience to learn at your own pace. Make the Python &amp; Data Science package your trusted companion in your lifelong learning journey.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        200 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>The <strong>Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security  </strong>bundle is perfect for:</p><ul><li><strong>Beginners interested in technology: </strong>Individuals with little to no background in tech who are looking to start their careers in various IT domains.</li><li><strong>Aspiring Data Scientists and Analysts:</strong> Those aiming to build foundational and advanced skills in data science and machine learning.</li><li><strong>Future Software Developers: </strong>Individuals interested in learning Python and SQL for software development or database management.</li><li><strong>IT Security Enthusiasts: </strong>People who are keen on entering the field of cyber security and want to understand how to protect data in a digital environment.</li><li><strong>Cloud Computing Aspirants:</strong> Those looking to gain skills in cloud technologies and understand how to manage and deploy applications on the cloud.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You are warmly invited to register for this Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Upon <strong>Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security  </strong>course completion, you can expect to:</p><ul><li>Python Developer</li><li>Data Analyst</li><li>Machine Learning Engineer</li><li>Database Administrator</li><li>Cloud Solutions Architect</li><li>Cyber Security Specialist</li><li>Data Science Consultant</li><li>Systems Analyst</li><li>Network Security Engineer</li><li>Research Scientist (AI/ML)</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>20 CPD Quality Standard Pdf Certificates</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Compliance Central

Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security

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			<h2><b>Course Overview</b></h2>		</div>
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					<div><p><span>Learn the logistics of advanced coding by using the world's most popular programming language with this course on </span><b>Computer Science with Python. </b><span>Trying to understand the theories of computation, algorithms, and technology can be challenging, even for the most adept IT technician. This advanced training will help anyone excel in coding and programming practices, taking your IT capabilities to whole new levels.        </span></p><p><span>This specialised </span><b>Python </b><span>tuition can assist even experienced computer scientists gain a greater understanding of the complexities and mathematical theories that drive all software and software platforms. The instructor provides complete guidance and support, along with regular assessments and quizzes to ensure that crucial knowledge has been embedded. The tutorial presents this complex subject matter in a way that will improve your computer skills significantly. </span></p></div>
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					<div><p>This best selling <strong>Computer Science With Python </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Computer Science With Python </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p>
<p>The <strong>Computer Science With Python </strong>is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The <strong>Computer Science With Python </strong>is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p>
<p>After successfully completing the<strong> Computer Science With Python</strong>, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the <strong>Computer Science With Python </strong>will help you stand out from the crowd. You can also validate your certification on our website.</p>
<p>We know that you are busy and that time is precious, so we have designed the <strong>Computer Science With Python </strong>to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p>
<p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Course Cloud

Computer Science With Python

<strong>Learn Flask, the simple yet powerful Python web framework. This course is a ridiculously simple way to learn Flask in less than a weekend.</strong>
        <p>This course will teach you how to build Flask apps using only Flask and two essential extensions. You don't have to worry about managing multiple extensions on your machine or about incompatible database systems. By learning without using extra extensions other than Flask-SQLAlchemy and Flask-Login, you'll have a better understanding of how things work; thus, when you actually use extensions, you'll get much more out of them. 
Why Flask? Even though Flask is simple, you can create any web app you can imagine using it. Flask is not only easy to learn, it's also virtually guaranteed to work on your machine. If you've ever tried installing a large library only to find it doesn't work on your computer, you'll be delighted to find that Flask, with its few dependencies and small footprint, will work on your computer.  
You'll start by learning the basics of Flask. You'll learn enough to understand the fundamentals of Flask, how to use templates, and how to connect and use an SQLite database with Flask-SQLAlchemy. Once you decide to change databases, you'll simply update the configuration because you used Flask-SQLAlchemy. And, since the best way to learn is by example, we'll build two demo applications that use only what you learned in the preceding sections. This course covers using Flask 1.0 along with Flask-SQLAlchemy 2.3 and Flask-Login 0.4. Python 3.6+ is required, but no advanced features are used so you may be able to use an older version of Python.</p>
        <h2>What You Will Learn</h2><p>Explore the advanced networking concepts, build WANs, and work with IPV6<br>Learn EIGRP troubleshooting, GNS3 labs, and simulations<br>Practice DCE DTE physical router demos<br>NAT configuration and testing, IPV6<br>Discover OSPF anConfigure VPN and Dynamic Multipoint VPN (DMVPN)<br>Master GRE tunnel configuration and the WAN technologyd BGP</p>
        <h2>Audience</h2><p>This course is for anyone who has mastered the Python fundamentals and is keen to learn how to build web frameworks in Flask. Since Flask is a microframework, beginners can easily learn and use the framework. All you need to know before starting the course is the Python basics. If you're already comfortable working with features such as loops and dicts in Python, you are ready for this course.   </p>
        <h2>Approach</h2><p>The course starts by covering the basics of the Flask framework. You will learn basic request and response handling in Flask, and then how to create templates in Flask using the Jinja library. Finally, you will learn how to interact with a SQL database using Flask-SQLAlchemy. Once all the basics have been covered, we walk you through creating three app examples that use the basics of Flask and more.</p>
        <h2>Key Features</h2><p>These videos last hours and explain all the fundamentals of the Flask web framework. They cover both how to use Flask and examples of apps built with Flask. * Explanations targeted at beginners. We don't assume you know anything about Flask, so we explain all the code you write. We don't just show you how we also explain why.</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/flask-for-beginners</p>
        <h2>About the Author</h2><h3>Anthony Herbert</h3><p>Anthony Herbert is the founder of Pretty Printed. He has been programming since 2004, but a number of those years were spent with a lack of understanding of concepts. To help others avoid the issues he had while learning to program, he created Pretty Printed so that programmers of all skill levels can understand programming concepts easier and faster.</p>
        <h2>Course Outline</h2><h4>1. Course Intro</h4><p>Here, we begin with course introduction.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. StartIntro</p><p style='margin: 0'>Course Intro: StartIntro</p></td></tr><tr><td style='padding: 15px;'><p>2. StartWhich Version of Python</p><p style='margin: 0'>Course Intro: StartWhich Version of Python</p></td></tr><tr><td style='padding: 15px;'><p>3. StartNote About Pipenv</p><p style='margin: 0'>Course Intro: StartNote About Pipenv</p></td></tr><tr><td style='padding: 15px;'><p>4. StartDownload the Source Code</p><p style='margin: 0'>Course Intro: StartDownload the Source Code</p></td></tr></tbody></table><br><h4>2. Flask Basics</h4><p>In this section, we begin with Flask basics with installation and configuration.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. StartInstall Flask</p><p style='margin: 0'>Flask Basics: StartInstall Flask</p></td></tr><tr><td style='padding: 15px;'><p>2. StartRouting</p><p style='margin: 0'>Flask Basics: StartRouting</p></td></tr><tr><td style='padding: 15px;'><p>3. StartRequest Methods</p><p style='margin: 0'>Flask Basics: StartRequest Methods</p></td></tr><tr><td style='padding: 15px;'><p>4. StartRoute Variables</p><p style='margin: 0'>Flask Basics: StartRoute Variables</p></td></tr><tr><td style='padding: 15px;'><p>5. StartQuery String Arguments</p><p style='margin: 0'>Flask Basics: StartQuery String Arguments</p></td></tr><tr><td style='padding: 15px;'><p>6. StartForm Data</p><p style='margin: 0'>Flask Basics: StartForm Data</p></td></tr><tr><td style='padding: 15px;'><p>7. PreviewJSON Data</p><p style='margin: 0'>Flask Basics: PreviewJSON Data</p></td></tr><tr><td style='padding: 15px;'><p>8. StartRedirect and url_for</p><p style='margin: 0'>Flask Basics: StartRedirect and url_for</p></td></tr><tr><td style='padding: 15px;'><p>9. StartDebug</p><p style='margin: 0'>Flask Basics: StartDebug</p></td></tr></tbody></table><br><h4>3. Templates</h4><p>Here, we look into templates and various conditionals.