Name: Deep Learning - Deep Neural Network for Beginners Using Python
Price: 41.99 GBP
Availability: InStock

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					<div><p><span>The comprehensive <span>Python Complete Crash </span>Course has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the <span>Python Complete Crash </span> Course today, and learn from the very best the industry has to offer!</span></p></div>
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					<div><p><span>This best selling <span>Python Complete Crash </span>Course has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Python Complete Crash Course is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</span></p><p><span>The <span>Python Complete Crash </span>Course 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 <span>Python Complete Crash </span>Course 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.</span></p><p><span>After successfully completing the <span>Python Complete Crash </span>Course, 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 Python Complete Crash Course will help you stand out from the crowd. You can also validate your certification on our website.</span></p><p><span>We know that you are busy and that time is precious, so we have designed the  to be completed at your <span>Python Complete Crash </span>Course 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. </span></p><p><span>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</span></p></div>
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Course Cloud

Python Complete Crash Course

General Admission

<strong>Explore the quick and easy way to learn the MySQL Database with Python</strong>
        <p>Today databases are highly valued as they allow users to effectively manage, access, and update data. MySQL is one of the most popular databases and has a wide variety of applications in e-commerce, data warehousing, and website management. When combined with Python, one of the most popular and powerful programming languages today, you'll be able to manage data efficiently and systematically.

In this course, you'll get started by understanding the basics of using MySQL with Python. You'll learn how to install MySQL and Python, before going on to develop databases. In addition to this, you'll explore the technique of creating tables for safely storing data. The course will then guide you on how to add, sort, and retrieve data through functions such as INSERT, ORDER BY, and SELECT. As you progress, you'll be equipped with the knowledge of inserting a single record as well as multiple records into a table. Toward the end, you will discover clauses such as WHERE and LIKE, and later learn to update records.

By the end of this course, you will have learned how to confidently use Python with MySQL for your database management needs.  

All code files are placed at https://github.com/PacktPublishing/Using-MySQL-Databases-With-Python</p>
        <h2>What You Will Learn</h2><p>Get up to speed with the working of a database<br>Understand how to install Python, MySQL, Git Bash, and MySQL Connector<br>Work through creating a table<br>Explore how to connect to a database in Python<br>Update and delete data from the database<br>Discover the technique of inserting a single record as well as multiple records into a table<br>Create basic reports with the data from your database</p>
        <h2>Audience</h2><p>This course is for anyone who wants to use the MySQL Database with Python. Although a basic understanding of Python programming is required, knowledge of databases or MySQL is not necessary.</p>
        <h2>Approach</h2><p>A complete course packed with step-by-step instructions, working examples, and helpful advice.</p>
        <h2>Key Features</h2><p>Learn to use MySQL databases with Python * Get to grips with adding, sorting and pulling specific data</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/using-mysql-databases-with-python</p>
        <h2>About the Author</h2><h3>John Elder</h3><p>John Elder is a pioneer in Web Development who created one of the first Internet advertising networks back in 1997. He sold it to a publicly traded company at the height of the dot com boom and then went on to create the best-selling Submission-Spider search engine submission software that's been used by over 3 million individuals and small businesses in over 45 countries.

John graduated with honors with a degree in economics from Washington University in St. Louis where he was an artsci scholar. Today he teaches Web Development courses at Codemy the online code school he founded.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><br><h4>2. What is a Database</h4><p></p><br><h4>3. Install Python</h4><p></p><br><h4>4. Install Git Bash Terminal</h4><p></p><br><h4>5. Download MySQL</h4><p></p><br><h4>6. Install MySQL and Workbench</h4><p></p><br><h4>7. Install MySQL Connector</h4><p></p><br><h4>8. Connect to Database in Python</h4><p></p><br><h4>9. Explore MySQL Workbench</h4><p></p><br><h4>10. Create a Database</h4><p></p><br><h4>11. Create a Table</h4><p></p><br><h4>12. Insert One record into table</h4><p></p><br><h4>13. Insert Many records into Table</h4><p></p><br><h4>14. Understanding Data Types</h4><p></p><br><h4>15. Select Data from Table</h4><p></p><br><h4>16. Format our results</h4><p></p><br><h4>17. The Where Clause</h4><p></p><br><h4>18. Using AND and OR</h4><p></p><br><h4>19. The Like Clause and Wild cards</h4><p></p><br><h4>20. Updating Records</h4><p></p><br><h4>21. Limit and Ordering</h4><p></p><br><h4>22. Delete Records</h4><p></p><br><h4>23. Delete (Drop) a Table and Backups</h4><p></p>

Packt

Database Programming

Python

MySQL

Explore the quick and easy way to learn the MySQL Database with Python

Using MySQL Databases with Python

<strong>Step into the world of data analysis and gain practical experience analyzing real-world datasets with the help of this course. This course will not only guide you in analyzing data efficiently in Python from scratch but also help you in conducting your own analysis with Python and extracting valuable insights that can transform your business!</strong>
        <p>Data analysis is a critical skill and is getting more popular. Nowadays, every organization has some data. Data could be extremely useful, but not without appropriate analysis. Data analysis enables us to transform data into insights for businesses to make informative decisions.

You can find data analysis being used in every industry, be it healthcare, finance, or technology. Python is one of the most in-demand skills for data science by employers. It is not only easy to learn but also powerful.

The course follows the approach of rather than dumping all the available Python libraries or functions to you, we picked only the most useful ones based on our industry experience to cover in the course. This allows you to focus and master the foundations. Besides Python programming, you will also get exposed to the basic statistical knowledge necessary for data analysis. Combined with detailed video lectures, you will be given a few projects to work on to reinforce your knowledge.

By the end of the course, you will have a solid foundation of data analysis, and be able to use Python for the complete process.

All resources and code files are placed here: https://github.com/PacktPublishing/Python-for-Data-Analysis-step-by-step-with-projects-</p>
        <h2>What You Will Learn</h2><p>Learn to use Python for data analysis<br>Explore Python data analysis libraries (Pandas, Scikit-learn, Seaborn)<br>Learn about time data series in Python<br>Create data visualizations in Python<br>Learn to calculate summary statistics<br>Learn how to clean, manipulate, and transform data</p>
        <h2>Audience</h2><p>This course is helpful for anyone interested in analyzing data effectively. You want to become a data analyst or a data scientist, or you just want the skills to work on your projects.<br><br>This course is beginner friendly. However, we recommend you have some basic knowledge of Python or at least another programming language.</p>
        <h2>Approach</h2><p>This course offers 10 hours of HD video lectures, detailed code notebooks, and 3 guided practice projects, based on multiple real-world datasets.</p>
        <h2>Key Features</h2><p>Experience analyzing real-world datasets in lectures and guided projects * The course is arranged in different sections based on the step-by-step process of REAL data analysis * Get exposed to basic statistical knowledge necessary for data analysis</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Python-for-Data-Analysis-step-by-step-with-projects-</p>
        <h2>About the Author</h2><h3>Just Into Data</h3><p>Just Into Data is the brainchild of Justin and Lianne. Justin is an experienced data scientist in many different fields, such as marketing, anti-money laundering, and big data technologies. He also has a bachelor's degree in computer engineering and a master's degree in statistics.

