Name: QUALIFI Level 3 Diploma in Data Science
Price: 780.35 GBP
Availability: InStock

<div>
	[vc_row][vc_column][vc_column_text]
<h3><strong>Description:</strong></h3>
<p>This <b>Python Basic to Advanced for Data Science Online Course</b> is a great way to get started in programming. It covers the study of the Python language used to build most of the world's object-oriented systems.</p>
<p>The course is for interested students with a good level of computer literacy who wish to acquire programming skills. It is also ideal for those who wish to move to a developer role or areas such as software engineering. This is a great course to develop your coding skills. This <b>Python Basic to Advanced for Data Science Online Course </b>is an ideal preliminary to the Object-Oriented Programming using Python. Join the course now!</p>
<h3><strong>Entry Requirement</strong></h3>
<ul>
<li>This course is available to all learners, of all academic backgrounds.</li>
<li>Learners should be aged 16 or over to undertake the qualification.</li>
<li>Good understanding of English language, numeracy and ICT are required to attend this course.</li>
</ul>
<h3><strong>Certification:</strong></h3>
<p>After completing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24.</p>
<h3><strong>Why choose us?</strong></h3>
<ul>
<li>Affordable, engaging &amp; high-quality e-learning study materials;</li>
<li>Tutorial videos/materials from the industry leading experts;</li>
<li>Study in a user-friendly, advanced online learning platform;</li>
<li>The UK &amp; internationally recognized accredited qualification;</li>
<li>Access to course content on mobile, tablet or desktop from anywhere anytime;</li>
<li>The benefit of career advancement opportunities;</li>
<li>24/7 student support via email.</li>
</ul>
<h3><strong>Career Path</strong></h3>
<p>After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market.[/vc_column_text][/vc_column][/vc_row]
		</p></div><table width="100%">				<tbody><tr>
					<td colspan="4">Python 3 Beginners</td>
				</tr>
								<tr>
					<td colspan="4">Module 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td><span>FREE</span> </td>
					<td><span><i></i> 00:29:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Starter Examples</td>
					<td> </td>
					<td><span><i></i> 00:33:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Learning C Concepts</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 02</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Types and Inference</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Sizeof and IEEE 754</td>
					<td> </td>
					<td><span><i></i> 00:33:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Constants L and R Values</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Operators and Precedence</td>
					<td> </td>
					<td><span><i></i> 00:25:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Literals</td>
					<td> </td>
					<td><span><i></i> 00:26:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 03</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Classes and Structs</td>
					<td><span>FREE</span> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Enums</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Unions</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Pointers</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pointers and Array Indexing</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Using Const with Pointers</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pointers to String Literals</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>References</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Smart Pointers</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Arrays</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Standard Library Strings</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>More Standard Library Strings</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Functions</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>More Functions</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Function Pointers</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Control Statements</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Python 3 Intermediate</td>
				</tr>
								<tr>
					<td colspan="4">Module 04</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Installing Python</td>
					<td><span>FREE</span> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Documentation</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Command Line</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Variables</td>
					<td> </td>
					<td><span><i></i> 00:29:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Simple Python Syntax</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Keywords</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Import Module</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Additional Topics</td>
					<td> </td>
					<td><span><i></i> 00:23:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 05</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>If Elif Else</td>
					<td> </td>
					<td><span><i></i> 00:31:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Iterable</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>For</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Loops</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Execute</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Exceptions</td>
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Types</td>
					<td> </td>
					<td><span><i></i> 00:24:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 06</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Number Types</td>
					<td> </td>
					<td><span><i></i> 00:28:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>More Number Types</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Strings</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>More Strings</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Files</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Lists</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Dictionaries</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Tuples</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Sets</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 07</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Comprehensions</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Definitions</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Functions</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Default Arguments</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Doc Strings</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Variadic Functions</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Factorial</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Function Objects</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 08</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Lambda</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Generators</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Closures</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Classes</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Object Initialization</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Class Static Members</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Classic Inheritance</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Hiding</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Python 3 Advanced</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Iterators and Generators</td>
					<td><span>FREE</span> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Regular Expressions</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introspection and Lambda Functions</td>
					<td> </td>
					<td><span><i></i> 00:27:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Metaclasses and Decorators</td>
					<td> </td>
					<td><span><i></i> 00:24:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Modules and Packages</td>
					<td> </td>
					<td><span><i></i> 00:25:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Working with APIs</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Metaprogramming Primer</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Decorators and Monkey Patching</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>XML and JSON Structure</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Generating XML and JSON</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Parsing XML and JSON</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Implementing Algorithms</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Certificate and Transcript</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Order Your Certificates and Transcripts</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table>