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Startintro to Templates</p><p style='margin: 0'>Templates: Startintro to Templates</p></td></tr><tr><td style='padding: 15px;'><p>2. StartTemplate Variables</p><p style='margin: 0'>Templates: StartTemplate Variables</p></td></tr><tr><td style='padding: 15px;'><p>3. StartConditionals</p><p style='margin: 0'>Templates: StartConditionals</p></td></tr><tr><td style='padding: 15px;'><p>4. StartLoops</p><p style='margin: 0'>Templates: StartLoops</p></td></tr><tr><td style='padding: 15px;'><p>5. PreviewInclude</p><p style='margin: 0'>Templates: PreviewInclude</p></td></tr><tr><td style='padding: 15px;'><p>6. StartInheritance</p><p style='margin: 0'>Templates: StartInheritance</p></td></tr><tr><td style='padding: 15px;'><p>7. StartComments</p><p style='margin: 0'>Templates: StartComments</p></td></tr><tr><td style='padding: 15px;'><p>8. StartStatic Files</p><p style='margin: 0'>Templates: StartStatic Files</p></td></tr></tbody></table><br><h4>4. Flask-SQLAlchemy</h4><p>In this section, we start by discovering SQLAlchemy.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. StartIntro and Install</p><p style='margin: 0'>Flask-SQLAlchemy: StartIntro and Install</p></td></tr><tr><td style='padding: 15px;'><p>2. StartDetermine the URI</p><p style='margin: 0'>Flask-SQLAlchemy: StartDetermine the URI</p></td></tr><tr><td style='padding: 15px;'><p>3. StartConfigure and Create the Database</p><p style='margin: 0'>Flask-SQLAlchemy: StartConfigure and Create the Database</p></td></tr><tr><td style='padding: 15px;'><p>4. StartCreate Table</p><p style='margin: 0'>Flask-SQLAlchemy: StartCreate Table</p></td></tr><tr><td style='padding: 15px;'><p>5. StartInsert Data</p><p style='margin: 0'>Flask-SQLAlchemy: StartInsert Data</p></td></tr><tr><td style='padding: 15px;'><p>6. PreviewUpdate Data</p><p style='margin: 0'>Flask-SQLAlchemy: PreviewUpdate Data</p></td></tr><tr><td style='padding: 15px;'><p>7. StartDelete Data</p><p style='margin: 0'>Flask-SQLAlchemy: StartDelete Data</p></td></tr><tr><td style='padding: 15px;'><p>8. StartCreate One to Many Relationships</p><p style='margin: 0'>Flask-SQLAlchemy: StartCreate One to Many Relationships</p></td></tr><tr><td style='padding: 15px;'><p>9. StartAdd Data to One to Many Relationships</p><p style='margin: 0'>Flask-SQLAlchemy: StartAdd Data to One to Many Relationships</p></td></tr><tr><td style='padding: 15px;'><p>10. StartQuery One to Many Relationships</p><p style='margin: 0'>Flask-SQLAlchemy: StartQuery One to Many Relationships</p></td></tr><tr><td style='padding: 15px;'><p>11. StartCreate Many to Many</p><p style='margin: 0'>Flask-SQLAlchemy: StartCreate Many to Many</p></td></tr><tr><td style='padding: 15px;'><p>12. StartAdd Data to Many to Many</p><p style='margin: 0'>Flask-SQLAlchemy: StartAdd Data to Many to Many</p></td></tr><tr><td style='padding: 15px;'><p>13. StartQuery Many to Many</p><p style='margin: 0'>Flask-SQLAlchemy: StartQuery Many to Many</p></td></tr><tr><td style='padding: 15px;'><p>14. StartGet All Data</p><p style='margin: 0'>Flask-SQLAlchemy: StartGet All Data</p></td></tr></tbody></table><br><h4>5. Structuring Flask Apps</h4><p>Here, we structure Flask Apps.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. PreviewApp Factories</p><p style='margin: 0'>Structuring Flask Apps: PreviewApp Factories</p></td></tr><tr><td style='padding: 15px;'><p>2. StartBlueprints</p><p style='margin: 0'>Structuring Flask Apps: StartBlueprints</p></td></tr><tr><td style='padding: 15px;'><p>3. StartOrganizing Projects Beyond a Single File</p><p style='margin: 0'>Structuring Flask Apps: StartOrganizing Projects Beyond a Single File</p></td></tr></tbody></table><br><h4>6. Registration App</h4><p>In this section, we create registration app.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. StartApp Overview</p><p style='margin: 0'>Registration App: StartApp Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. StartSetup Project and Display Template</p><p style='margin: 0'>Registration App: StartSetup Project and Display Template</p></td></tr><tr><td style='padding: 15px;'><p>3. StartSetting Up the Models</p><p style='margin: 0'>Registration App: StartSetting Up the Models</p></td></tr><tr><td style='padding: 15px;'><p>4. StartSetup Database</p><p style='margin: 0'>Registration App: StartSetup Database</p></td></tr><tr><td style='padding: 15px;'><p>5. StartSeed Topic and Language Data</p><p style='margin: 0'>Registration App: StartSeed Topic and Language Data</p></td></tr><tr><td style='padding: 15px;'><p>6. StartSetup Password Hash</p><p style='margin: 0'>Registration App: StartSetup Password Hash</p></td></tr><tr><td style='padding: 15px;'><p>7. StartVerify Form Data is Being Submitted</p><p style='margin: 0'>Registration App: StartVerify Form Data is Being Submitted</p></td></tr><tr><td style='padding: 15px;'><p>8. StartLoad Languages and Topics</p><p style='margin: 0'>Registration App: StartLoad Languages and Topics</p></td></tr><tr><td style='padding: 15px;'><p>9. StartSave Data from Form</p><p style='margin: 0'>Registration App: StartSave Data from Form</p></td></tr><tr><td style='padding: 15px;'><p>10. StartLoad Existing Data</p><p style='margin: 0'>Registration App: StartLoad Existing Data</p></td></tr><tr><td style='padding: 15px;'><p>11. StartUpdate Database with New Data</p><p style='margin: 0'>Registration App: StartUpdate Database with New Data</p></td></tr><tr><td style='padding: 15px;'><p>12. StartError Handling</p><p style='margin: 0'>Registration App: StartError Handling</p></td></tr></tbody></table><br><h4>7. Registration API</h4><p>In this section, we work with registration API.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. StartPOSTMan</p><p style='margin: 0'>Registration API: StartPOSTMan</p></td></tr><tr><td style='padding: 15px;'><p>2. StartOrganize Files</p><p style='margin: 0'>Registration API: StartOrganize Files</p></td></tr><tr><td style='padding: 15px;'><p>3. StartAdd JSON to Method</p><p style='margin: 0'>Registration API: StartAdd JSON to Method</p></td></tr><tr><td style='padding: 15px;'><p>4. StartGet Members Route</p><p style='margin: 0'>Registration API: StartGet Members Route</p></td></tr><tr><td style='padding: 15px;'><p>5. StartGet One Member</p><p style='margin: 0'>Registration API: StartGet One Member</p></td></tr><tr><td style='padding: 15px;'><p>6. StartCreate Member</p><p style='margin: 0'>Registration API: StartCreate Member</p></td></tr><tr><td style='padding: 15px;'><p>7. StartEdit Member</p><p style='margin: 0'>Registration API: StartEdit Member</p></td></tr></tbody></table><br><h4>8. Dashboard App</h4><p>In this section, we create the DashBoard app.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. StartApp Overview</p><p style='margin: 0'>Dashboard App: StartApp Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. StartOverview of Templates</p><p style='margin: 0'>Dashboard App: StartOverview of Templates</p></td></tr><tr><td style='padding: 15px;'><p>3. StartSetup Flask App and Template</p><p style='margin: 0'>Dashboard App: StartSetup Flask App and Template</p></td></tr><tr><td style='padding: 15px;'><p>4. StartCreate Models for Dashboard</p><p style='margin: 0'>Dashboard App: StartCreate Models for Dashboard</p></td></tr><tr><td style='padding: 15px;'><p>5. StartCommand to Create Tables</p><p style='margin: 0'>Dashboard App: StartCommand to Create Tables</p></td></tr><tr><td style='padding: 15px;'><p>6. StartAdd Data into Database</p><p style='margin: 0'>Dashboard App: StartAdd Data into Database</p></td></tr><tr><td style='padding: 15px;'><p>7. StartOverview of Queries We Need</p><p style='margin: 0'>Dashboard App: StartOverview of Queries We Need</p></td></tr><tr><td style='padding: 15px;'><p>8. StartWriting the Queries</p><p style='margin: 0'>Dashboard App: StartWriting the Queries</p></td></tr><tr><td style='padding: 15px;'><p>9. StartWriting the Queries</p><p style='margin: 0'>Dashboard App: StartWriting the Queries</p></td></tr><tr><td style='padding: 15px;'><p>10. StartWriting the Queries</p><p style='margin: 0'>Dashboard App: StartWriting the Queries</p></td></tr><tr><td style='padding: 15px;'><p>11. StartWriting the Queries</p><p style='margin: 0'>Dashboard App: StartWriting the Queries</p></td></tr><tr><td style='padding: 15px;'><p>12. StartAdd the Card Values</p><p style='margin: 0'>Dashboard App: StartAdd the Card Values</p></td></tr><tr><td style='padding: 15px;'><p>13. StartAdd the Revenue Goals</p><p style='margin: 0'>Dashboard App: StartAdd the Revenue Goals</p></td></tr><tr><td style='padding: 15px;'><p>14. StartWork with the Area Chart</p><p style='margin: 0'>Dashboard App: StartWork with the Area Chart</p></td></tr><tr><td style='padding: 15px;'><p>15. StartWork with the Pie Chart</p><p style='margin: 0'>Dashboard App: StartWork with the Pie Chart</p></td></tr><tr><td style='padding: 15px;'><p>16. StartWork with Bar Chart</p><p style='margin: 0'>Dashboard App: StartWork with Bar Chart</p></td></tr><tr><td style='padding: 15px;'><p>17. StartFill in Order Table</p><p style='margin: 0'>Dashboard App: StartFill in Order Table</p></td></tr><tr><td style='padding: 15px;'><p>18. StartSetup Flask Login</p><p style='margin: 0'>Dashboard App: StartSetup Flask Login</p></td></tr><tr><td style='padding: 15px;'><p>19. StartProtecting the Routes</p><p style='margin: 0'>Dashboard App: StartProtecting the Routes</p></td></tr><tr><td style='padding: 15px;'><p>20. StartRegister a User</p><p style='margin: 0'>Dashboard App: StartRegister a User</p></td></tr><tr><td style='padding: 15px;'><p>21. StartLog In User</p><p style='margin: 0'>Dashboard App: StartLog In User</p></td></tr><tr><td style='padding: 15px;'><p>22. StartAdd Password Hashing</p><p style='margin: 0'>Dashboard App: StartAdd Password Hashing</p></td></tr><tr><td style='padding: 15px;'><p>23. StartLogout User</p><p style='margin: 0'>Dashboard App: StartLogout User</p></td></tr><tr><td style='padding: 15px;'><p>24. StartUpdate Links</p><p style='margin: 0'>Dashboard App: StartUpdate Links</p></td></tr><tr><td style='padding: 15px;'><p>25. StartAdd Current User Name</p><p style='margin: 0'>Dashboard App: StartAdd Current User Name</p></td></tr><tr><td style='padding: 15px;'><p>26. StartAdd Remember Me</p><p style='margin: 0'>Dashboard App: StartAdd Remember Me</p></td></tr><tr><td style='padding: 15px;'><p>27. StartFormat Numbers and Dates</p><p style='margin: 0'>Dashboard App: StartFormat Numbers and Dates</p></td></tr><tr><td style='padding: 15px;'><p>28. StartFix Pie Chart Colors</p><p style='margin: 0'>Dashboard App: StartFix Pie Chart Colors</p></td></tr><tr><td style='padding: 15px;'><p>29. StartForm Validation</p><p style='margin: 0'>Dashboard App: StartForm Validation</p></td></tr></tbody></table><br><h4>9. Course Outro</h4><p>Here, we summarize the course.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Outro</p><p style='margin: 0'>Course Outro: Outro</p></td></tr></tbody></table>