Lianne is an experienced statistician who has worked in the central bank as well as commercial banks, where she monitored major financial institutions and conducted fraud analysis. She has both a bachelor's and a master's degree in statistics.</p>
        <h2>Course Outline</h2><h4>1. Let's get started!</h4><p></p><br><h4>2. Python crash course (optional)</h4><p></p><br><h4>3. Importing data</h4><p></p><br><h4>4. Exploring data (manipulation)</h4><p></p><br><h4>5. Capstone practice project I</h4><p></p><br><h4>6. Cleaning data</h4><p></p><br><h4>7. Transforming columns/features</h4><p></p><br><h4>8. Capstone practice project II</h4><p></p><br><h4>9. Exploring data (Exploratory Data Analysis)</h4><p></p><br><h4>10. Capstone practice project III</h4><p></p><br><h4>11. Bonus section: congrats and thank you!</h4><p></p>

Data Visualization

Pandas

Step into the world of data analysis and gain practical experience analyzing real-world datasets with the help of this course. This course will not only guide you in analyzing data efficiently in Python from scratch but also help you in conducting your own analysis with Python and extracting valuable insights that can transform your business!

Python for Data Analysis: Step-By-Step with Projects

<p>Did you know that there are over 27 million software developers worldwide, with the number projected to grow by 22% over the next few years? As the demand for technology continues to skyrocket, there's never been a better time to start your journey in programming.</p><p>Our bundle of courses, including Basic C# Coding, Introduction to Java, and a Diploma in Python Programming, provides a comprehensive introduction to the world of programming, allowing you to gain the skills you need to succeed in this competitive industry.</p><p>Basic C# Coding is the perfect course for those new to programming. You'll learn the basic syntax and programming concepts of C#, including variables, operators, and control structures. With this knowledge, you'll be able to write simple but functional programs quickly.</p><p>Once you've mastered the basics, you'll move on to Introduction to Java, where you'll learn about the fundamental concepts of Java programming language, including object-oriented programming, Java classes, and methods. This course will give you the wisdom to create powerful Java applications that can run on any device.</p><p>Finally, with our Diploma in Python Programming, you'll gain comprehensive knowledge of Python's syntax, data structures, and algorithms. This course will prepare you with the ability to write efficient, reliable, and scalable code that will help you easily build complex applications.</p><p>This bundle demonstrates the excellent level of education obtained through QLS-endorsed courses. This bundle includes three courses, ensuring learners receive high-quality, instructive, enjoyable learning.</p><p>Investing in your education is always a sensible decision, and with 3 QLS Endorsed certifications under your belt, you can be confident that you're double-boosting your rÃ©sumÃ©. Besides the QLS courses, the individuals will have access to 10 CPD courses related to the subject. They will widen your wisdom and improve your general comprehension.</p><p>Don't miss out on this opportunity to jumpstart your career in programming. Sign up for our bundle of courses today and join the millions of developers worldwide who are shaping the future of technology.</p><p><strong>QLS Endorsed Courses:</strong></p><ul><li><strong>Course 01:</strong> Diploma in Basic C# Coding at QLS Level 5</li><li><strong>Course 02:</strong> Diploma in Introduction to Java at QLS Level 5</li><li><strong>Course 03:</strong> Diploma in Python Programming at QLS Level 5</li></ul><p><strong>CPD QS Accredited Courses:</strong></p><ul><li><strong>Course 04:</strong> Coding Essentials - Javascript, ASP. Net, C# - Bonus HTML</li><li><strong>Course 05:</strong> Master JavaScript with Data Visualization</li><li><strong>Course 06:</strong> Python from Scratch</li><li><strong>Course 07:</strong> Coding with Scratch</li><li><strong>Course 08:</strong> Mastering Java for Beginners &amp; Experts</li></ul><p>Take your career to the next level with our bundle that includes not only technical courses but also <strong>five guided courses</strong> focused on personal development and <strong> career growth.</strong></p><ul><li><strong>Course 09:</strong> Personal Development</li><li><strong>Course 10:</strong> Career Development Plan Fundamentals</li><li><strong>Course 11:</strong> Leadership and Management Course</li><li><strong>Course 12:</strong> Communication Building Masterclass</li><li><strong>Course 13:</strong> Positive Psychology Masterclass</li></ul><p><strong>Learning Outcomes:</strong></p><ul><li>Understand the basic principles of programming languages such as C#, Java, and Python</li><li>Realise the different data types, control structures, and functions in C#, Java, and Python</li><li>Enhance talents in writing, testing, and debugging code using C#, Java, and Python</li><li>Comprehend the principles of object-oriented programming and its practices</li><li>Learn about the different types of objects, classes, and methods in C#, Java, and Python</li><li>Enrich aptitudes in object-oriented programming techniques</li><li>Understand the principles of software development and its practices</li><li>Learn about the different stages of the software development lifecycle and their implementation</li></ul><p><strong>Please Note: </strong>Imperial Academy is One Education approved resale partner for Quality Licence Scheme Endorsed courses.</p><p>This course bundle provides a comprehensive overview of three essential programming languages: C#, Java, and Python. The courses are designed to equip learners with the understanding necessary to develop programs using these popular programming languages.</p><p>The Basic C# Coding course covers the fundamental programming principles of C#, including data types, control structures, and functions. Learners will gain a thorough understanding of C# syntax and learn how to develop programs that solve real-world problems.</p><p>The Introduction to Java course provides learners with an understanding of the key principles of programming with Java, including object-oriented programming concepts and syntax. They will learn how to develop programs using Java and create user interfaces using graphical user interface (GUI) components.</p><p>The Diploma in Python Programming course covers the fundamental principles of programming with Python, including data types, control structures, and functions. Learners will gain a thorough understanding of Python syntax and learn how to develop programs that solve real-world problems.</p><p>We recognise the distinctiveness and obstacles that each community faces. We developed our courses to be particularly personalised and matched to your requirements because of this. Our classes are intended to be engaging and simple to comprehend, ensuring that you remember the wisdom you need to contribute to your community.</p><p><strong>Certificate</strong></p><p>QLS-endorsed courses are designed to provide learners with the skills and knowledge they need to succeed in their chosen field.</p><p>The Quality Licence Scheme is a distinguished and respected accreditation in the UK, denoting exceptional quality and excellence. It carries significant weight among industry professionals and recruiters.</p><p>Upon completion, learners will receive Three QLS Endorsed hard copy certificates, making it easy for them to showcase their achievements. These certificates validate their course completion, the level of the course they have completed, and the QLS endorsement.</p><h2>
        