John Academy

Online Course Marketing

Online Course Creation

Programming Fundamentals

Computer Programming

Trainers Course

Python Basic to Advanced for Data Science Online Course

General Admission

<strong>In this self-paced course, you will learn how to use TensorFlow 2 to build convolutional neural networks (CNNs). You will learn how to apply CNNs to several practical image recognition datasets and learn about techniques that help improve performance, such as batch normalization, data augmentation, and transfer learning.</strong>
        <p>TensorFlow is the world's most popular library for deep learning, and it is built by Google. It is the library of choice for many companies doing AI (Artificial Intelligence) and machine learning. So, if you want to do deep learning, you must know TensorFlow.

In this course, you will learn how to use TensorFlow 2 to build convolutional neural networks (CNN). We will first start by having an in-depth look at what convolution is, why it is useful, and how to integrate it into a neural network. Then you will learn how to apply CNNs to several practical image recognition datasets, from small and relatively simple to large and complex. Next, you will learn how to perform text preprocessing and text classification with CNNs.

In the last section, you will learn about techniques that help improve performance, such as batch normalization, data augmentation, and transfer learning for Computer Vision.

By the end of this course, we will have understood how to build convolutional neural networks in deep learning with TensorFlow.</p>
        <h2>What You Will Learn</h2><p>Understand the concept of convolution<br>Integrate convolution into neural networks<br>Apply CNNs to several image recognition datasets, both small and large<br>Learn best practices for designing CNN architectures<br>Learn about batch normalization and data augmentation<br>Learn how to preform text preprocessing</p>
        <h2>Audience</h2><p>This course is designed for anyone interested in deep learning and machine learning or for anyone who wants to implement convolutional neural networks in TensorFlow 2.<br><br>One must have decent Python programming skills, should know how to build a feedforward ANN (Artificial Neural Network) in TensorFlow 2, and must have experience with data science libraries such as NumPy and Matplotlib.</p>
        <h2>Approach</h2><p>In this self-paced course, you will learn how to use TensorFlow 2 to build convolutional neural networks. The course is well-balanced with theory that explains the CNN concepts and hands-on coding exercises for practical understanding.</p>
        <h2>Key Features</h2><p>Learn how to use TensorFlow 2 to build Convolutional Neural Networks (CNNs) * The course covers Natural Language Processing (NLP) and transfer learning for Computer Vision * Explains how to apply CNNs to NLP</p>
        