Programming

Learn Flask, the simple yet powerful Python web framework. This course is a ridiculously simple way to learn Flask in less than a weekend.

Flask for Beginners

<div id="course-pills-1">Duration<p>5 Days</p><p>30 CPD hours</p>This course is intended for<p></p><p>Students in this course are interested in Azure development or in passing the Microsoft Azure Developer Associate certification exam.</p><p></p><p></p><p>This course teaches developers how to create end-to-end solutions in Microsoft Azure. Students will learn how to implement Azure compute solutions, create Azure Functions, implement and manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization, and secure their solutions by using KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services and third-party services, and include event- and message-based models in their solutions. The course also covers monitoring, troubleshooting, and optimizing Azure solutions.</p><p></p>Prerequisites<p>To be successful in this course, learners should have the following: Hands-on experience with Azure IaaS and PaaS solutions, and the Azure Portal. Experience writing in an Azure supported language at the intermediate level. (C#, JavaScript, Python, or Java) Ability to write code to connect and perform operations on, a SQL or NoSQL database product. (SQL Server, Oracle, MongoDB, Cassandra or similar) Experience writing code to handle authentication, authorization, and other security principles at the intermediate level. A general understanding of HTML, the HTTP protocol and REST API interfaces.</p></div><div id="course-pills-2"><h3>1 - Explore Azure App Service</h3> <ul> <li>Examine Azure App Service</li> <li>Examine Azure App Service plans</li> <li>Deploy to App Service</li> <li>Explore authentication and authorization in App Service</li> <li>Discover App Service networking features</li> </ul> <h3>2 - Configure web app settings</h3> <ul> <li>Configure application settings</li> <li>Configure general settings</li> <li>Configure path mappings</li> <li>Enable diagnostic logging</li> <li>Configure security certificates</li> </ul> <h3>3 - Scale apps in Azure App Service</h3> <ul> <li>Examine autoscale factors</li> <li>Identify autoscale factors</li> <li>Enable autoscale in App Service</li> <li>Explore autoscale best practices</li> </ul> <h3>4 - Explore Azure App Service deployment slots</h3> <ul> <li>Explore staging environments</li> <li>Examine slot swapping</li> <li>Swap deployment slots</li> <li>Route traffic in App Service</li> </ul> <h3>5 - Explore Azure Functions</h3> <ul> <li>Discover Azure Functions</li> <li>Compare Azure Functions hosting options</li> <li>Scale Azure Functions</li> </ul> <h3>6 - Develop Azure Functions</h3> <ul> <li>Explore Azure Functions development</li> <li>Create triggers and bindings</li> <li>Connect functions to Azure services</li> </ul> <h3>7 - Explore Azure Blob storage</h3> <ul> <li>Explore Azure Blob storage</li> <li>Discover Azure Blob storage resource types</li> <li>Explore Azure Storage security features</li> <li>Discover static website hosting in Azure Storage</li> </ul> <h3>8 - Manage the Azure Blob storage lifecycle</h3> <ul> <li>Explore the Azure Blob storage lifecycle</li> <li>Discover Blob storage lifecycle policies</li> <li>Implement Blob storage lifecycle policies</li> <li>Rehydrate blob data from the archive tier</li> </ul> <h3>9 - Work with Azure Blob storage</h3> <ul> <li>Explore Azure Blob storage client library</li> <li>Create a client object</li> <li>Manage container properties and metadata by using .NET</li> <li>Set and retrieve properties and metadata for blob resources by using REST</li> </ul> <h3>10 - Explore Azure Cosmos DB</h3> <ul> <li>Identify key benefits of Azure Cosmos DB</li> <li>Explore the resource hierarchy</li> <li>Explore consistency levels</li> <li>Choose the right consistency level</li> <li>Explore supported APIs</li> <li>Discover request units</li> </ul> <h3>11 - Work with Azure Cosmos DB</h3> <ul> <li>Explore Microsoft .NET SDK v3 for Azure Cosmos DB</li> <li>Create stored procedures</li> <li>Create triggers and user-defined functions</li> <li>Explore change feed in Azure Cosmos DB</li> </ul> <h3>12 - Manage container images in Azure Container Registry</h3> <ul> <li>Discover the Azure Container Registry</li> <li>Explore storage capabilities</li> <li>Build and manage containers with tasks</li> <li>Explore elements of a Dockerfile</li> </ul> <h3>13 - Run container images in Azure Container Instances</h3> <ul> <li>Explore Azure Container Instances</li> <li>Run containerized tasks with restart policies</li> <li>Set environment variables in container instances</li> <li>Mount an Azure file share in Azure Container Instances</li> </ul> <h3>14 - Implement Azure Container Apps</h3> <ul> <li>Explore Azure Container Apps</li> <li>Explore containers in Azure Container Apps</li> <li>Implement authentication and authorization in Azure Container Apps</li> <li>Manage revisions and secrets in Azure Container Apps</li> <li>Explore Dapr integration with Azure Container Apps</li> </ul> <h3>15 - Explore the Microsoft identity platform</h3> <ul> <li>Explore the Microsoft identity platform</li> <li>Explore service principals</li> <li>Discover permissions and consent</li> <li>Discover conditional access</li> </ul> <h3>16 - Implement authentication by using the Microsoft Authentication Library</h3> <ul> <li>Explore the Microsoft Authentication Library</li> <li>Initialize client applications</li> </ul> <h3>17 - Implement shared access signatures</h3> <ul> <li>Discover shared access signatures</li> <li>Choose when to use shared access signatures</li> <li>Explore stored access policies</li> </ul> <h3>18 - Explore Microsoft Graph</h3> <ul> <li>Discover Microsoft Graph</li> <li>Query Microsoft Graph by using REST</li> <li>Query Microsoft Graph by using SDKs</li> <li>Apply best practices to Microsoft Graph</li> </ul> <h3>19 - Implement Azure Key Vault</h3> <ul> <li>Explore Azure Key Vault</li> <li>Discover Azure Key Vault best practices</li> <li>Authenticate to Azure Key Vault</li> </ul> <h3>20 - Implement managed identities</h3> <ul> <li>Explore managed identities</li> <li>Discover the managed identities authentication flow</li> <li>Configure managed identities</li> <li>Acquire an access token</li> </ul> <h3>21 - Implement Azure App Configuration</h3> <ul> <li>Explore the Azure App Configuration service</li> <li>Create paired keys and values</li> <li>Manage application features</li> <li>Secure app configuration data</li> </ul> <h3>22 - Explore API Management</h3> <ul> <li>Discover the API Management service</li> <li>Explore API gateways</li> <li>Explore API Management policies</li> <li>Create advanced policies</li> <li>Secure APIs by using subscriptions</li> <li>Secure APIs by using certificates</li> </ul> <h3>23 - Explore Azure Event Grid</h3> <ul> <li>Explore Azure Event Grid</li> <li>Discover event schemas</li> <li>Explore event delivery durability</li> <li>Control access to events</li> <li>Receive events by using webhooks</li> <li>Filter events</li> </ul> <h3>24 - Explore Azure Event Hubs</h3> <ul> <li>Discover Azure Event Hubs</li> <li>Explore Event Hubs Capture</li> <li>Scale your processing application</li> <li>Control access to events</li> <li>Perform common operations with the Event Hubs client library</li> </ul> <h3>25 - Discover Azure message queues</h3> <ul> <li>Choose a message queue solution</li> <li>Explore Azure Service Bus</li> <li>Discover Service Bus queues, topics, and subscriptions</li> <li>Explore Service Bus message payloads and serialization</li> <li>Explore Azure Queue Storage</li> <li>Create and manage Azure Queue Storage and messages by using .NET</li> </ul> <h3>26 - Monitor app performance</h3> <ul> <li>Explore Application Insights</li> <li>Discover log-based metrics</li> <li>Instrument an app for monitoring</li> <li>Select an availability test</li> <li>Troubleshoot app performance by using Application Map</li> </ul> <h3>27 - Develop for Azure Cache for Redis</h3> <ul> <li>Explore Azure Cache for Redis</li> <li>Configure Azure Cache for Redis</li> <li>Interact with Azure Cache for Redis by using .NET</li> </ul> <h3>28 - Develop for storage on CDNs</h3> <ul> <li>Explore Azure Content Delivery Networks</li> <li>Control cache behavior on Azure Content Delivery Networks</li> <li>Interact with Azure Content Delivery Networks by using .NET</li> </ul></div>

Nexus Human

Microsoft AZ-900

Microsoft AZ-104

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

AWS Certified Solutions Architect

AZ-204T00 Developing Solutions for Microsoft Azure

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure.</p><p></p><p></p><p>AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language.</p><p></p>Prerequisites<p>Before attending this course, students must have:  </p><li>Knowledge of Microsoft Azure and ability to navigate the Azure portal  </li><li>Knowledge of either C# or Python  </li><li>Familiarity with JSON and REST programming semantics  <br />  Recommended course prerequisites  </li><li>AI-900T00: Microsoft Azure AI Fundamentals course<p></p></li></div><div id="course-pills-2"><h3>1 - Prepare to develop AI solutions on Azure</h3> <ul> <li>Define artificial intelligence</li> <li>Understand AI-related terms</li> <li>Understand considerations for AI Engineers</li> <li>Understand considerations for responsible AI</li> <li>Understand capabilities of Azure Machine Learning</li> <li>Understand capabilities of Azure AI Services</li> <li>Understand capabilities of the Azure Bot Service</li> <li>Understand capabilities of Azure Cognitive Search</li> </ul> <h3>2 - Create and consume Azure AI services</h3> <ul> <li>Provision an Azure AI services resource</li> <li>Identify endpoints and keys</li> <li>Use a REST API</li> <li>Use an SDK</li> </ul> <h3>3 - Secure Azure AI services</h3> <ul> <li>Consider authentication</li> <li>Implement network security</li> </ul> <h3>4 - Monitor Azure AI services</h3> <ul> <li>Monitor cost</li> <li>Create alerts</li> <li>View metrics</li> <li>Manage diagnostic logging</li> </ul> <h3>5 - Deploy Azure AI services in containers</h3> <ul> <li>Understand containers</li> <li>Use Azure AI services containers</li> </ul> <h3>6 - Analyze images</h3> <ul> <li>Provision an Azure AI Vision resource</li> <li>Analyze an image</li> <li>Generate a smart-cropped thumbnail</li> </ul> <h3>7 - Classify images</h3> <ul> <li>Provision Azure resources for Azure AI Custom Vision</li> <li>Understand image classification</li> <li>Train an image classifier</li> </ul> <h3>8 - Detect, analyze, and recognize faces</h3> <ul> <li>Identify options for face detection analysis and identification</li> <li>Understand considerations for face analysis</li> <li>Detect faces with the Azure AI Vision service</li> <li>Understand capabilities of the face service</li> <li>Compare and match detected faces</li> <li>Implement facial recognition</li> </ul> <h3>9 - Read Text in images and documents with the Azure AI Vision Service</h3> <ul> <li>Explore Azure AI Vision options for reading text</li> <li>Use the Read API</li> </ul> <h3>10 - Analyze video</h3> <ul> <li>Understand Azure Video Indexer capabilities</li> <li>Extract custom insights</li> <li>Use Video Analyzer widgets and APIs</li> </ul> <h3>11 - Analyze text with Azure AI Language</h3> <ul> <li>Provision an Azure AI Language resource</li> <li>Detect language</li> <li>Extract key phrases</li> <li>Analyze sentiment</li> <li>Extract entities</li> <li>Extract linked entities</li> </ul> <h3>12 - Build a question answering solution</h3> <ul> <li>Understand question answering</li> <li>Compare question answering to Azure AI Language understanding</li> <li>Create a knowledge base</li> <li>Implement multi-turn conversation</li> <li>Test and publish a knowledge base</li> <li>Use a knowledge base</li> <li>Improve question answering performance</li> </ul> <h3>13 - Build a conversational language understanding model</h3> <ul> <li>Understand prebuilt capabilities of the Azure AI Language service</li> <li>Understand resources for building a conversational language understanding model</li> <li>Define intents, utterances, and entities</li> <li>Use patterns to differentiate similar utterances</li> <li>Use pre-built entity components</li> <li>Train, test, publish, and review a conversational language understanding model</li> </ul> <h3>14 - Create a custom text classification solution</h3> <ul> <li>Understand types of classification projects</li> <li>Understand how to build text classification projects</li> </ul> <h3>15 - Create a custom named entity extraction solution</h3> <ul> <li>Understand custom named entity recognition</li> <li>Label your data</li> <li>Train and evaluate your model</li> </ul> <h3>16 - Translate text with Azure AI Translator service</h3> <ul> <li>Provision an Azure AI Translator resource</li> <li>Specify translation options</li> <li>Define custom translations</li> </ul> <h3>17 - Create speech-enabled apps with Azure AI services</h3> <ul> <li>Provision an Azure resource for speech</li> <li>Use the Azure AI Speech to Text API</li> <li>Use the text to speech API</li> <li>Configure audio format and voices</li> <li>Use Speech Synthesis Markup Language</li> </ul> <h3>18 - Translate speech with the Azure AI Speech service</h3> <ul> <li>Provision an Azure resource for speech translation</li> <li>Translate speech to text</li> <li>Synthesize translations</li> </ul> <h3>19 - Create an Azure AI Search solution</h3> <ul> <li>Manage capacity</li> <li>Understand search components</li> <li>Understand the indexing process</li> <li>Search an index</li> <li>Apply filtering and sorting</li> <li>Enhance the index</li> </ul> <h3>20 - Create a custom skill for Azure AI Search</h3> <ul> <li>Create a custom skill</li> <li>Add a custom skill to a skillset</li> </ul> <h3>21 - Create a knowledge store with Azure AI Search</h3> <ul> <li>Define projections</li> <li>Define a knowledge store</li> </ul> <h3>22 - Plan an Azure AI Document Intelligence solution</h3> <ul> <li>Understand AI Document Intelligence</li> <li>Plan Azure AI Document Intelligence resources</li> <li>Choose a model type</li> </ul> <h3>23 - Use prebuilt Azure AI Document Intelligence models</h3> <ul> <li>Understand prebuilt models</li> <li>Use the General Document, Read, and Layout models</li> <li>Use financial, ID, and tax models</li> </ul> <h3>24 - Extract data from forms with Azure Document Intelligence</h3> <ul> <li>What is Azure Document Intelligence?</li> <li>Get started with Azure Document Intelligence</li> <li>Train custom models</li> <li>Use Azure Document Intelligence models</li> <li>Use the Azure Document Intelligence Studio</li> </ul> <h3>25 - Get started with Azure OpenAI Service</h3> <ul> <li>Access Azure OpenAI Service</li> <li>Use Azure OpenAI Studio</li> <li>Explore types of generative AI models</li> <li>Deploy generative AI models</li> <li>Use prompts to get completions from models</li> <li>Test models in Azure OpenAI Studio's playgrounds</li> </ul> <h3>26 - Build natural language solutions with Azure OpenAI Service</h3> <ul> <li>Integrate Azure OpenAI into your app</li> <li>Use Azure OpenAI REST API</li> <li>Use Azure OpenAI SDK</li> </ul> <h3>27 - Apply prompt engineering with Azure OpenAI Service</h3> <ul> <li>Understand prompt engineering</li> <li>Write more effective prompts</li> <li>Provide context to improve accuracy</li> </ul> <h3>28 - Generate code with Azure OpenAI Service</h3> <ul> <li>Construct code from natural language</li> <li>Complete code and assist the development process</li> <li>Fix bugs and improve your code</li> </ul> <h3>29 - Generate images with Azure OpenAI Service</h3> <ul> <li>What is DALL-E?</li> <li>Explore DALL-E in Azure OpenAI Studio</li> <li>Use the Azure OpenAI REST API to consume DALL-E models</li> </ul> <h3>30 - Use your own data with Azure OpenAI Service</h3> <ul> <li>Understand how to use your own data</li> <li>Add your own data source</li> <li>Chat with your model using your own data</li> </ul> <h3>31 - Fundamentals of Responsible Generative AI</h3> <ul> <li>Plan a responsible generative AI solution</li> <li>Identify potential harms</li> <li>Measure potential harms</li> <li>Mitigate potential harms</li> <li>Operate a responsible generative AI solution</li> </ul></div>