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    </h2>

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

                        <div id="who_is_this_course_for">
                            <ul><li>Students or professionals in computer science, software engineering, or related fields</li><li>Programmers or developers looking to expand their knowledge in C#, Java, or Python</li><li>Entrepreneurs looking to start a software development business</li><li>Anyone interested in gaining wisdom in software development, coding, or programming</li><li>Those who want to learn about the principles of object-oriented programming and its practices</li><li>Individuals interested in pursuing a career in software engineering, web development, or mobile app development</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>Anyone can enrol on this C# Coding, Java and Python Programming Course.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>C# Developer - £25,000-£60,000</li><li>Java Developer - £25,000-£60,000</li><li>Python Developer - £25,000-£60,000</li><li>Full-stack Developer - £25,000-£60,000</li><li>Mobile App Developer - £25,000-£50,000</li><li>Web Developer - £25,000-£50,000</li><li>Software Engineer - £25,000-£60,000</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>

                        </div>

Imperial Academy

3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | 10 CPD Courses | Lifetime Access | 24/7 Tutor Support

C# Coding, Java and Python Programming - QLS Endorsed Certificate

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					<div><p>The innovative <strong>Python from Scratch Level 3</strong> has been compiled with the assistance and expertise of industry professionals. It has been carefully crafted to meet the business requirements needed for an outstanding contribution to this role and the career path beyond it. By enrolling in this tutorial, a significant advantage can be gained by the student for securing their dream job and building an excellent reputation in this sector.</p></div>
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					<div><p>This popular <strong>Python from Scratch Level 3 </strong>has been designed to help dedicated individuals train to become the absolute best in this business field. Many other entrepreneurs and talented students have already completed this course, and others like it, empowering them to move onto satisfying and rewarding careers. This unique <strong>Python from Scratch Level 3</strong> course is perfectly suited for those dedicated and ambitious individuals who are committed to genuinely becoming the best in the business. </p><p>The <strong>Python from Scratch Level 3</strong> is recognised and accredited by CPD standards, so all contents are guaranteed to be accurate and reputable, adding valuable competencies and qualifications to a CV, making anyone stand out from other potential candidates or business rivals. For added convenience, the <strong>Python from Scratch Level 3</strong> consists of a range of educational modules that allow study sessions to be organised at any time and any place</p><p>When the final assessment of the <strong>Python from Scratch Level 3 </strong>has been completed, a certificate of completion is supplied to evidence newly acquired skills and knowledge. This will provide a significant boost for job-seeking or entry into a new and exciting career path. The valuable qualification from the <strong>Python from Scratch Level 3</strong> course can help to make all the difference in a dynamic employment sector and can also be validated on our website.</p><p>We are aware that a student's lifestyles and work ethics may not allow much time for a dedicated study session, so the <strong>Python from Scratch Level 3</strong> has been specifically designed to be taken at a personally selected pace, and the hours that are suited to each individual. Full access is immediately available after registration, and this can be achieved via any online device, and at any global location you are sighted at.  </p><p>Our fully-trained tutors are committed to helping you throughout the course, and will instantly respond to any queries that are sent to them via email.</p></div>
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Python from Scratch Level 3

<strong>This course is designed for beginners or anyone who wants to get started with Python-based face recognition. In this course, you will learn how to perform face detection from images, face detection from real-time videos, emotion detection, age-gender prediction, face recognition from images and real-time videos, and more!</strong>
        <p>This course will help you delve into face recognition using Python without having to deal with all the complexities and mathematics associated with the deep learning process.

You will start with an introduction to face detection and face recognition technology. After this, you'll get the system ready by installing the Anaconda package and other dependencies and libraries. You'll then write Python code to detect faces from a given image and extract the faces as separate images. Next, you'll focus on face detection by streaming a real-time video from the webcam.

Customize the face detection program to blur the detected faces dynamically from the webcam video stream. You'll also learn facial expression recognition and age and gender prediction using a pre-trained deep learning model.

Later, you'll progress to writing Python code for face recognition, which will help identify the faces that are already detected. Then you'll explore the concept of face distance and tweak the face landmark points used for face detection.

By the end of this course, you'll be well-versed with face recognition and detection and be able to apply your skills in the real world.

All the codes and supporting files for this course will be available at https://github.com/PacktPublishing/Computer-Vision-Face-Recognition-Quick-Starter-in-Python</p>
        <h2>What You Will Learn</h2><p>Become well-versed with face detection and face recognition technology<br>Understand how to install the Anaconda package<br>Install dependencies and libraries such as dlib, OpenCV, and Pillow<br>Learn how to perform face detection and face recognition<br>Use the face distance parameter to calculate the magnitude of faces<br>Create custom face make-up for an image with face landmark points</p>
        <h2>Audience</h2><p>This course is designed for beginners or anyone who wants to get started with Python-based face recognition.</p>
        <h2>Approach</h2><p>Starting with an introductory section along with plenty of examples, this course will help you even if you do not have a Python background by getting you up and running with the basics. You'll be able to learn effectively with detailed explanations and even useful Python assignments.</p>
        <h2>Key Features</h2><p>Use Python to detect and recognize faces from images and real-time webcam video * Become well-versed with emotion detection * Get up to speed with predicting age and gender from images and real-time webcam video</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Computer-Vision-Face-Recognition-Quick-Starter-in-Python</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. Introduction to face recognition</h4><p></p><br><h4>2. Introduction to Face Recognition</h4><p></p><br><h4>3. Environment Setup: Installing Anaconda Package</h4><p></p><br><h4>4. Python Basics (Optional)</h4><p></p><br><h4>5. Setting up Environment - Additional Dependencies (With DLib Fixes)</h4><p></p><br><h4>6. (Optional) DLib Error: Downgrading Python and Fixing</h4><p></p><br><h4>7. Introduction to Face Detectors</h4><p></p><br><h4>8. Face Detection Implementation</h4><p></p><br><h4>9. Optional: cv2.imshow() Not Responding Issue Fix</h4><p></p><br><h4>10. Realtime Face Detection from WebCam</h4><p></p><br><h4>11. Video Face Detection</h4><p></p><br><h4>12. Realtime Face Detection - Face Blurring</h4><p></p><br><h4>13. Real-time Facial Expression Detection - Installing Libraries</h4><p></p><br><h4>14. Real-time Facial Expression Detection - Implementation</h4><p></p><br><h4>15. Video Facial Expression Detection</h4><p></p><br><h4>16. Image Facial Expression Detection</h4><p></p><br><h4>17. Real-time Age and Gender Detection Introduction</h4><p></p><br><h4>18. Real-time Age and Gender Detection Implementation</h4><p></p><br><h4>19. Image Age and Gender Detection Implementation</h4><p></p><br><h4>20. Introduction to Face Recognition</h4><p></p><br><h4>21. Face Recognition Implementation</h4><p></p><br><h4>22. Realtime Face Recognition</h4><p></p><br><h4>23. Video Face Recognition</h4><p></p><br><h4>24. Face Distance</h4><p></p><br><h4>25. Face Landmarks Visualization</h4><p></p><br><h4>26. Multi Face Landmarks</h4><p></p><br><h4>27. Multi Face Landmarks from Real-time and Pre-saved Video</h4><p></p><br><h4>28. Face Makeup Using Face Landmarks</h4><p></p><br><h4>29. Real-time Face Makeup</h4><p></p>