        <h2>About the Author</h2><h3>Lazy Programmer</h3><p>The Lazy Programmer, a distinguished online educator, boasts dual master's degrees in computer engineering and statistics, with a decade-long specialization in machine learning, pattern recognition, and deep learning, where he authored pioneering courses. His professional journey includes enhancing online advertising and digital media, notably increasing click-through rates and revenue. As a versatile full-stack software engineer, he excels in Python, Ruby on Rails, C++, and more. His expansive knowledge covers areas like bioinformatics and algorithmic trading, showcasing his diverse skill set. Dedicated to simplifying complex topics, he stands as a pivotal figure in online education, adeptly navigating students through the nuances of data science and AI.</p>
        <h2>Course Outline</h2><h4>1. Welcome</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>In this video, we will introduce the author and understand the course learning objective.</p></td></tr><tr><td style='padding: 15px;'><p>2. Outline</p><p style='margin: 0'>In this video, we will understand the course learning approach and what is required to start with this course. Then we will also understand what is covered in this course.</p></td></tr></tbody></table><br><h4>2. Convolutional Neural Networks (CNNs)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What Is Convolution? (Part 1)</p><p style='margin: 0'>In this video, we will get introduced to the concept of convolution.</p></td></tr><tr><td style='padding: 15px;'><p>2. What Is Convolution? (Part 2)</p><p style='margin: 0'>In this video, we will look at a new perspective on convolution to understand how it works.</p></td></tr><tr><td style='padding: 15px;'><p>3. What Is Convolution? (Part 3)</p><p style='margin: 0'>In this video, you will learn how to view convolution as matrix multiplication.</p></td></tr><tr><td style='padding: 15px;'><p>4. Convolution on Color Images</p><p style='margin: 0'>In this video, we will understand convolution on color images.</p></td></tr><tr><td style='padding: 15px;'><p>5. CNN Architecture</p><p style='margin: 0'>In this video, we will understand the CNN architecture.</p></td></tr><tr><td style='padding: 15px;'><p>6. CNN Code Preparation</p><p style='margin: 0'>In this video, we will look at the code preparation we will use for CNN and understand it.</p></td></tr><tr><td style='padding: 15px;'><p>7. CNN for Fashion MNIST</p><p style='margin: 0'>In this video, we will start with implementing CNN with the fashion MNIST dataset.</p></td></tr><tr><td style='padding: 15px;'><p>8. CNN for CIFAR-10</p><p style='margin: 0'>In this video, we will work on image classification with the CIFAR-10 dataset.</p></td></tr><tr><td style='padding: 15px;'><p>9. Data Augmentation</p><p style='margin: 0'>In this video, you will learn about data augmentation.</p></td></tr><tr><td style='padding: 15px;'><p>10. Batch Normalization</p><p style='margin: 0'>In this video, you will learn about batch normalization.</p></td></tr><tr><td style='padding: 15px;'><p>11. Improving CIFAR-10 Results</p><p style='margin: 0'>In this video, you will learn how to improve CIFAR-10 results using data augmentation and batch normalization.</p></td></tr><tr><td style='padding: 15px;'><p>12. Suggestion Box</p><p style='margin: 0'>In this video, we will look at the suggestion box where we can add feedback for this course.</p></td></tr></tbody></table><br><h4>3. Natural Language Processing (NLP)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Embeddings</p><p style='margin: 0'>In this video, we will understand the text as sequence data.</p></td></tr><tr><td style='padding: 15px;'><p>2. Code Preparation (NLP)</p><p style='margin: 0'>In this video, we will look at the code preparation we will use for NLP and understand it.</p></td></tr><tr><td style='padding: 15px;'><p>3. Text Preprocessing</p><p style='margin: 0'>In this video, we will move into action and understand how to do text preprocessing using Colab notebook.</p></td></tr><tr><td style='padding: 15px;'><p>4. CNNs for Text</p><p style='margin: 0'>In this video, we will understand how we can use CNNs for text sequences.</p></td></tr><tr><td style='padding: 15px;'><p>5. Text Classification with CNNs</p><p style='margin: 0'>In this video, we will move into action and work on text classification with CNNs.</p></td></tr></tbody></table><br><h4>4. Transfer Learning for Computer Vision</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Transfer Learning Theory</p><p style='margin: 0'>In this video, we will get introduced to the concept of transfer learning.</p></td></tr><tr><td style='padding: 15px;'><p>2. Some Pre-Trained Models (VGG, ResNet, Inception, MobileNet)</p><p style='margin: 0'>In this video, we will understand VGG, ResNet, Inception, and MobileNet.</p></td></tr><tr><td style='padding: 15px;'><p>3. Large Datasets and Data Generators</p><p style='margin: 0'>In this video, you will learn how to work with large image datasets in TensorFlow and Keras with data generators.</p></td></tr><tr><td style='padding: 15px;'><p>4. 2 Approaches to Transfer Learning</p><p style='margin: 0'>In this video, we will discuss the two approaches used for transfer learning, which we will use in the next videos.</p></td></tr><tr><td style='padding: 15px;'><p>5. Transfer Learning Code (Part 1)</p><p style='margin: 0'>In this video, we will dive into action and look at codes for transfer learning with data augmentation.</p></td></tr><tr><td style='padding: 15px;'><p>6. Transfer Learning Code (Part 2)</p><p style='margin: 0'>In this video, we will dive into action and look at codes for transfer learning without data augmentation.</p></td></tr></tbody></table>

Packt

Computer Vision

Data Science

Python

TensorFlow

In this self-paced course, you will learn how to use TensorFlow 2 to build convolutional neural networks (CNNs). You will learn how to apply CNNs to several practical image recognition datasets and learn about techniques that help improve performance, such as batch normalization, data augmentation, and transfer learning.