Azure Machine Learning

Microsoft AI-900

Azure Cognitive Services

AI-102T00 Designing and Implementing an Azure AI Solution

"Start your career as a Certified Python Programmer and earn up to £70,000 per Year."
Are you looking to make your mark in the ever-evolving world of Data Analyst? The demand for Python programmers has never been higher. Just in the UK, job postings for Analysts / Python programmers surged by an astounding 70% in 2022. This exponential growth trend signifies the soaring need for skilled Python programmers. Amid this vibrant job market, our Python Programmer online Training is your golden ticket to a prosperous career in programming or Data Analysis. Regardless of your level - beginner or expert - we ensure a comprehensive learning experience that will enhance your current skills and prepare you for the dynamic tech industry.
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Course 01: Computer Science With Python
Course 02: Ultimate Python Training for Beginners
Course 03: Python Intermediate Training
Course 04: Python Advanced Training
Course 05: Deep Learning & Neural Networks Python - Keras
Course 06: Complete Python Machine Learning & Data Science Fundamentals
Course 06: Introduction to Data Analysis
Course 07: Business and Data Analytics for Beginners
Course 08: Data Analytics with Tableau
Course 09: Quick Data Science Approach from Scratch
Course 10: Learn MySQL from Scratch for Data Science and Analytics
Course 11: SQL for Data Science, Data Analytics and Data Visualization
Course 12: Statistics & Probability for Data Science & Machine Learning
Course 13: Basic Google Data Studio
Course 14: Machine Learning with Python Course
Course 15: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 16: Web Scraping and Mapping Dam Levels in Python and Leaflet
Course 17: Coding Essentials - Javascript, ASP. Net, C#
Course 19: Master JavaScript with Data Visualization
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Begin your exciting journey with us by enrolling in the Python Certification Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
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Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.
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After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.
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We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.
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With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.
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Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.
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Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.
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Once you've secured your dream job in Python Programming, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Python Programming begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
This Python Certification Course is suitable for:
Beginners with no prior programming experience who are looking to enter the world of coding.
Intermediate programmers who wish to expand their skills and explore Python's extensive usage.
IT professionals seeking to diversify their skill sets and stay relevant in today's tech-driven market.
Data analysts and scientists who want to leverage Python's powerful libraries for their data processing needs.
Students and recent graduates looking to enhance their employability in the thriving tech industry.
Entrepreneurs who wish to understand and utilise Python to automate tasks and analyse data for their businesses.
Anyone with a keen interest in Python programming and a desire to delve into its applications in diverse fields like web development, data science, machine learning, and more.
 Requirements 
No experience required. Just enrol & start learning python.
 Career path 
Upon completion of our Program, the potential career paths include:
Python Developer: £30,000 - £90,000 annually
Data Scientist: £40,000 - £100,000 annually
Machine Learning Engineer: £50,000 - £110,000 annually
Data Analyst: £35,000 - £85,000 annually
Software Engineer: £35,000 - £95,000 annually
Back-end Developer: £40,000 - £95,000 annually
Web Developer: £30,000 -£85,000 annually
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Academy for Health and Fitness

Programming Fundamentals

Career Development

IT Certifications

Become an IT professional with our Python Certification - IT Job Ready Program! Gain comprehensive skills in Python programming, data analysis, and automation. We offer a money-back guarantee if you don't secure a job within six months of completion. Enroll now and jumpstart your tech career!


Ready to land your dream job in tech? Our Python Certification - IT Job Ready Program equips you with essential Python programming, data analysis, and automation skills. Plus, we offer a money-back guarantee if you don't get hired within six months of completing the course. Don't miss out – enroll today and take the first step towards a successful IT career! 💻📊 #PythonCertification #TechTraining #CareerReady #MoneyBackGuarantee

Python Certification - IT Job Ready Program with Money Back Guarantee

<strong>Learn Python Programming the Easy Way, Complete with Examples, Quizzes, Exercises and more. Learn Python 2 and Python 3.</strong>
        <p>This course will teach you Python in a practical manner, complete with examples, quizzes, exercises, and more. You will learn when to use Python 2 and Python 3; both versions are covered in the course and you will learn to program in both. You'll learn how to take tedious and repetitious tasks and turn them into programs that will save you time and simplify your life on Linux, UNIX, or MAC systems. You will learn how to prepare your computer for programming in Python; how to work with various data types including strings, lists, tuples, dictionaries, Booleans; how to perform mathematical operations using Python, and more.</p>
        <h2>What You Will Learn</h2><p>When to use Python 2 and when to use Python 3.<br>How to install Python on Windows, Mac, and Linux.<br>How to prepare your computer for programming in Python.<br>The various ways to run a Python program on Windows, Mac, and Linux.<br>Suggested text editors and Integrated Development Environments to use when coding in Python.<br>How to work with various data types including strings, lists, tuples, dictionaries, Booleans, and more.<br>What variables are and when to use them.<br>How to perform mathematical operations using Python.<br>How to capture input from a user.<br>Ways to control the flow of your programs.<br>The importance of white space in Python.<br>How to organize your Python programs: learn what goes where.<br>What modules are, when you should use them, and how to create your own.<br>How to define and use functions.<br>Important built-in Python functions that you ll use often.<br>How to read from and write to files.<br>The difference between binary and text files.<br>Various ways of getting help, including finding Python documentation.<br></p>
        <h2>Audience</h2><p>This course targets anyone interested in Python programming, Python scripting, or computer programming in general; those who want to become a highly paid Python developer; and those who want to open up doors in their IT career by learning one of the world's most popular and in-demand programming languages.</p>
        <h2>Approach</h2><p>A complete course packed with step-by-step instructions, practice exercises with solutions, and quizzes. This course is clearly divided into small parts to help you understand each part individually and learn at your own pace. Once you've completed this course you'll know how to write programs that will run on the Linux, Mac, and Windows operating systems. You can even take what you've learned and apply it to web applications. </p>
        <h2>Key Features</h2><p>How to install Python on Windows, Mac, and Linux. * A practical tutorial designed for Python beginners. * </p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/python-for-beginners-learn-python-programming-python-3-</p>
        <h2>About the Author</h2><h3>Jason Cannon</h3><p>Jason Cannon is a professional system administrator, consultant, and author. He started his career as a Unix and Linux System engineer in 1999. Since that time, he has utilized his Linux skills at companies such as Xerox, UPS, Hewlett-Packard, and Amazon.com. Additionally, he has acted as a technical consultant and independent contractor for small businesses and Fortune 500 companies.

Jason has professional experience with CentOS, RedHat Enterprise Linux, SUSE Linux Enterprise Server, and Ubuntu. He has used several Linux distributions on personal projects including Debian, Slackware, CrunchBang, and others. In addition to Linux, Jason has experience supporting proprietary Unix operating systems including AIX, HP-UX, and Solaris. He enjoys teaching others how to use and exploit the power of the Linux operating system.</p>
        <h2>Course Outline</h2><h4>1. Course Overview and Downloads</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course Overview</p><p style='margin: 0'>Course Overview and Downloads: Course Overview</p></td></tr></tbody></table><br><h4>2. Python Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Python 2 vs Python 3</p><p style='margin: 0'>Python Setup: Python 2 vs Python 3</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing Python on Windows</p><p style='margin: 0'>Python Setup: Installing Python on Windows</p></td></tr><tr><td style='padding: 15px;'><p>3. Installing Python on Mac</p><p style='margin: 0'>Python Setup: Installing Python on Mac</p></td></tr><tr><td style='padding: 15px;'><p>4. Installing Python on Linux</p><p style='margin: 0'>Python Setup: Installing Python on Linux</p></td></tr><tr><td style='padding: 15px;'><p>5. Writing Python Programs</p><p style='margin: 0'>Python Setup: Writing Python Programs</p></td></tr><tr><td style='padding: 15px;'><p>6. Running Python Programs</p><p style='margin: 0'>Python Setup: Running Python Programs</p></td></tr></tbody></table><br><h4>3. Strings and Variables</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Strings and Variables: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Variables and Strings</p><p style='margin: 0'>Strings and Variables: Variables and Strings</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions and Printing</p><p style='margin: 0'>Strings and Variables: Functions and Printing</p></td></tr><tr><td style='padding: 15px;'><p>4. String Methods</p><p style='margin: 0'>Strings and Variables: String Methods</p></td></tr><tr><td style='padding: 15px;'><p>5. String Concatenation</p><p style='margin: 0'>Strings and Variables: String Concatenation</p></td></tr><tr><td style='padding: 15px;'><p>6. Formatting Strings</p><p style='margin: 0'>Strings and Variables: Formatting Strings</p></td></tr><tr><td style='padding: 15px;'><p>7. Section Summary</p><p style='margin: 0'>Strings and Variables: Section Summary</p></td></tr><tr><td style='padding: 15px;'><p>8. Solutions to the Practice Exercises - #1 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #1 - Video</p></td></tr><tr><td style='padding: 15px;'><p>9. Solutions to the Practice Exercises - #2 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #2 - Video</p></td></tr><tr><td style='padding: 15px;'><p>10. Solutions to the Practice Exercises - #3 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #3 - Video</p></td></tr></tbody></table><br><h4>4. Numbers and Math</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Numbers and Math: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Numbers, Numeric Operations, and Numeric Functions</p><p style='margin: 0'>Numbers and Math: Numbers, Numeric Operations, and Numeric Functions</p></td></tr><tr><td style='padding: 15px;'><p>3. Comments</p><p style='margin: 0'>Numbers and Math: Comments</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Numbers and Math: Section Summary</p></td></tr></tbody></table><br><h4>5. Booleans and Conditionals</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Booleans and Conditionals: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Booleans</p><p style='margin: 0'>Booleans and Conditionals: Booleans</p></td></tr><tr><td style='padding: 15px;'><p>3. Conditionals</p><p style='margin: 0'>Booleans and Conditionals: Conditionals</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Booleans and Conditionals: Section Summary</p></td></tr></tbody></table><br><h4>6. Functions</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Functions: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Functions, Part I</p><p style='margin: 0'>Functions: Functions, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions, Part II</p><p style='margin: 0'>Functions: Functions, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Functions: Section Summary</p></td></tr></tbody></table><br><h4>7. Lists</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Lists: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Lists</p><p style='margin: 0'>Lists: Lists</p></td></tr><tr><td style='padding: 15px;'><p>3. Slices</p><p style='margin: 0'>Lists: Slices</p></td></tr><tr><td style='padding: 15px;'><p>4. Exception Handling</p><p style='margin: 0'>Lists: Exception Handling</p></td></tr><tr><td style='padding: 15px;'><p>5. Loops</p><p style='margin: 0'>Lists: Loops</p></td></tr><tr><td style='padding: 15px;'><p>6. Sorting and Ranges</p><p style='margin: 0'>Lists: Sorting and Ranges</p></td></tr><tr><td style='padding: 15px;'><p>7. Section Summary</p><p style='margin: 0'>Lists: Section Summary</p></td></tr></tbody></table><br><h4>8. Dictionaries</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Dictionaries: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Dictionaries - Part I</p><p style='margin: 0'>Dictionaries: Dictionaries - Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Dictionaries - Part II</p><p style='margin: 0'>Dictionaries: Dictionaries - Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Dictionaries: Section Summary</p></td></tr></tbody></table><br><h4>9. Tuples</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Tuples: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Tuples</p><p style='margin: 0'>Tuples: Tuples</p></td></tr><tr><td style='padding: 15px;'><p>3. Section Summary</p><p style='margin: 0'>Tuples: Section Summary</p></td></tr></tbody></table><br><h4>10. Files</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Files: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Files, Part I</p><p style='margin: 0'>Files: Files, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Files, Part II</p><p style='margin: 0'>Files: Files, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Files: Section Summary</p></td></tr></tbody></table><br><h4>11. Modules</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Modules: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Modules, Part I</p><p style='margin: 0'>Modules: Modules, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Modules, Part II</p><p style='margin: 0'>Modules: Modules, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Overview</p><p style='margin: 0'>Modules: Section Overview</p></td></tr></tbody></table>