Computer Vision

This course is designed for beginners or anyone who wants to get started with Python-based face recognition. In this course, you will learn how to perform face detection from images, face detection from real-time videos, emotion detection, age-gender prediction, face recognition from images and real-time videos, and more!

Computer Vision: Face Recognition Quick Starter in Python

<strong>This comprehensive course will help you learn the basics to advanced mechanisms of chatbot development using deep learning with Python. This course is a complete package for beginners to learn chatbot fundamentals with deep learning and its applications and build it from scratch using deep learning (RNNs) with Python.</strong>
        <p>AI-powered chatbots are also capable of automating various tasks, including sales and marketing, customer service, and administrative and operational tasks. In this course about developing advanced chatbots with deep learning, we will understand their applications and build from scratch using deep learning with Python.

The course begins with a brief overview and the fundamentals of deep learning for chatbots. We will understand and compare conventional chatbots with deep learning-based chatbots. Then, we will explore self-learning chatbots, including generative chatbots and retrieval chatbots. You will learn more about deep learning-empowered chatbot features and compare and distinguish the abilities of conventional chatbots and self-learning chatbots in real action. We will focus on chatbot development with deep learning, tokenization, setting up an Encoder-Decoder, implementing RNN-based model development, and finally, training, testing, and validating the chatbot we developed.

Upon completing this course successfully, you will relate concepts and understand theories of chatbots in various domains, understand and implement deep learning models for building real-world chatbots, and evaluate deep learning-based chatbot models.

All resources are available at: https://github.com/PacktPublishing/Advanced-Chatbots-with-Deep-Learning-Python</p>
        <h2>What You Will Learn</h2><p>Relate the concepts and theories for chatbots in various domains<br>Compare conventional chatbots with deep learning-based chatbots<br>Understand deep learning algorithms for chatbots<br>Implement deep learning models for building real-world chatbots<br>Learn about tokenization and setting up an encoder-decoder<br>Implement recurrent neural network-based model development</p>
        <h2>Audience</h2><p>This course is designed for individuals looking to advance their skills in applied deep learning, acquire knowledge regarding the relationships of data analysis with deep learning, wish to build customized chatbots for their applications, learn to implement deep learning algorithms for chatbots, and are passionate about rule-based and self-learning chatbots. Deep learning practitioners/scholars working on chatbot concepts would benefit from this course. No prior knowledge of chatbots, deep learning, data analysis, or mathematics is needed. Basic to intermediate Python knowledge is required.</p>
        <h2>Approach</h2><p>The course is crafted to help you understand the impact of chatbots in real-world applications and provides a unique hands-on experience using a project. This course is easily understandable, with engaging content covering necessary theoretical concepts, a practical approach with live coding, and an in-depth project covering the complete course content.</p>
        <h2>Key Features</h2><p>Learn basic to advanced mechanisms of developing chatbots using deep learning with Python * Use Python to evaluate datasets based on conversational notes, online resources, and websites * Explore conventional/self-learning chatbots in action and chatbot development with deep learning</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Advanced-Chatbots-with-Deep-Learning-Python </p>
        <h2>About the Author</h2><h3>AI Sciences</h3><p>AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.

AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences.