Deep Learning - Convolutional Neural Networks with TensorFlow

<div id="course-pills-1">Duration<p>5 Days</p><p>30 CPD hours</p>This course is intended for<p>This course is intended for new and experienced programmers that want to learn how to write and troubleshoot Python code. This is the Microsoft recommended course for preparing for the 98-381 test. Previous programming experience is not required but recommended.</p>Overview<p>By the end of this course, you will be able to:<br />Create Operations using Data Types and Operators<br />Create Control Flow Operations<br />Create Input and Output Operations<br />Write and Document code to solve a specified problem<br />Troubleshoot Problems and Write Error Handling Operations<br />Perform Operations Using Modules and Tools</p><p>This five-day instructor-led course (three-day boot camp) is intended for students who want to learn how to write, debug and document Python code</p></div><div id="course-pills-2"><h4>Module 1: Perform Operations Using Data Types and Operators</h4><ul><li>Assign data types to variables</li><li>Perform data and data type operations</li><li>Perform Arithmetic, Comparison and Logical Operations</li><li>Review</li></ul><h4>Module 2: Control Flow with Decisions and Loops</h4><ul><li>Construct and analyze code segments that use branching statements</li><li>Construct and analyze code segments that perform iterations</li><li>Review</li></ul><h4>Module 3: Perform Input and Output Operations</h4><ul><li>Create Python code segments that perform file input and output operations</li><li>Create Python code segments that perform console input and output operations</li><li>Review</li></ul><h4>Module 4: Document and Structure Code</h4><ul><li>Construct and analyze code segments</li><li>Document code segments using comments and documentation strings</li><li>Review</li></ul><h4>Module 5: Perform Troubleshooting and Error Handling</h4><ul><li>Analyze, Detect and Fix code segments that have errors</li><li>Analyze and construct code segments that handle exceptions</li><li>Review</li></ul><h4>Module 6: Perform Operations Using Modules and Tools</h4><ul><li>Use Built-In Modules to perform basic operations</li><li>Use Built-In Modules to perform complex operations</li><li>Review</li></ul></div>

Nexus Human

Computing Skills

Microsoft AZ-104

Microsoft AZ-303

55264 Introduction to Programming Using Python

Loughborough

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		<div>
			
			<p>This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects.</p>
			<div><i></i> 3 Days</div>
			<div><i></i>  £350.00 incl. VAT</div>
			
			
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			<p>Want to run this event in-house?  Enquire about running this event in-house </p>
			
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			<p>Interested in attending? Have a suggestion about running this event near you?<br />Register your interest now</p>
			
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		<h3>Description</h3>
		<p></p><p>The stakes for software security are very high, and yet many development teams deal with software security only after the code has been developed and the software is being prepared for delivery. As with any aspect of software quality, to ensure successful implementation, security and privacy issues should be managed throughout the entire software development lifecycle. </p>
<p>This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects. You will learn general strategies for dealing with security defects and misconfiguration, how to design software to deal with the human element in security, and how to incorporate security into all phases of development. </p>
<h3>Course Objectives:</h3>
<p>In this course, you will employ best practices in software development to develop secure software. You will:</p>
<ul>
<li>Identify the need for security in your software projects.</li>
<li>Eliminate vulnerabilities within software.</li>
<li>Use a Security by Design approach to design a secure architecture for your software.</li>
<li>Implement common protections to protect users and data.</li>
<li>Apply various testing methods to find and correct security defects in your software.</li>
<li>Maintain deployed software to ensure ongoing security.</li>
</ul>
<p><b><i>This course includes hands-on activities for each topic area. The goal of these activities is to demonstrate concepts utilizing two universal languages Python and JavaScript. Developers who use alternate languages will be able to apply the principles from the activities to any coding languages.</i></b></p>
<p><b><i>Hands-on exercises are designed to keep the typing of code to a bare minimum. We provide students with all of the code they need to complete activities. The activities do not require a 'deep dive' into code to understand the principles being covered.</i></b></p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is designed for software developers, testers, and architects who design and develop software in various programming languages and platforms, including desktop, web, cloud, and mobile, and who want to improve their ability to deliver software that is of high quality, particularly regarding security and privacy.</p>
<p>This course is also designed for students who are seeking the CertNexus Cyber Secure Coder certification.</p>
<p></p>
	