Learn Python Programming the Easy Way, Complete with Examples, Quizzes, Exercises and more. Learn Python 2 and Python 3.

Python for Beginners: Learn Python Programming (Python 3)

<p><strong>Start your career as a Data Analyst and earn upto £35,000/ Month </strong></p><p>Have you ever imagined commanding a six-figure salary with the power of Python? Welcome to the "Data Analyst with Python - Job Ready Program with Career Support", where the world of big data is at your fingertips, and the only limit is your own curiosity. Explore the revolutionary journey that is geared towards turning raw data into insightful decisions. Our comprehensive program paves the way to becoming a sought-after Data Analyst, unlocking the door to a thriving career field as Python continues to spearhead the data revolution.</p><p><strong>Our mission is simple</strong> - to be your trusted partner every step of the way, from training to employment.</p><p>In addition to teaching you the technical skills you need, we will also provide you with <strong>career mentoring and support</strong>. We will help you build your resume, prepare for interviews, and land your <strong>dream job</strong>. We also have<strong> partnerships with many companies</strong> that are hiring Data Analysts with Python expertise, so we can help you get your foot in the door.</p><p>If you are not happy with our service, we also offer a <strong>100% money-back guarantee</strong>. So what are you waiting for? Enrol in our Data Analyst with Python - Job Ready Program today and start your journey to becoming a successful Data Analyst!</p><p><strong>Why Choose Us?</strong></p><p>So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Analyst with Python Job Ready Program:</p><ul><li><strong>Personalised Guidance:</strong> Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some experience, we will guide you towards honing your skills and developing a strong foundation in Data Analysis with Python.<br /><br /></li><li><strong>One-On-One Consultation Sessions with Experts:</strong> Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Analyst field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.<br /><br /></li><li><strong>Extensive Job Opportunities:</strong> We have established partnerships with numerous companies actively seeking IT Helpdesk Support. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere. <br /><br /></li><li><strong>Interview Preparation:</strong> We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.<br /><br /></li><li><strong>Money-Back Guarantee:</strong> Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee.<br /><br /></li><li><strong>Continuous Career Support: </strong>Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance. .</li></ul><p>If you have any questions, you can <strong>contact us</strong>. We will be happy to provide you with all the information you need.</p><p><strong>Here are the courses we will provide once you enrol in the program:</strong></p><ul><li>Course 01: Business and Data Analytics for Beginners</li><li>Course 02: Quick Data Science Approach from Scratch</li><li>Course 03: Learn MySQL from Scratch for Data Science and Analytics</li><li>Course 04: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 05: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>Course 06: R Programming for Data Science</li><li>Course 07: Python Data Science with Numpy, Pandas and Matplotlib</li><li>Course 08: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li>Course 09: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li>Course 10: Python from Scratch</li><li>Course 11: Level 2 Python Course</li><li>Course 12: Machine Learning for Predictive Maps in Python and Leaflet</li><li>Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li>Course 14: Python for Spatial Analysis in ArcGIS</li><li>Course 15: Ultimate Python Training for Beginners</li><li>Course 16: Python Level 1 Crash Course</li><li>Course 17: Python Programming from Scratch with My SQL Database</li></ul><p>These courses will help you to develop your knowledge and skills to become a <strong>successful Data Analyst</strong>.</p><p><strong>How Can We Offer Job Guarantees?</strong></p><p>HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.</p> <p><strong>The Data Analyst with Python Program is completed in 9 easy steps:</strong></p><p><strong>Step 1: Enrol in the Programme</strong></p><p>Begin your exciting journey with us by enrolling in the Data Analyst with Python program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.</p><p>After you enrol in the Program, you will get lifetime access to 17 premium courses related to Data Analysis with Python. These courses will teach you the knowledge and skills required to become a successful Data Analyst with Python Programmer. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!</p><p><strong>Step 2: Initial One-On-One Counselling Session</strong></p><p>Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.</p><p><strong>Step 3: </strong><strong>Certification upon Course Completion</strong></p><p>After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.</p><p><strong>Step 4: </strong><strong>CV Revamping</strong></p><p>Our team of professionals will build you a compelling CV and <strong>LinkedIn profile</strong>. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Finance industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.</p><p><strong>Step 5: Building Network and Submitting CV</strong></p><p>We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many<strong> high-profile individuals and companies</strong> through your LinkedIn profile.</p><p><strong>Step 6: Interview Preparation</strong></p><p>With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.</p><p><strong>Step 7: Securing Job Interviews</strong></p><p>Leveraging our partnerships with leading companies, <strong>we'll secure job interviews for you</strong>. We'll ensure you get the opportunity to showcase your skills to potential employers and <strong>get the dream job you want</strong>.</p><p><strong>Step 8: Post-Interview Support</strong></p><p>Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.</p><p><strong>Step 9: Celebrate Your New Job!</strong></p><p>Once you've secured your dream job in Data Analysis with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.</p><p>We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Analysis with Python begins with us.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        100 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This course is tailored to suit a broad spectrum of learners, including:</p><ul><li>Aspiring Data Analysts who want to launch a new career in data analytics.</li><li>Current analysts or professionals from similar fields looking to hone their Python skills and modernise their toolset.</li><li>Business and IT students or recent graduates desiring a competitive edge in the job market.</li><li>Career shifters interested in a more dynamic and high-paying field.</li><li>Any individual who loves working with numbers, solving problems, and has a curiosity for uncovering insights in data.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>No experience required. Just enrol &amp; start learning.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li><strong>Data Analyst</strong>: £27,000 - £60,000</li><li><strong>Senior Data Analyst</strong>: £40,000 - £75,000</li><li><strong>Data Scientist</strong>: £50,000 - £100,000</li><li><strong>Data Engineer</strong>: £45,000 - £90,000</li><li><strong>Analytics Manager</strong>: £60,000 - £120,000</li><li><strong>Director of Data Science</strong>: £90,000 - £150,000</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited e-Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Framed (Hardcopy) Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Enrolment Letter</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>QLS Endorsed Hard Copy Certificate </h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Student ID Card</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Start your career as a Data Analyst and earn upto £35,000/ Month 
Have you ever imagined commanding a six-figure salary with the power of Python? Welcome to the "Data Analyst with Python - Job Ready Program with Career Support", where the world of big data is at your fingertips, and the only limit is your own curiosity. Explore the revolutionary journey that is geared towards turning raw data into insightful decisions. Our comprehensive program paves the way to becoming a sought-after Data Analyst, unlocking the door to a thriving career field as Python continues to spearhead the data revolution.
Our mission is simple - to be your trusted partner every step of the way, from training to employment.
In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Data Analysts with Python expertise, so we can help you get your foot in the door.
If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Data Analyst with Python - Job Ready Program today and start your journey to becoming a successful Data Analyst!
Why Choose Us?
So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Analyst with Python Job Ready Program:
Personalised Guidance: Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some experience, we will guide you towards honing your skills and developing a strong foundation in Data Analysis with Python.
One-On-One Consultation Sessions with Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Analyst field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.
Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking IT Helpdesk Support. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.
Interview Preparation: We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.
Money-Back Guarantee: Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee.
Continuous Career Support: Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance. .
If you have any questions, you can contact us. We will be happy to provide you with all the information you need.
Here are the courses we will provide once you enrol in the program:
Course 01: Business and Data Analytics for Beginners
Course 02: Quick Data Science Approach from Scratch
Course 03: Learn MySQL from Scratch for Data Science and Analytics
Course 04: SQL for Data Science, Data Analytics and Data Visualization
Course 05: Statistics & Probability for Data Science & Machine Learning
Course 06: R Programming for Data Science
Course 07: Python Data Science with Numpy, Pandas and Matplotlib
Course 08: Complete Python Machine Learning & Data Science Fundamentals
Course 09: 2021 Data Science & Machine Learning with R from A-Z
Course 10: Python from Scratch
Course 11: Level 2 Python Course
Course 12: Machine Learning for Predictive Maps in Python and Leaflet
Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 14: Python for Spatial Analysis in ArcGIS
Course 15: Ultimate Python Training for Beginners
Course 16: Python Level 1 Crash Course
Course 17: Python Programming from Scratch with My SQL Database
These courses will help you to develop your knowledge and skills to become a successful Data Analyst.
How Can We Offer Job Guarantees?
HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
The Data Analyst with Python Program is completed in 9 easy steps:
Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Data Analyst with Python program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 17 premium courses related to Data Analysis with Python. These courses will teach you the knowledge and skills required to become a successful Data Analyst with Python Programmer. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
Step 2: Initial One-On-One Counselling Session
Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.
Step 3: Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.
Step 4: CV Revamping
Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Finance industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.
Step 5: Building Network and Submitting CV
We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.
Step 6: Interview Preparation
With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.
Step 7: Securing Job Interviews
Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.
Step 8: Post-Interview Support
Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.
Step 9: Celebrate Your New Job!
Once you've secured your dream job in Data Analysis with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Analysis with Python begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
This course is tailored to suit a broad spectrum of learners, including:
Aspiring Data Analysts who want to launch a new career in data analytics.
Current analysts or professionals from similar fields looking to hone their Python skills and modernise their toolset.
Business and IT students or recent graduates desiring a competitive edge in the job market.
Career shifters interested in a more dynamic and high-paying field.
Any individual who loves working with numbers, solving problems, and has a curiosity for uncovering insights in data.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Analyst: £27,000 - £60,000
Senior Data Analyst: £40,000 - £75,000
Data Scientist: £50,000 - £100,000
Data Engineer: £45,000 - £90,000
Analytics Manager: £60,000 - £120,000
Director of Data Science: £90,000 - £150,000
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Business Analytics & Intelligence

Data Engineering

Big Data Analytics

Data Skills

Data Analyst

Data Analyst with Python Job Ready Program with Career Support & Money Back Guarantee