Their courses have successfully helped more than 100,000 students master AI and data science.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p>This section focuses on introducing the author and the AI Sciences group and describes the course content you will be learning.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course and Instructor Introduction</p><p style='margin: 0'>In this video, we will be introduced to the course's author and his qualifications and experience in teaching learners on the online platform.</p></td></tr><tr><td style='padding: 15px;'><p>2. AI Sciences Introduction</p><p style='margin: 0'>This video briefly introduces the AI Sciences group and discusses the benefits of learning through AI Sciences.</p></td></tr><tr><td style='padding: 15px;'><p>3. Course Description</p><p style='margin: 0'>In this lesson, we will get an overview of what is covered in the course, including a comparison of chatbots and the benefits of chatbots. We will look at the chatbots in action. We will also look at deep learning frameworks in chatbots.</p></td></tr></tbody></table><br><h4>2. Fundamentals of Chatbots for Deep Learning</h4><p>This section focuses on the basics of chatbots, how deep learning benefits chatbots, conventional versus AI chatbots, the use of chatbots in the medical field, and the use of chatbots in business and ecommerce.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Module Introduction</p><p style='margin: 0'>This introduction video elaborates on the concepts to be covered in this module, including comparing chatbots, the conventional versus AI chatbots, and use of chatbots in various fields of applications.</p></td></tr><tr><td style='padding: 15px;'><p>2. Conventional Versus AI Chatbots</p><p style='margin: 0'>In this video, we will understand conventional and artificial intelligence-based chatbots and understand the differences between the two kinds.</p></td></tr><tr><td style='padding: 15px;'><p>3. Generative Versus Retrieval Chatbots</p><p style='margin: 0'>In this lecture, you will learn about a generative and retrieval chatbot and compare the differences between the two chatbots.</p></td></tr><tr><td style='padding: 15px;'><p>4. Benefits of Deep Learning Chatbots</p><p style='margin: 0'>In this video, we will look at what deep learning chatbots are and how they work. We will also understand the benefits of deep learning chatbots, including improved customer experience, service integration, customer care, personalized services, and saving resources.</p></td></tr><tr><td style='padding: 15px;'><p>5. Chatbots in Medical Domain</p><p style='margin: 0'>We will explore the first kind of chatbot operating in the medical domain. We will look at the benefits, including the ability to schedule appointments, check patient symptoms, provide support, help with coverage and insurance claims, and improve the patient experience.</p></td></tr><tr><td style='padding: 15px;'><p>6. Chatbots in Business</p><p style='margin: 0'>In this video, we will understand the benefits of chatbots in businesses, including lead qualification, lead nurturing, and data mining techniques.</p></td></tr><tr><td style='padding: 15px;'><p>7. Chatbots in Ecommerce</p><p style='margin: 0'>Let's understand the benefits of chatbots in ecommerce, including personalized services, real-time interaction, collection of feedback, provide metrics, lead generation, deep analytics, and storytelling.</p></td></tr></tbody></table><br><h4>3. Deep Learning-Based Chatbot Architecture and Development</h4><p>This section focuses on chatbot architecture and development based on deep learning, including understanding deep learning architecture, encoders and decoders, data preparation, importing libraries, and making predictions.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Module Introduction</p><p style='margin: 0'>In this video, you will learn more about deep learning and the general architecture, chatbot development with deep learning, and its related concepts.</p></td></tr><tr><td style='padding: 15px;'><p>2. Deep Learning Architecture</p><p style='margin: 0'>This video elaborates on the deep learning architecture in chatbots, integration of deep learning with chatbots, natural language processing (NLP), source content, interaction history, and analytics.</p></td></tr><tr><td style='padding: 15px;'><p>3. Encoder Decoder</p><p style='margin: 0'>In this video, we will understand what encoder and decoder are, their architecture, and long short-term memory (LSTM), a neural network used in deep learning.</p></td></tr><tr><td style='padding: 15px;'><p>4. Steps Involved</p><p style='margin: 0'>In this lesson, you will learn about the various steps involved in developing chatbots based on deep learning techniques. We will install the required packages, define chat models and tokenization, and set up the encoder-decoder model.</p></td></tr><tr><td style='padding: 15px;'><p>5. Project Overview and Packages</p><p style='margin: 0'>After theoretically learning about chatbots, we will now develop a chatbot practically by importing the requisite libraries-TensorFlow NumPy, Keras, and Pickle. We will build a chatbot based on a story and make predictions of true or false.</p></td></tr><tr><td style='padding: 15px;'><p>6. Importing Libraries</p><p style='margin: 0'>This video demonstrates how to import step by step the four main libraries required for our project, including TensorFlow, NumPy, Keras, and Pickle, and you will learn about importing Sequential and Model.</p></td></tr><tr><td style='padding: 15px;'><p>7. Data Preparation</p><p style='margin: 0'>We will use the two datasets available for our project, the training QA and the testing QA. We will save them in our project folder and invoke them as needed.</p></td></tr><tr><td style='padding: 15px;'><p>8. Develop Vocabulary</p><p style='margin: 0'>In this video, you will learn to combine the datasets, test data, and train data; we will use the all_data function to combine the datasets.</p></td></tr><tr><td style='padding: 15px;'><p>9. Max Story and Question Length</p><p style='margin: 0'>In this video, you will learn to define the project's story length and question length, determined by the number of words in the story or question.</p></td></tr><tr><td style='padding: 15px;'><p>10. Tokenizer</p><p style='margin: 0'>You will learn to import the tokenizer with and without filters. We will fit the tokenizer into our vocabulary using the fit_on_texts built-in command.</p></td></tr><tr><td style='padding: 15px;'><p>11. Separation and Sequence</p><p style='margin: 0'>In this video, you will learn to make the train-test story questions and answers. We will then use a for loop to enter the story, question, and answer into the respective parts.</p></td></tr><tr><td style='padding: 15px;'><p>12. Vectorize Stories</p><p style='margin: 0'>In this video, we will understand how to vectorize the story by defining functions, using the data, and developing an index and tokenizer. We will also determine the maximum story length calculated.</p></td></tr><tr><td style='padding: 15px;'><p>13. Vectorizing Train and Test Data</p><p style='margin: 0'>After creating the vectorization function, we will input the stories, queries, and answers using the vectorize function that we created using the train data.</p></td></tr><tr><td style='padding: 15px;'><p>14. Encoding</p><p style='margin: 0'>We will begin to develop our deep learning model and input placeholders to store the maximum story length, question length, and define the vocabulary size. We will now build our encoder using the sequential model.</p></td></tr><tr><td style='padding: 15px;'><p>15. Answer and Response</p><p style='margin: 0'>After learning to create our encoders for the input sequences and the questions, the encoders will match the data and obtain the responses.</p></td></tr><tr><td style='padding: 15px;'><p>16. Model Completion</p><p style='margin: 0'>In this video, after training and testing the data, querying the questions, and obtaining responses, we are now at model completion with compiling the questions and responses to check for accuracy.</p></td></tr><tr><td style='padding: 15px;'><p>17. Predictions</p><p style='margin: 0'>After checking our model for accuracy, we will make predictions of our results from the model we created. We will visualize the predictions using the test data.</p></td></tr></tbody></table>

Web Development

This comprehensive course will help you learn the basics to advanced mechanisms of chatbot development using deep learning with Python. This course is a complete package for beginners to learn chatbot fundamentals with deep learning and its applications and build it from scratch using deep learning (RNNs) with Python.