		<h3>Prerequisites</h3>
		<p></p><p>This course presents secure programming concepts that apply to many different types of software development projects. Although this course uses Python®, HTML, and JavaScript® to demonstrate various programming concepts, you do not need to have experience in these languages to benefit from this course. However, you should have some programming experience, whether it be developing desktop, mobile, web, or cloud applications. </p>
<div>
<h3>Course-specific Technical Requirements</h3>
</div>
<h4>Hardware</h4>
<p>For this course, you will need one computer for each student and one for the instructor. Each computer will need the following minimum hardware configurations:</p>
<ul>
<li>1 GHz or faster 32-bit (x86) or 64-bit (x64) processor</li>
<li>2 gigabytes (GB) RAM (32-bit or 64-bit)</li>
<li>20 GB available hard disk space (32-bit or 64-bit)</li>
<li>Keyboard and mouse (or other pointing device)</li>
<li>1,024 x 768 resolution monitor recommended</li>
<li>Projection system to display the instructor's computer screen</li>
<li>Local area network and Internet connection</li>
</ul>
<h4>Software</h4>
<ul>
<li>Windows® 10/8.1/8/7/Vista (64-bit). This course was successfully keyed on Windows 10. Some activity steps may not key exactly as written if students key on a different version of Windows.</li>
<li>Python version 3.8.1 (python-3.8.1.amd64.msi, provided with the course data files).</li>
<li>PyCharm Community Edition version 2019.3.3 (pycharm-community-2019.3.3.exe, provided with the course data files). Python is distributed under the Python Software Foundation License (PSFL). PyCharm Community Edition is distributed under the Apache® License 2.0.</li>
</ul>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4>Lesson 1: Identifying the Need for Security in Your Software Projects</h4>
<p>Topic A: Identify Security Requirements and Expectations <br />Topic B: Identify Factors That Undermine Software Security <br />Topic C: Find Vulnerabilities in Your Software<br />Topic D: Gather Intelligence on Vulnerabilities and Exploits</p>
<h4>Lesson 2: Handling Vulnerabilities</h4>
<p>Topic A: Handle Vulnerabilities Due to Software Defects and Misconfiguration <br />Topic B: Handle Vulnerabilities Due to Human Factors<br />Topic C: Handle Vulnerabilities Due to Process Shortcomings</p>
<h4>Lesson 3: Designing for Security</h4>
<p>Topic A: Apply General Principles for Secure Design <br />Topic B: Design Software to Counter Specific Threats</p>
<h4>Lesson 4: Developing Secure Code</h4>
<p>Topic A: Follow Best Practices for Secure Coding <br />Topic B: Prevent Platform Vulnerabilities<br />Topic C: Prevent Privacy Vulnerabilities</p>
<h4>Lesson 5: Implementing Common Protections</h4>
<p>Topic A: Limit Access Using Login and User Roles <br />Topic B: Protect Data in Transit and At Rest <br />Topic C: Implement Error Handling and Logging <br />Topic D: Protect Sensitive Data and Functions <br />Topic E: Protect Database Access</p>
<h4>Lesson 6: Testing Software Security</h4>
<p>Topic A: Perform Security Testing<br />Topic B: Analyze Code to find Security Problems<br />Topic C: Use Automated Testing Tools to Find Security Problems</p>
<h4>Lesson 7: Maintaining Security in Deployed Software</h4>
<p>Topic A: Monitor and Log Applications to Support Security <br />Topic B: Maintain Security after Deployment</p>
<p></p>

Mpi Learning - Professional Learning And Development Provider

This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects.