<p><strong>Start your career in Data Science and earn up to £90,000 per month.</strong></p><p>Are you eager to dive into the high-speed world of Data Science powered by Python? In the UK alone, Data Scientist job postings witnessed a dramatic increase of 67% in 2022, emphasising the burgeoning demand for proficient Python programmers. Amid such a dynamic job market, our online course - Data Science with Python, serves as your stepping-stone to a universe of opportunities. Whether you're taking your first step into the realm of Data Science or aiming to augment your existing skills, our program offers peerless support, ensuring you're industry-ready by the time you complete our course.</p><p><strong>Our mission is simple</strong> - to be your trusted partner every step of the way, from training to employment.</p><p>In addition to teaching you the technical skills you need, we will also provide you with <strong>career mentoring and support</strong>. We will help you build your resume, prepare for interviews, and land your <strong>dream job</strong>. We also have<strong> partnerships with many companies</strong> that are hiring Data <strong>Scientists</strong>, so we can help you get your foot in the door.</p><p>If you are not happy with our service, we also offer a <strong>100% money-back guarantee</strong>. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!</p><p>If you have any questions, you can <strong>contact us</strong>. We will be happy to provide you with all the information you need.</p><p><strong>Why Choose Us?</strong></p><p>So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:</p><ul><li><strong>Personalised Guidance:</strong> We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in both Data Science and Python.<br /><br /></li><li><strong>One-On-One Consultation Sessions with Industry Experts:</strong> Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.<br /><br /></li><li><strong>Extensive Job Opportunities:</strong> We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.<br /><br /></li><li><strong>Interview Preparation:</strong> No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.<br /><br /></li><li><strong>Money-Back Guarantee:</strong> Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a <strong>100% money-back guarantee. </strong>If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. We believe in the value we provide and want you to feel completely satisfied with your decision to join us.<br /><br /></li><li><strong>Continuous Career Support: </strong>Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance.</li></ul><p><strong>Here are the courses we will provide once you enrol in the program:</strong></p><ul><li>Course 01: Business and Data Analytics for Beginners</li><li>Course 02: Quick Data Science Approach from Scratch</li><li>Course 03: Learn MySQL from Scratch for Data Science and Analytics</li><li>Course 04: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 05: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>Course 06: R Programming for Data Science</li><li>Course 07: Python Data Science with Numpy, Pandas and Matplotlib</li><li>Course 08: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li>Course 09: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li>Course 10: Python Programming from Scratch with My SQL Database</li><li>Course 11: Level 2 Python Course</li><li>Course 12: Machine Learning for Predictive Maps in Python and Leaflet</li><li>Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li>Course 14: Python for Spatial Analysis in ArcGIS</li><li>Course 15: Ultimate Python Training for Beginners</li><li>Course 16: PyScript Fundamentals Training</li></ul><p><strong>How Can We Offer Job Guarantees?</strong></p><p>HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.</p> <p><strong>The </strong><strong>Data Scientist with Python </strong><strong>Program is completed in 9 easy steps:<br /><br /></strong></p><p><strong>Step 1: Enrol in the Programme</strong></p><p>Begin your exciting journey with us by enrolling in the Data Science with Python Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.</p><p>After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Science with Python. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!</p><p><strong>Step 2: Initial One-On-One Counselling Session</strong></p><p>Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.<br /><br /></p><p><strong>Step 3 - </strong><strong>Certification upon Course Completion</strong></p><p>After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.<br /><br /></p><p><strong>Step 4: </strong><strong>CV Revamping</strong></p><p>Our team of professionals will build you a compelling CV and <strong>LinkedIn profile</strong>. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Science with Python industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. <br /><br /></p><p><strong>Step 5: Building Network and Submitting CV</strong></p><p>We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many<strong> high-profile individuals and companies</strong> through your LinkedIn profile.<br /><br /></p><p><strong>Step 6: Interview Preparation</strong></p><p>With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.<br /><br /></p><p><strong>Step 7: Securing Job Interviews</strong></p><p>Leveraging our partnerships with leading companies, <strong>we'll secure job interviews for you</strong>. We'll ensure you get the opportunity to showcase your skills to potential employers and <strong>get the dream job you want</strong>.<br /><br /></p><p><strong>Step 8: Post-Interview Support</strong></p><p>Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.<br /><br /></p><p><strong>Step 9: Celebrate Your New Job!</strong></p><p>Once you've secured your dream job in Data Science with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.</p><p>We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science with Python begins with us.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        100 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <ul><li>Beginners with an interest in Data Science and Python programming.</li><li>Programmers and Software Engineers looking to transition into Data Science.</li><li>Business Analysts and Project Managers aiming to leverage Data Science in their domains.</li><li>Researchers and Academics who wish to utilise Python for complex data analysis.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>No experience required. Just enrol &amp; start learning.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Scientist: £60,000 - £90,000</li><li>Machine Learning Engineer: £65,000 - £100,000</li><li>Data Analyst: £40,000 - £60,000</li><li>Business Intelligence Analyst: £45,000 - £70,000</li><li>Data Engineer: £50,000 - £80,000</li><li>Big Data Architect: £70,000 - £120,000</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited e-Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Framed (Hardcopy) Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Enrolment Letter</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>QLS Endorsed Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Student ID Card</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Start your career in Data Science and earn up to £90,000 per month.
Are you eager to dive into the high-speed world of Data Science powered by Python? In the UK alone, Data Scientist job postings witnessed a dramatic increase of 67% in 2022, emphasising the burgeoning demand for proficient Python programmers. Amid such a dynamic job market, our online course - Data Science with Python, serves as your stepping-stone to a universe of opportunities. Whether you're taking your first step into the realm of Data Science or aiming to augment your existing skills, our program offers peerless support, ensuring you're industry-ready by the time you complete our course.
Our mission is simple - to be your trusted partner every step of the way, from training to employment.
In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Data Scientists, so we can help you get your foot in the door.
If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!
If you have any questions, you can contact us. We will be happy to provide you with all the information you need.
Why Choose Us?
So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:
Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in both Data Science and Python.
One-On-One Consultation Sessions with Industry Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.
Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.
Interview Preparation: No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.
Money-Back Guarantee: Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee. If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. We believe in the value we provide and want you to feel completely satisfied with your decision to join us.
Continuous Career Support: Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance.
Here are the courses we will provide once you enrol in the program:
Course 01: Business and Data Analytics for Beginners
Course 02: Quick Data Science Approach from Scratch
Course 03: Learn MySQL from Scratch for Data Science and Analytics
Course 04: SQL for Data Science, Data Analytics and Data Visualization
Course 05: Statistics & Probability for Data Science & Machine Learning
Course 06: R Programming for Data Science
Course 07: Python Data Science with Numpy, Pandas and Matplotlib
Course 08: Complete Python Machine Learning & Data Science Fundamentals
Course 09: 2021 Data Science & Machine Learning with R from A-Z
Course 10: Python Programming from Scratch with My SQL Database
Course 11: Level 2 Python Course
Course 12: Machine Learning for Predictive Maps in Python and Leaflet
Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 14: Python for Spatial Analysis in ArcGIS
Course 15: Ultimate Python Training for Beginners
Course 16: PyScript Fundamentals Training
How Can We Offer Job Guarantees?
HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
The Data Scientist with Python Program is completed in 9 easy steps:


Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Data Science with Python Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Science with Python. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
Step 2: Initial One-On-One Counselling Session
Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.


Step 3 - Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.


Step 4: CV Revamping
Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Science with Python industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. 


Step 5: Building Network and Submitting CV
We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.


Step 6: Interview Preparation
With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.


Step 7: Securing Job Interviews
Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.


Step 8: Post-Interview Support
Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.


Step 9: Celebrate Your New Job!
Once you've secured your dream job in Data Science with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science with Python begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Beginners with an interest in Data Science and Python programming.
Programmers and Software Engineers looking to transition into Data Science.
Business Analysts and Project Managers aiming to leverage Data Science in their domains.
Researchers and Academics who wish to utilise Python for complex data analysis.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Scientist: £60,000 - £90,000
Machine Learning Engineer: £65,000 - £100,000
Data Analyst: £40,000 - £60,000
Business Intelligence Analyst: £45,000 - £70,000
Data Engineer: £50,000 - £80,000
Big Data Architect: £70,000 - £120,000
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Data Science with Python - IT Job Ready Program with Career Support & Money Back Guarantee

<strong>You will master the fundamentals and more advanced principles of Python programming in this beginner's tutorial. This Python course covers every Python fundamental, including installation and more complex material such as Python data science.</strong>
        <p>'Python is the future of artificial intelligence and machine learning.'-Adrian Rosebrock, author.

Python is the programming language most loved by developers, data scientists, software engineers, and even hackers.

This Python basic to advanced course covers the fundamental concepts of Python programming and ways to apply this to real-world applications. The course modules, lesson-end quizzes, and lesson-end projects collectively cover the training course topics such as data operations, strings, file I/O, exception handling, error handling, conditional statements, CGI programming, shell scripting, web scraping, and Django.

It also covers Logging Framework, Unittest Framework, Socket Programming, Tornado Framework, and Networking. You will also build a Python chat server.

By the end of this course, you will have the skills to create and send robust Python applications using off-the-rack libraries confidently.

The code bundle for this course is available at: https://github.com/PacktPublishing/Python-Programming</p>
        <h2>What You Will Learn</h2><p>Learn the basics of Python<br>Learn networking and database access using Python and CGI programming<br>Understand the Python debugger<br>Understand web scraping using Beautiful Soup<br>Learn about Python Unittest<br>Build a Python chat server</p>
        <h2>Audience</h2><p>This course is for new Python users looking to make the best of this powerful programming language-college freshers, software developers, programming enthusiasts, and technical leads. Python is widely used in artificial intelligence, so if you are planning to start your career in AI/machine learning then you need to have an understanding of Python as a prerequisite.</p>
        <h2>Approach</h2><p>This course comprises self-paced videos, demos, lesson-end quizzes, and a competitive course-end project. This will help you increase your in-depth understanding of Python's design, memory models, object-arranged highlights, and information, and be industry-prepared.</p>
        <h2>Key Features</h2><p>Go from a beginner level to a confident level of Python programming * Increase your in-depth understanding of Python's design, memory models, and more * Work on a competitive project at the end of the course</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/python-programming</p>
        <h2>About the Author</h2><h3>Learnkart Technology Private Limited</h3><p>Learnkart understands the importance of upskilling and its impact on you. They pride themselves in creating specialized e-learning courses that will not only prepare you for certification exams but also help you gain hands-on knowledge for real-world applications. Thousands of students have developed their skills with Learnkart through a variety of courses, such as PgMP, Risk Management Professional (RMP), speech recognition, Python, Amazon Web Services (AWS), and more. Learnkart regularly adds courses to its portfolio to lend more value to your learning experience.</p>
        <h2>Course Outline</h2><h4>1. Course Introduction</h4><p></p><br><h4>2. Python Basics</h4><p></p><br><h4>3. Data Operations</h4><p></p><br><h4>4. Conditional Statements and Functions</h4><p></p><br><h4>5. Error Handling and File Operations</h4><p></p><br><h4>6. Shell Scripting and Django</h4><p></p><br><h4>7. Course End Project</h4><p></p>

You will master the fundamentals and more advanced principles of Python programming in this beginner's tutorial. This Python course covers every Python fundamental, including installation and more complex material such as Python data science.