Advanced Chatbots with Deep Learning and Python

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					<div><p><span>This <strong>Basic Python</strong> course is the quickest and most effective way to learn Python online. Designed and taught by industry experts, it covers the fundamentals of Python programming in bite-size modules ideal for beginners. </span></p><p><span>Starting from the very beginning, you will learn how to install Python, write and run Python programs. Through video guidance, you will explore the key elements of Python, including its different data structures. </span></p><p><span>Whether you are new to Python programming or want to update your skills, this course will teach you everything you need to know to master Python in the shortest time possible - without skipping any of the important lessons. Take steps to become an entry-level Software Developer, and gain core industry knowledge today.</span></p></div>
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					<div><p>This best selling <strong>Basic Python </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Basic Python </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The <strong>Basic 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>Basic 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> Basic 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>Basic 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>Basic 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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Basic Python

<div> <div>     </div> <div>  <div> <div> <h3><strong>Highlights of the Course</strong></h3> <ul> <li><strong>Course Type:</strong> Online Learning</li> <li><strong>Duration:</strong> 17 Hours 21 Minutes</li> <li><strong>Tutor Support:</strong> Tutor support is included</li> <li><strong>Customer Support:</strong> 24/7 customer support is available</li> <li><strong>Quality Training:</strong> The course is designed by an industry expert</li> <li><strong>Recognised Credential:</strong> Recognised and Valuable Certification</li> <li><strong>Completion Certificate:</strong> Free Course Completion Certificate Included</li> <li><strong>Instalment:</strong> 3 Installment Plan on checkout</li> </ul> </div> </div> <div> <div> <hr /> <h3><strong>What you will learn from this course?</strong></h3> <ul> <li>Gain comprehensive knowledge about python programming</li> <li>Understand the core competencies and principles of python programming</li> <li>Explore the various areas of python programming</li> <li>Know how to apply the skills you acquired from this course in a real-life context</li> <li>Become a confident and expert python programmer and developer</li> </ul> </div> </div> <div> <div> <div> <hr /> <h3><strong>Python Hacking Masterclass Course</strong></h3> <p>Master the skills you need to propel your career forward in python programming. This course will equip you with the essential knowledge and skillset that will make you a confident python programmer and developer and take your career to the next level. This comprehensive python hacking masterclass<b> </b>course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this python hacking masterclass course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career.</p> <p>This comprehensive course will teach you the theory of effective python programming practice and equip you with the essential skills, confidence and competence to assist you in the python programming industry. You'll gain a solid understanding of the core competencies required to drive a successful career in python programming. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for python programmer and developer or for people who are aspiring to specialise in python programming.</p> <p>Enrol in this python hacking masterclass course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates.</p> </div> <div> <h3><strong>Who is this Course for?</strong></h3> <p>This comprehensive python hacking masterclass course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this python programming can also take this course.</p> <p>Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector.</p> </div> <div> <h3><strong>Entry Requirements</strong></h3> <p>This python hacking masterclass course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection.</p> </div> <div> <h3><strong>Assessment</strong></h3> <p>This python hacking masterclass course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%.</p> </div> <div> <h3><strong>Advance Your Career</strong></h3> <p>This python hacking masterclass<b> </b>course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume.</p> </div> </div> </div> </div> </div><div> <div> <h2> Recognised Accreditation </h2> <p>This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement.</p>  <p>The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries.</p>  </div> <div> <div> <div> <h3>What is CPD?</h3> <p>Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements.</p> <h4>Benefits of CPD</h4> <ul> <li>Improve your employment prospects </li> <li>Boost your job satisfaction </li> <li>Promotes career advancement </li> <li>Enhances your CV </li> <li>Provides you with a competitive edge in the job market </li> <li>Demonstrate your dedication </li> <li>Showcases your professional capabilities</li> </ul> </div> </div> <div> <div>  <h3>What is IPHM? </h3> <p>The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. </p> <h4>Benefits of IPHM </h4> <ul> <li>It will help you establish a positive reputation in your chosen field </li> <li>You can join a network and community of successful therapists that are dedicated to providing excellent care to their client </li> <li>You can flaunt this accreditation in your CV </li> <li>It is a worldwide recognised accreditation </li> </ul> </div> </div> <div> <div>  <h3>What is Quality Licence Scheme?</h3> <p>This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries.</p> <h4> Benefits of Quality License Scheme </h4> <ul> <li>Certificate is valuable</li> <li>Provides a competitive edge in your career</li> <li>It will make your CV stand out</li> </ul> </div> </div> </div> </div><div> <h3> <span>Course Curriculum</span> </h3> <div> <table> <tbody><tr> <td colspan="4"> Introduction and Setup</td> </tr> <tr> <td><i></i></td> <td> Welcome to Python for ethical hacking! </td> <td> </td> <td><span><i></i> 00:05:00</span></td> </tr> <tr> <td><i></i></td> <td> VirtualBox Installation </td> <td> </td> <td><span><i></i> 00:12:00</span></td> </tr> <tr> <td><i></i></td> <td> Kali Linux Installation </td> <td> </td> <td><span><i></i> 00:17:00</span></td> </tr> <tr> <td><i></i></td> <td> Adding Guest Additions </td> <td> </td> <td><span><i></i> 00:15:00</span></td> </tr> <tr> <td><i></i></td> <td> Adding Guest Additions </td> <td> </td> <td><span><i></i> 00:15:00</span></td> </tr> <tr> <td colspan="4">Port and Vulnerability Scanning</td> </tr> <tr> <td><i></i></td> <td> Coding A Simple Port Scanner </td> <td> </td> <td><span><i></i> 00:15:00</span></td> </tr> <tr> <td><i></i></td> <td> Adding Raw_Input To Our Port Scanner </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Scanning The First 1,000 Ports </td> <td> </td> <td><span><i></i> 00:05:00</span></td> </tr> <tr> <td><i></i></td> <td> Coding An Advanced Port Scanner Part 1 </td> <td> </td> <td><span><i></i> 00:13:00</span></td> </tr> <tr> <td><i></i></td> <td> Coding an Advanced Port Scanner Part 2 </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Finishing And Testing Our Scanner </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Configuring IP Address And Installing Metasploitable </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td><i></i></td> <td> Returning Banner From Open Port </td> <td> </td> <td><span><i></i> 00:15:00</span></td> </tr> <tr> <td><i></i></td> <td> Coding A Vulnerability Scanner Part 1 </td> <td> </td> <td><span><i></i> 00:12:00</span></td> </tr> <tr> <td><i></i></td> <td> Coding A Vulnerability Scanner Part 2 </td> <td> </td> <td><span><i></i> 00:07:00</span></td> </tr> <tr> <td colspan="4">SSH and FTP Attacks</td> </tr> <tr> <td><i></i></td> <td> Automating SSH Login Part 1 </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Automating SSH Login Part 2 </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Testing Our SSH Login Program </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Coding A SSH Brute-Forcer </td> <td> </td> <td><span><i></i> 00:11:00</span></td> </tr> <tr> <td><i></i></td> <td> Executing Commands On Target After Brute-Forcing SSH </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Anonymous FTP Login Attack </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Username &amp; password