Cyber Secure Coder

<p>Picture this: you're a highly skilled Web Application Penetration Tester, working to identify vulnerabilities and protect businesses from cyber-attacks. In today's world, where cyber-attacks are becoming more common and sophisticated, the demand for experts in this field is on the rise. In fact, according to Cybersecurity Ventures, cybercrime is expected to cost the world $6 trillion annually by 2021. This highlights the importance of having highly skilled professionals in the field of cybersecurity.</p><p>The <strong>Web Application Penetration Tester - QLS Endorsed Bundle </strong> is designed to equip learners with the skills and knowledge needed to become experts in the field of web application penetration testing. This bundle includes courses such as the Web Application Penetration Testing Course, Secure Programming of Web Applications, Python Programming Bible, and Azure Machine Learning. These courses cover a wide range of topics, including web application security, programming languages, and machine learning.</p><p>Why should people in the UK learn about web application penetration testing? Well, cybercrime is a global problem, and the UK is not immune. In fact, according to the UK government, 46% of UK businesses reported experiencing a cyber-attack in 2020. This highlights the need for highly skilled cybersecurity professionals in the UK. In addition, the UK cybersecurity industry is growing rapidly, with a market value of £8.3 billion in 2020.</p><p>By completing the Web Application Penetration Tester - QLS Endorsed Bundle, learners will gain highly sought-after skills that are in high demand in the UK and around the world. With<strong> 10 QLS Endorsed certificate hardcopy free of charge,</strong> learners will have the credentials to prove their expertise and stand out in a competitive job market.</p><p>Take the first step towards a rewarding career in cybersecurity with the Web Application Penetration Tester - QLS Endorsed Bundle.</p><p><strong>Learning Outcomes:</strong></p><ul><li>Develop knowledge and skills in web application security and penetration testing.</li><li>Learn to identify and exploit vulnerabilities in web applications.</li><li>Develop knowledge and skills in programming languages such as Python and Java.</li><li>Learn to use machine learning to enhance web application security.</li><li>Develop the ability to write secure code for web applications.</li><li>Learn to use Azure Machine Learning for data analysis and machine learning tasks.</li><li>Develop the skills needed to pursue a career in cybersecurity or web application penetration testing.</li></ul><p><strong>Please Note:</strong> Imperial Academy is One Education approved resale partner for Quality Licence Scheme Endorsed courses.</p><p>The Web Application Penetration Tester - QLS Endorsed Bundle includes a range of courses that cover different aspects of web application security and penetration testing. The Web Application Penetration Testing Course covers the principles and practices of web application penetration testing, as well as the tools and techniques used in this field. The Secure Programming of Web Applications course covers the principles of secure coding and how they can be applied in the development of web applications.</p><p>The Python Programming Bible course covers a range of topics related to Python programming, including networking, GUI, email, XML, and CGI. The Azure Machine Learning course covers the use of Azure Machine Learning for data analysis and machine learning tasks. The Introduction to Java course covers the basics of Java programming, including data types, variables, control structures, and methods. The C++ Development: The Complete Coding Guide course covers the basics of C++ programming, including data types, variables, and control structures.</p><p><strong>This bundle comprises the following courses:</strong></p><p><strong>QLS Endorsed Courses:</strong></p><ul><li><strong>Course 01:</strong> Web Application Penetration Testing Course</li><li><strong>Course 02:</strong> Secure Programming of Web Applications - Developers and TPMs</li><li><strong>Course 03:</strong> Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li><strong>Course 04:</strong> Diploma in Python Programming</li><li><strong>Course 05:</strong> Azure Machine Learning</li><li><strong>Course 06:</strong> Introduction to Java</li><li><strong>Course 07:</strong> C++ Development: The Complete Coding Guide</li><li><strong>Course 08:</strong> How To Build Easy Drag &amp; Drop Landing Pages With WordPress</li><li><strong>Course 09:</strong> Career Coaching</li><li><strong>Course 10:</strong> The Unstoppable Self-Confidence &amp; High Self-Esteem Blueprint</li></ul><p><strong>Certificate: </strong></p><p>The Quality Licence Scheme ensures excellence and quality. These courses' learning outcomes provide the learners with high competence in their line of work as well. So, QLS-endorsed courses deliver not only deep knowledge but also add great value to the resume.</p><p>After completing the assessments, learners will be eligible for a prestigious QLS Certificate for each endorsed course in this bundle. Moreover, the certificates will be delivered to their home free of cost!</p><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <ul><li>Individuals interested in a career in cybersecurity or web application penetration testing.</li><li>IT professionals looking to enhance their skills in web application security and penetration testing.</li><li>Developers and programmers looking to learn about secure coding practices for web applications.</li><li>Data analysts and machine learning enthusiasts looking to apply their skills to web application security.</li><li>Anyone interested in learning about web application security and penetration testing.</li></ul>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Web Application Penetration Tester - Average Salary £45,000 per year</li><li>Cybersecurity Analyst - Average Salary £35,000 - £65,000 per year</li><li>Information Security Manager - Average Salary £60,000 - £90,000 per year</li><li>Web Application Developer - Average Salary £30,000 - £60,000 per year</li><li>Data Analyst - Average Salary £25,000 - £50,000 per year</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