Python Programming

Demand for data analysts, data scientists and data engineers tripled over the past five years, rising 231%. That's much faster than job postings overall in the UK, which grew 36%. Hence, the demand for skilled data analysts has skyrocketed in the UK and worldwide! On average, salaries for these data analysts' roles are £64,376 and keep rising.
With a broader overview of the data analyst's responsibility, data chart, and presentation tools, the bundle describes how to filter, improve and handle data to present various information. You'll learn process management, how to analyse data and how to make vital business decisions. The data analyst bundle will buckle you up to perform simple to complex business analysis tasks effectively and efficiently.
Furthermore, the data analyst course accentuates developing your programming skills for a data analyst, such as Python, SQL, and R. What's more? Besides strengthening Microsoft Excel skills for a data analyst, you can improve your expertise in Tableau, Google Data Studio and business analysis ability from this Data Analyst (Data Analytics) Bundle course. Hence, you can be an efficient data analyst and a competent candidate for a challenging position.
Learning Outcomes of Data Analyst (Data Analytics)
Upon completion of the Data Analyst (Data Analytics) program, you will have acquired:
Acquire a big-picture understanding of the data analyst role
Fundamentals of data analysis (data analysis), including process management, tools for data analysis, various charts
Ability to conduct thorough research and turn raw data into presentable information
Perform many data operations in Python's famous "pandas" library, including grouping, pivoting, joining and more!
Learn about NLP, Machine Learning (ML), data visualisation using Matplotlib, Seaborn and much more
Knowledge of all the essential SQL commands and become proficient in SQL tools like GROUP BY, JOINS, and Subqueries
Become competent in using sorting and filtering commands in SQL
Learn general cloud computing concepts and gain a solid understanding of the fundamental systems on which the cloud is based
Learn how to use the R programming language for data science, machine learning, and data visualisation
Learn data analytics with Tableau, business intelligence and data mining masterclass, basic Google Data studio
This Data Analyst (Data Analytics) Bundle Consists of the following Premium courses:
Course 01: Introduction to Data Analysis
Course 02: Python for Data Analysis
Course 03: SQL Programming Masterclass
Course 04: Data Science & Machine Learning with R
Course 05: Data Analytics with Tableau
Course 06: Basic Google Data Studio
Course 07: Business Intelligence and Data Mining Masterclass
Course 08: Business Analysis Level 3
Course 09: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query
Course 10: Cloud Computing / CompTIA Cloud+ (CV0-002)
Course 11: GDPR Data Protection Level 5
Course 12: ChatGPT Crash Course
Upon finishing this 12-course Data Analyst (Data Analytics) bundle, you will acquire the necessary skills for a thriving career in this rapidly expanding industry. Waste no more time - enrol today and commence your path towards a promising future!
The Curriculum of the Data Analyst Bundle:
Course 1: Introduction to Data Analysis
Introduction
Agenda and Principles of Process Management
The Voice of the Process
Working as One Team for Improvement
Exercise: The Voice of the Customer
Tools for Data Analysis
The Pareto Chart
The Histogram
The Run Chart
Exercise: Presenting Performance Data
Understanding Variation
The Control Chart
Control Chart Example
Control Chart Special Cases
Interpreting the Control Chart
Control Chart Exercise
Strategies to Deal with Variation
Using Data to Drive Improvement
A Structure for Performance Measurement
Exercise
Course Project
Test your Understanding
Course 2: Python for Data Analysis
Welcome, Course Introduction & overview, and
Environment set-up
Python Essentials
Python for Data Analysis using NumPy
Python for Data Analysis using Pandas
Python for Data Visualization using mat plotlib
Python for Data Visualization using Seaborn
Python for Data Visualization using pandas
Python for interactive & geographical plotting using Plotly
and Cufflinks
Capstone Project - Python for Data Analysis &
Visualisation
Python for Machine Learning (ML) - sci-kit-learn - Linear
Regression Model
Python for Machine Learning - scikit-learn - Logistic
Regression Model
Python for Machine Learning - scikit-learn - K Nearest
Neighbours
Python for Machine Learning - scikit-learn - Decision Tree
and Random Forests
Python for Machine Learning - scikit-learn -Support Vector
Machines (SVMs)
Python for Machine Learning - scikit-learn - K Means
Clustering
Python for Machine Learning - scikit-learn - Principal
Component Analysis (PCA)
Recommender Systems with Python - (Additional Topic)
Python for Natural Language Processing (NLP) - NLTK -
(Additional Topic)
Course 3: SQL Programming Masterclass
Introduction
Setting up Course Tools
Browsing & Filtering Data
Filter Data with AND, OR, NOT Operators
Math Operations
String Concatenation
Tidy Up Your Results: Sorting, Alias Names, Limit
Records
NULL, DISTINCT & CASE Statements
Functions in SQL: Multiple-Row Functions
Functions in SQL: Single-Row Functions
Nested Queries
Casting & Data Conversion
Combination Relationships
Joins in SQL
Data Manipulation (DML)
SQL Data Definition Language (DDL)
Course 4: Data Science & Machine Learning with R
Data Science and Machine Learning Course Intro
Data Types and Structures in R
Data Types and Structures in R
Intermediate R
Data Manipulation in R
Data Visualisation in R
Creating Reports with R Markdown
Building WebApps with R Shiny
Introduction to Machine Learning
Starting A Career in Data Science
Course 5: Data Analytics with Tableau
Introduction to the Course
Project 1: Discount Mart (Sales and Profit Analytics)
Project 2: Green Destinations (HR Analytics)
Project 3: Superstore (Sales Agent Tracker)
Northwind Trade (Shipping Analytics)
Project 5: Tesla (Stock Price Analytics)
Bonus: Introduction to Database Concepts
Tableau Stories
Course 6: Basic Google Data Studio
Introduction to GDS
Data Visualisation
Geo-visualisation
A Socio-Economic Case Study
Course 7: Business Intelligence and Data Mining Masterclass
What is Business Intelligence?
Starting Case in understanding BI needs in diff phases
of business
Decision-Making Process and Need for IT Systems
Problem Structure and Decision Support System
Introduction to BI Applications
Dashboard presentation systems
Different Types of Charts used in 131 Dashboards
Good Dashboard and BSC
Examples of Bad Dashboards
Process of KPI Development
Overview of Data Warehouse
More explanation of the data warehouse and steps in
processing
Data Warehouse Architecture -Tiers
Data Warehouse - components
Approach to developing data structure and Models of
database
Basics of Data Mining - Meaning
Basics of Data Mining - Stages of DM
Data Mining Technique - Classification
Data mining - Clustering
Data Mining - Association Rules
Data Mining Applications - Banking
Data Mining Applications - CRM
Data Mining Applications - other industries
Course 8: Business Analysis Level 3
Introduction to Business Analysis
Business Processes
Business Analysis Planning and Monitoring
Strategic Analysis and Product Scope
Solution Evaluation
Investigation Techniques
Ratio Analysis
Stakeholder Analysis & Management
Process Improvement with Gap Analysis
Documenting & Managing Requirements
Career Prospect as a Business Analyst in the UK
Course 9: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query
Introduction
Prepaid Expenses Models: Resources Download
Accounting for Prepaid Expenses
Excel Formulas Detailed: Introduction to three Excel
Models
Formula-Based Prepaid Expenses Model
Calculate Prepaid Expenses Amortisation from Exact
Start Date
Prepaid Expenses Summary with Power Query & Pivot
Table
Advanced VBA Prepaid Expenses Amortisation Model
BONUS: Dynamic Dashboard for Divisional Profit &
Loss statements: Easy Way
Power Query & Pivot Tables based Dashboard without any Formulas, Fully Dynamic
Course 10: Cloud Computing CompTIA Cloud+ (CV0-002)
What You Need to Know
Introducing the Cloud
System Requirements for Cloud Deployments
Cloud Storage
Cloud Compute
Cloud Networking
Cloud Security
Migrating to the Cloud
Maintaining Cloud Solutions
Troubleshooting Cloud Solutions
Course 11: GDPR Data Protection
GDPR Basics
GDPR Explained
Lawful Basis for Preparation
Rights and Breaches
Course 12: ChatGPT Crash Course
Sign up for an OpenAI Account
What can ChatGPT do for you?
ChatGPT for Business
ChatGPT for Teaching
ChatGPT for Research
Limitations of ChatGPT
Additional Videos
 CPD 
130 CPD hours/points  Accredited by CPD Quality Standards
 Who is this course for? 
Anyone from any background can enrol in this Data Analyst (Data Analytics) bundle. Persons with similar professions can also refresh or strengthen their skills by enrolling in this Data Analyst (Data Analytics) bundle course. Students can take this course to gather professional knowledge besides their studies or for the future. 
Aspiring data analysts
Business analyst professionals who want to improve their skills
Anyone who desires to develop their data analysis skills
 
 Career path 
This Data Analyst (Data Analytics) Bundle is ideal for those who want to take their development to the next level and fast-track their career in any of the following roles:
Data Analyst: £30,000 - £50,000
Senior Data Analyst: £50,000 - £70,000
Data Scientist: £70,000 - £100,000
Business Intelligence Manager: £60,000 - £80,000
Machine Learning Engineer: £60,000 - £90,000
 Certificates 
Certificate of Completion
Digital certificate - Included
PDF certificate - Free (Previously, it was £6*12 = £72)
Certificate of Completion
Hard Copy certificate - Included
Hard Copy Certificate - Free (For The Title Course: Previously, it was £10)
Other Hard Copy certificates are available for £10 each
Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

Apex Learning

Google Data Studio

GDPR

Data Mining

Tableau

Business Intelligence (BI)

ChatGPT

12 in 1 Career Guided Programme | Python, Data Science, ML, Tableau, SQL Programming, Data Mining, Business Analysis | 130 CPD Points | Tutor Support | Lifetime Access

Data Analyst (Data Analytics) Diploma - CPD Certified

Master Python 3.10 from the experts with this course and demonstrate programming wizardry in Python. Go from a geek to a wizard in no time with this well-structured video course and write Python code like a pro. Learn about the often-forgotten basics and special features of programming and Python in general.

The Ultimate Guide to Python Programming with Python 3.10

<strong>This course offers you the exact skills and principles you need to deliver a project using Python along with the tools you can use to create solid Python code. Master the language constructs, tools, and terminology with this carefully designed course for beginners.</strong>
        <p>Python is one of the most popular computer programming languages and this hands-on course for beginners will make it easy for someone who wants to get started with learning Python.

This course takes you through the introduction to the course and the learning objectives. You will learn to get started with Replit and write your first Python program. You will learn to store, process, and compare information in Python as well as learn to tidy messy data. You will learn about variables, strings, dictionaries, indexing, and slicing in Python. Further, you will understand loops in Python along with break, continue, and else functions.

Moving ahead, you will understand error handling in Python, get to know the try-and-catch block, and learn to add resources to Replit. You will also understand function parameters and explore the difference between local and global variables, and positional and keyword parameters. You will learn to work with JSON and clean the data along with various numeric functions such as min, max, and sum.

By the end of the course, you will gain a solid foundation in Python programming and be able to write high-quality code in Python.