List Attack On FTP </td> <td> </td> <td><span><i></i> 00:18:00</span></td> </tr> <tr> <td colspan="4">Password Cracking</td> </tr> <tr> <td><i></i></td> <td> SHA256, SHA512, MD5 </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Cracking SHA1 Hash With Online Dictionary </td> <td> </td> <td><span><i></i> 00:17:00</span></td> </tr> <tr> <td><i></i></td> <td> Getting Password From MD5 Hash </td> <td> </td> <td><span><i></i> 00:13:00</span></td> </tr> <tr> <td><i></i></td> <td> Cracking Crypt Passwords With Salt </td> <td> </td> <td><span><i></i> 00:24:00</span></td> </tr> <tr> <td colspan="4">Sniffers, Flooders and Spoofers</td> </tr> <tr> <td><i></i></td> <td> Changing MAC Address Manually </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Coding MAC Address Changer </td> <td> </td> <td><span><i></i> 00:17:00</span></td> </tr> <tr> <td><i></i></td> <td> Theory Behind ARP Spoofing </td> <td> </td> <td><span><i></i> 00:05:00</span></td> </tr> <tr> <td><i></i></td> <td> Crafting Malicious ARP Packet </td> <td> </td> <td><span><i></i> 00:19:00</span></td> </tr> <tr> <td><i></i></td> <td> Coding ARP Spoofer </td> <td> </td> <td><span><i></i> 00:14:00</span></td> </tr> <tr> <td><i></i></td> <td> Forwarding Packets And Restoring ARP Tables </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td><i></i></td> <td> Spoofing Our IP Address And Sending Message With TCP Payload </td> <td> </td> <td><span><i></i> 00:12:00</span></td> </tr> <tr> <td><i></i></td> <td> Running SynFlooder With Changed Source IP Address </td> <td> </td> <td><span><i></i> 00:11:00</span></td> </tr> <tr> <td><i></i></td> <td> Getting Source And Destination MAC Address From Received Packets </td> <td> </td> <td><span><i></i> 00:25:00</span></td> </tr> <tr> <td><i></i></td> <td> Sniffing FTP Username And Password Part 1 </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td><i></i></td> <td> Sniffing FTP Username And Password Part 2 </td> <td> </td> <td><span><i></i> 00:12:00</span></td> </tr> <tr> <td><i></i></td> <td> Getting Passwords From HTTP Websites </td> <td> </td> <td><span><i></i> 00:14:00</span></td> </tr> <tr> <td><i></i></td> <td> Cloning Any Webpage </td> <td> </td> <td><span><i></i> 00:11:00</span></td> </tr> <tr> <td><i></i></td> <td> Printing DNS Queries </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td colspan="4">Coding DNS Spoofer</td> </tr> <tr> <td><i></i></td> <td> Redirecting Response To Cloned Page </td> <td> </td> <td><span><i></i> 00:17:00</span></td> </tr> <tr> <td><i></i></td> <td> Setting IP Table Rules And Running DNS Spoofer </td> <td> </td> <td><span><i></i> 00:11:00</span></td> </tr> <tr> <td colspan="4">Network Analysis</td> </tr> <tr> <td><i></i></td> <td> Analyzing Ethernet Header </td> <td> </td> <td><span><i></i> 00:16:00</span></td> </tr> <tr> <td><i></i></td> <td> Analyzing IP Header Part 1 </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Analyzing IP Header Part 2 </td> <td> </td> <td><span><i></i> 00:26:00</span></td> </tr> <tr> <td><i></i></td> <td> Analyzing TCP Header </td> <td> </td> <td><span><i></i> 00:15:00</span></td> </tr> <tr> <td><i></i></td> <td> Analyzing UDP Header </td> <td> </td> <td><span><i></i> 00:13:00</span></td> </tr> <tr> <td colspan="4">Multi-functioning Reverse</td> </tr> <tr> <td><i></i></td> <td> Theory Behind Socket Programming </td> <td> </td> <td><span><i></i> 00:07:00</span></td> </tr> <tr> <td><i></i></td> <td> Wine And Pyinstaller Installation </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td><i></i></td> <td> Setting Up Listener </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td><i></i></td> <td> Establishing Connection Between Target And Server </td> <td> </td> <td><span><i></i> 00:07:00</span></td> </tr> <tr> <td><i></i></td> <td> Implementing Send &amp; Receive Functions </td> <td> </td> <td><span><i></i> 00:11:00</span></td> </tr> <tr> <td><i></i></td> <td> Executing Commands On Target System </td> <td> </td> <td><span><i></i> 00:12:00</span></td> </tr> <tr> <td><i></i></td> <td> Importing JSON Library To Parse Data </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td><i></i></td> <td> Converting Python Backdoor To .Exe </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td><i></i></td> <td> Using OS Library To Change Directory </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Downloading &amp; Uploading Files To Target PC </td> <td> </td> <td><span><i></i> 00:19:00</span></td> </tr> <tr> <td><i></i></td> <td> Hiding Our Backdoor And Creating Persistence </td> <td> </td> <td><span><i></i> 00:14:00</span></td> </tr> <tr> <td><i></i></td> <td> Trying To Connect To Server Every 20 Seconds </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td><i></i></td> <td> Downloading Files To Target PC </td> <td> </td> <td><span><i></i> 00:12:00</span></td> </tr> <tr> <td><i></i></td> <td> Capturing Screenshot On Target PC </td> <td> </td> <td><span><i></i> 00:23:00</span></td> </tr> <tr> <td><i></i></td> <td> Administrator Privilege Check </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td><i></i></td> <td> Starting Other Programs With Our Shell </td> <td> </td> <td><span><i></i> 00:11:00</span></td> </tr> <tr> <td><i></i></td> <td> Running Our Shell As An Image, Audio, PDF </td> <td> </td> <td><span><i></i> 00:20:00</span></td> </tr> <tr> <td colspan="4">Coding a Keylogger</td> </tr> <tr> <td><i></i></td> <td> Installing Pynput </td> <td> </td> <td><span><i></i> 00:06:00</span></td> </tr> <tr> <td><i></i></td> <td> Printing Space Character </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Calling Timer On Our Keylogger </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Adding Keylogger To Our Backdoor </td> <td> </td> <td><span><i></i> 00:13:00</span></td> </tr> <tr> <td colspan="4">Command and Control Center</td> </tr> <tr> <td><i></i></td> <td> What Is A Threaded Server </td> <td> </td> <td><span><i></i> 00:05:00</span></td> </tr> <tr> <td><i></i></td> <td> Accepting Connections With A Thread </td> <td> </td> <td><span><i></i> 00:13:00</span></td> </tr> <tr> <td><i></i></td> <td> Managing Multiple Sessions </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Testing Threaded Server With Windows 10 Target </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Fixing Q Command </td> <td> </td> <td><span><i></i> 00:11:00</span></td> </tr> <tr> <td><i></i></td> <td> Coding Exit Function </td> <td> </td> <td><span><i></i> 00:14:00</span></td> </tr> <tr> <td><i></i></td> <td> Attacking Multiple Targets And Gathering Botnet </td> <td> </td> <td><span><i></i> 00:16:00</span></td> </tr> <tr> <td colspan="4">Website Penetration Testing</td> </tr> <tr> <td><i></i></td> <td> Stealing Saved Wireless Passwords </td> <td> </td> <td><span><i></i> 00:22:00</span></td> </tr> <tr> <td><i></i></td> <td> Saving Passwords To A File </td> <td> </td> <td><span><i></i> 00:03:00</span></td> </tr> <tr> <td><i></i></td> <td> Bruteforcing Gmail </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Bruteforcing Any Login Page Part 1 </td> <td> </td> <td><span><i></i> 00:13:00</span></td> </tr> <tr> <td><i></i></td> <td> Bruteforcing Any Login Page Part 2 </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Finding Hidden Directories Part 1 </td> <td> </td> <td><span><i></i> 00:05:00</span></td> </tr> <tr> <td><i></i></td> <td> Finding Hidden Directories Part 2 </td> <td> </td> <td><span><i></i> 00:07:00</span></td> </tr> <tr> <td><i></i></td> <td> Discovering Subdomains </td> <td> </td> <td><span><i></i> 00:12:00</span></td> </tr> <tr> <td><i></i></td> <td> Changing HTTP Headers </td> <td> </td> <td><span><i></i> 00:14:00</span></td> </tr> <tr> <td><i></i></td> <td> Starting Basic And Digest Authentication Bruteforcer </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Controlling Threads </td> <td> </td> <td><span><i></i> 00:09:00</span></td> </tr> <tr> <td><i></i></td> <td> Coding Run Function </td> <td> </td> <td><span><i></i> 00:10:00</span></td> </tr> <tr> <td><i></i></td> <td> Printing Usage And Testing Our Program </td> <td> </td> <td><span><i></i> 00:13:00</span></td> </tr> <tr> <td><i></i></td> <td> Taking A Look At Ransomware </td> <td> </td> <td><span><i></i> 00:08:00</span></td> </tr> <tr> <td colspan="4">Certificate of Achievement</td> </tr> <tr> <td><i></i></td> <td> Certificate of Achievement </td> <td> </td> <td><span><i></i> 00:00:00</span></td> </tr> <tr> <td colspan="4">Get Your Insurance Now</td> </tr> <tr> <td><i></i></td> <td> Get Your Insurance Now </td> <td> </td> <td><span><i></i> 00:00:00</span></td> </tr> <tr> <td colspan="4">Feedback</td> </tr> <tr> <td><i></i></td> <td> Feedback </td> <td> </td> <td><span><i></i> 00:00:00</span></td> </tr> </tbody></table></div> </div>

Study Plex

Python Hacking Masterclass

<strong>In this course, you will quickly learn how to build DNNs (Deep Neural Networks) and how to train them. This learning-by-doing course will also help you master the elementary concepts and methodology with Python. You need to have a basic knowledge of python to get the best out of this course.</strong>
        <p>Are you ready to start your path to becoming a deep learning expert? Then this course is for you.

This course is step-by-step. In every new tutorial, we build on what we have already learned and move one extra step forward, and then we assign you a small task that is solved at the beginning of the next video. We start by teaching the theoretical part of the concept, and then implement everything as it is practically using Python.

This comprehensive course will be your guide to learning how to use the power of Python to train your machine such that your machine starts learning just like humans, and based on that learning, your machine starts making predictions as well!

We will be using Python as a programming language in this course, which is the hottest language nowadays if we talk about machine learning. Python will be taught from the elementary level up to an advanced level so that any machine learning concept can be implemented.

You will also learn various steps of data preprocessing, which allows us to make data ready for machine learning algorithms.

You will learn the general concepts of machine learning overall, which will be followed by the implementation of one of the essential ML algorithms, 'Deep Neural Networks'. Each concept of DNNs will be taught theoretically and will be implemented using Python.

By the end of this course, you will be able to understand the methodology of DNNs with deep learning using real-world datasets.

All the resources for this course are available at: https://github.com/PacktPublishing/Deep-Learning---Deep-Neural-Network-for-Beginners-Using-Python</p>
        <h2>What You Will Learn</h2><p>Learn the basics of machine learning and neural networks<br>Understand the architecture of neural networks<br>Learn the basics of training a DNN using the Gradient Descent algorithm<br>Learn how to implement a complete DNN using NumPy<br>Learn to create a complete structure for DNN from scratch using Python<br>Work on a project using deep learning for the IRIS dataset</p>
        <h2>Audience</h2><p>This course is designed for anyone who is interested in data science or interested in taking their data-speak to a higher level.<br><br>Students who want to master DNNs with real datasets in deep learning or who want to implement DNNs in realistic projects can also benefit from the course. You need to have a background in deep learning to get the best out of this course.</p>
        <h2>Approach</h2><p>This course is clear and easy to understand as it is designed for absolute beginners. In this course, we will start by first learning the theoretical part of a concept followed by implementing it practically, using Python.</p>
        <h2>Key Features</h2><p>Covers the most sophisticated and recently discovered DNN models by eminent data scientists * Relate the theoretical concepts and sequence modeling with DNNs * Understand the methodology of DNNs with deep learning using real-world datasets</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Deep-Learning---Deep-Neural-Network-for-Beginners-Using-Python</p>
        <h2>About the Author</h2><h3>AI Sciences</h3><p>AI Sciences are a group of experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.

AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science.

They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences.

Their courses have successfully helped more than 100,000 students master AI and data science.</p>
        <h2>Course Outline</h2><h4>1. Section 1: Introduction</h4><p></p><br><h4>2. Section 2: Basics of Deep Learning</h4><p></p><br><h4>3. Section 3: Deep Learning</h4><p></p><br><h4>4. Section 4: Optimizations</h4><p></p><br><h4>5. Section 5: Final Project</h4><p></p>

Data Science

Deep Learning

In this course, you will quickly learn how to build DNNs (Deep Neural Networks) and how to train them. This learning-by-doing course will also help you master the elementary concepts and methodology with Python. You need to have a basic knowledge of python to get the best out of this course.

Deep Learning - Deep Neural Network for Beginners Using Python

<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

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 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
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 Requirements 
No experience required. Just enrol & start learning python.
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Upon completion of our Program, the potential career paths include:
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 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!


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<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>

Programming

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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