All resources and code files are placed here: https://github.com/PacktPublishing/Python-Bootcamp-in-a-day---Python-Programming-for-Beginners</p>
        <h2>What You Will Learn</h2><p>Master Python programming fundamentals<br>Learn how to install Python to get up and running in no time<br>Learn how to process data to create Olympics Medals Tables<br>Solve multiple specific problems for a customer in the real world<br>Learn all about objects and variables in Python<br>Understand functions and function parameters in Python</p>
        <h2>Audience</h2><p>Whether you are a software engineer, software developer, computer programmer, web developer, transitioning into a new role, or simply someone who wants to understand what makes Python tick, this is the place to start. If you are preparing for a Python certification or job role, this course is for you.</p>
        <h2>Approach</h2><p>This course is video based course with no supporting document necessary. It takes you through the fundamentals of Python and teaches you how to use it with a simple tool so you can master the fundamentals in a day.</p>
        <h2>Key Features</h2><p>Be fluent in writing Python code and working with all the fundamentals of the language such as a list, string, function, dictionary, array, set, and much more * Learn to use Python's data analysis capabilities to analyze data from a real-world data source * A complete overview of the basics with exercises to test your knowledge of storing, processing, and storing information</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Python-Bootcamp-in-a-day---Python-Programming-for-Beginners</p>
        <h2>About the Author</h2><h3>Paul Ashun</h3><p>Paul Ashun is the CEO, MD, and chief consultant at Pashun Consulting Ltd., specializing in Scrum coaching and leadership within major global organizations. They are the authors of over 10 books on Scrum such as The Power of Scrum in the Real World, Confessions of a Scrum Master as well as the upcoming Agile User Storybook.

He started as a software developer and over ten years later, he became an Agile portfolio manager. He is a certified Scrum Master and a PMO manager. He has led projects for the BBC, General Electric, Oracle, BSkyB, HiT Entertainment, and Razorfish. He has been coaching product owners and business analysts in international blue-chip companies, dating back to 1999, in Agile and Scrum practices such as writing user stories.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video is an introduction the course and what you can expect from the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Learning Objectives - Introduction</p><p style='margin: 0'>This video explains the learning objectives of the course.</p></td></tr><tr><td style='padding: 15px;'><p>3. What Is Python?</p><p style='margin: 0'>This video explains what Python is and the need for Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. The Example</p><p style='margin: 0'>This video explains an example of a software engineer working in a media company to support the development team.</p></td></tr></tbody></table><br><h4>2. Getting Set Up</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Getting Set Up</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. How to Get Started with Replit</p><p style='margin: 0'>This video explains how to get started with Replit.</p></td></tr><tr><td style='padding: 15px;'><p>3. Writing Your First Python Program-Hello World</p><p style='margin: 0'>This video explains writing your first Python program-Hello World.</p></td></tr></tbody></table><br><h4>3. Storing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Storing Information</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Objects and Variables</p><p style='margin: 0'>This video explains objects and variables in Python using an example of Olympic results.</p></td></tr><tr><td style='padding: 15px;'><p>3. Variable Names</p><p style='margin: 0'>This video explains variable names in Python and the rules to use them.</p></td></tr><tr><td style='padding: 15px;'><p>4. Numbers</p><p style='margin: 0'>This video explains the different types of numbers in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. Strings</p><p style='margin: 0'>This video explains strings in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. Showing Output When Running Python</p><p style='margin: 0'>This video explains showing output when running Python.</p></td></tr></tbody></table><br><h4>4. Processing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Processing Information</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Processing Information</p><p style='margin: 0'>This video explains processing information in Python.</p></td></tr><tr><td style='padding: 15px;'><p>3. Indexing</p><p style='margin: 0'>This video explains indexing in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Slices</p><p style='margin: 0'>This video explains slices in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. String Functions</p><p style='margin: 0'>This video explains string functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. The 'input' Function</p><p style='margin: 0'>This video explains the input function in Python.</p></td></tr><tr><td style='padding: 15px;'><p>7. More String Operations</p><p style='margin: 0'>This video explains more string operations in Python.</p></td></tr><tr><td style='padding: 15px;'><p>8. Converting Between Different Types</p><p style='margin: 0'>This video explains converting between different types.</p></td></tr></tbody></table><br><h4>5. Comparing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Comparing Information</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Comparing Information</p><p style='margin: 0'>This video explains comparing information in Python.</p></td></tr></tbody></table><br><h4>6. Tidying Messy Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Tidying Messy Data</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Tidying Messy Data</p><p style='margin: 0'>This video explains how to tidy messy data.</p></td></tr></tbody></table><br><h4>7. Storing Multiple Things</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Storing Multiple Things</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Storing Multiple Things</p><p style='margin: 0'>This video explains how to store multiple things.</p></td></tr><tr><td style='padding: 15px;'><p>3. Introducing Python Lists</p><p style='margin: 0'>This video explains lists in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Adding Items to a List</p><p style='margin: 0'>This video explains how to add items to a list.</p></td></tr><tr><td style='padding: 15px;'><p>5. Indexing and Slicing Lists</p><p style='margin: 0'>This video explains indexing and slicing lists.</p></td></tr><tr><td style='padding: 15px;'><p>6. Deleting Items in a List</p><p style='margin: 0'>This video explains how to delete items in a list.</p></td></tr><tr><td style='padding: 15px;'><p>7. Tuples</p><p style='margin: 0'>This video explains tuples in Python.</p></td></tr><tr><td style='padding: 15px;'><p>8. Long Lines in Python</p><p style='margin: 0'>This video explains long lines in Python.</p></td></tr><tr><td style='padding: 15px;'><p>9. Dictionaries</p><p style='margin: 0'>This video explains dictionaries in Python.</p></td></tr><tr><td style='padding: 15px;'><p>10. List Functions - More Ways to Work with Lists</p><p style='margin: 0'>This video explains list functions.</p></td></tr><tr><td style='padding: 15px;'><p>11. Sets</p><p style='margin: 0'>This video explains sets in Python.</p></td></tr></tbody></table><br><h4>8. Processing Collections</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Processing Collections</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. A Simple 'for' Loop</p><p style='margin: 0'>This video explains a simple for loop.</p></td></tr><tr><td style='padding: 15px;'><p>3. More Complex 'for' loops - 'break', 'continue', and 'else'</p><p style='margin: 0'>This video explains more complex 'for' loops.</p></td></tr><tr><td style='padding: 15px;'><p>4. The 'range' Function - How to Create a List of Numbers</p><p style='margin: 0'>This video explains how to create a list of numbers.</p></td></tr><tr><td style='padding: 15px;'><p>5. The 'while' Loop - Do Something for a While</p><p style='margin: 0'>This video explains the while loop.</p></td></tr></tbody></table><br><h4>9. Robust Programs - Handling Errors</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Robust Programs - Handling Errors</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Robust Programs - Handling Errors</p><p style='margin: 0'>This video explains error handling in Python.</p></td></tr><tr><td style='padding: 15px;'><p>3. Look Before You Leap</p><p style='margin: 0'>This video explains one way of making the code more robust, which is called 'look before you leap'.</p></td></tr><tr><td style='padding: 15px;'><p>4. The Try and Except Block</p><p style='margin: 0'>This video explains the try and except block in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. The Catch-All Block</p><p style='margin: 0'>This video explains the catch-all block.</p></td></tr><tr><td style='padding: 15px;'><p>6. Adding Resources to Replit</p><p style='margin: 0'>This video explains how to add resources to Replit.</p></td></tr><tr><td style='padding: 15px;'><p>7. The Finally Block</p><p style='margin: 0'>This video explains the finally block.</p></td></tr></tbody></table><br><h4>10. Saving the Results - Working with Files</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Saving the Results - Working with Files</p><p style='margin: 0'>This video explains the learning objectives of the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Adding Bad Data</p><p style='margin: 0'>This video explains adding bad data.</p></td></tr><tr><td style='padding: 15px;'><p>3. Saving the Results - Working with Files</p><p style='margin: 0'>This video explains saving the results and working with files.</p></td></tr><tr><td style='padding: 15px;'><p>4. Binary File Modes</p><p style='margin: 0'>This video explains binary file modes.</p></td></tr><tr><td style='padding: 15px;'><p>5. Text File Modes</p><p style='margin: 0'>This video explains text file modes.</p></td></tr><tr><td style='padding: 15px;'><p>6. The With Statement</p><p style='margin: 0'>This video explains the with statement.</p></td></tr></tbody></table><br><h4>11. Breaking Up Larger Programs, Part 1</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Breaking Up Larger Programs, Part 1</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. About Replit.config</p><p style='margin: 0'>This video explains replit.config.</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions</p><p style='margin: 0'>This video explains functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Function Parameters</p><p style='margin: 0'>This video explains function parameters.</p></td></tr><tr><td style='padding: 15px;'><p>5. Local Versus Global Variables</p><p style='margin: 0'>This video explains local versus global variables.</p></td></tr><tr><td style='padding: 15px;'><p>6. Positional and Keyword Parameters</p><p style='margin: 0'>This video explains positional and keyword parameters.</p></td></tr><tr><td style='padding: 15px;'><p>7. Return Statement</p><p style='margin: 0'>This video explains the return statement.</p></td></tr><tr><td style='padding: 15px;'><p>8. Working With JSON</p><p style='margin: 0'>This video explains working with JSON.</p></td></tr><tr><td style='padding: 15px;'><p>9. Code Comments and Clear Code</p><p style='margin: 0'>This video explains code comments in Python.</p></td></tr></tbody></table><br><h4>12. Summarising and Presenting the Results</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Summarising and Presenting the Results</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Summarising and Presenting the Results Part 1</p><p style='margin: 0'>This video explains how to summarise the results using statistics.</p></td></tr><tr><td style='padding: 15px;'><p>3. Cleaning the Data</p><p style='margin: 0'>This video explains cleaning the data in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Summarising and Presenting the Results Part 2</p><p style='margin: 0'>This video explains the code in which we will get a sum of the scores of a country.</p></td></tr><tr><td style='padding: 15px;'><p>5. More Numeric Functions - Min, Max, Sum</p><p style='margin: 0'>This video explains min, max, and sum functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. Formatted Strings, f-strings</p><p style='margin: 0'>This video explains formatted strings and f-strings in Python.</p></td></tr></tbody></table><br><h4>13. Breaking Up Larger Programs, Part 2</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Breaking Up Larger Programs, Part 2</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Splitting Code into Modules</p><p style='margin: 0'>This video explains splitting code into modules.</p></td></tr><tr><td style='padding: 15px;'><p>3. Namespaces</p><p style='margin: 0'>This video explains namespaces in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Using Our Modules</p><p style='margin: 0'>This video explains how to use modules in Python.</p></td></tr></tbody></table><br><h4>14. Getting Set Up on a PC or MAC</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Getting Set Up on a PC or MAC</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Getting Set Up</p><p style='margin: 0'>This video explains how to set up Python on our systems.</p></td></tr><tr><td style='padding: 15px;'><p>3. Starting Python on Windows 10</p><p style='margin: 0'>This video explains how to start Python on Windows 10.</p></td></tr><tr><td style='padding: 15px;'><p>4. Starting a Terminal or Command Prompt on Windows</p><p style='margin: 0'>This video explains how to start a terminal or command prompt on Windows.</p></td></tr><tr><td style='padding: 15px;'><p>5. Installing Python on Windows</p><p style='margin: 0'>This video explains the installation of Python on Windows.</p></td></tr><tr><td style='padding: 15px;'><p>6. Installing Python on MacOS</p><p style='margin: 0'>This video explains the installation on Python on MacOS.</p></td></tr><tr><td style='padding: 15px;'><p>7. Quick Python Test - Running Python</p><p style='margin: 0'>This video explains how to run a Python script.</p></td></tr><tr><td style='padding: 15px;'><p>8. Python Scripts and IDLE</p><p style='margin: 0'>This video explains Python scripts and IDE.</p></td></tr><tr><td style='padding: 15px;'><p>9. Code Editors and IDEs</p><p style='margin: 0'>This video explains code editors and IDEs.</p></td></tr><tr><td style='padding: 15px;'><p>10. Running Python Scripts</p><p style='margin: 0'>This video explains how to run Python scripts.</p></td></tr></tbody></table>

This course offers you the exact skills and principles you need to deliver a project using Python along with the tools you can use to create solid Python code. Master the language constructs, tools, and terminology with this carefully designed course for beginners.

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