10 QLS Endorsed Courses for Programming | 10 Endorsed Certificates Included | Life Time Access

Web Application Penetration Tester - QLS Endorsed Bundle

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				<h3><span id="docs-internal-guid-8c7677fd-7fff-3dba-9e42-22d2785cca3c"><p><span>Experience the future of </span><span>geographical analysis</span><span> with our </span><span>Machine Learning for Predictive Maps in Python and Leaflet</span><span> course. Master the unique blend of programming, machine learning, and geographic information systems, all while honing your ability to predict and visualise spatial data in a powerful and effective way. This course offers you an unparalleled understanding of </span><span>modern map creation</span><span>, combined with the magic of prediction using </span><span>machine learning models</span><span>.</span></p><br /><p><span>Starting from the ground up, you'll be introduced to all the necessary setups and installations. After that, you will be diving into the depth of </span><span>Django server-side code</span><span> and front-end application code writing. The heart of the course lies in learning how to automate the machine learning pipeline, leading you to </span><span>easily create predictive models</span><span>. </span></p><br /><p><span>Improve your maps with </span><span>Leaflet programming</span><span>, making your predictions accurate and also </span><span>visually striking</span><span>. By the end of this course, you will be armed with experience furnished by our comprehensive project </span><span>source code and assignments</span><span>, empowering you to drive data-driven decisions and insightful spatial analysis. </span><span>Join us</span><span> and </span><span>map your way to success</span><span>! Sign up today.</span></p><br /><br /><p><span>Learning Outcomes:</span></p><p><span>Upon completion of the Machine Learning course, you will be able to:</span></p><br /><ul><li><p><span>Understand how to set up and install relevant software and libraries.</span></p></li><li><p><span>Master Django server-side and application front-end code writing.</span></p></li><li><p><span>Gain proficiency in the concepts and implementation of Machine Learning.</span></p></li><li><p><span>Learn to automate Machine Learning pipelines for efficient workflows.</span></p></li><li><p><span>Acquire skills in Leaflet programming for enhanced map visuals.</span></p></li><li><p><span>Handle project source code effectively for real-world projects.</span></p></li><li><p><span>Apply knowledge practically via assignments and gain experience.</span></p></li></ul><br /><br /><p><span>Who is this course for?</span></p><p><span>This Machine Learning course is ideal for:</span></p><br /><ul><li><p><span>Aspiring Data Scientists keen on harnessing geographical data.</span></p></li><li><p><span>GIS professionals aiming to integrate Machine Learning into their skill set.</span></p></li><li><p><span>Software Developers interested in creating geographically-focused applications.</span></p></li><li><p><span>Analysts keen on enhancing their data visualisation skills with mapping.</span></p></li></ul><br /><br /><p><span>Certification</span></p><p><span>After studying the course materials of the </span><span>Machine Learning for Predictive Maps in Python and Leaflet</span><span> course, there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test, you have a </span><span>range of certification options</span><span> to choose from. You can claim a CPD Accredited PDF Certificate for</span><span> £4.99</span><span>, a CPD Accredited Hardcopy Certificate at</span><span> £8.00</span><span>, or you may choose to receive a PDF Transcript for</span><span> £4.99</span><span> or a</span><span> </span><span>Hardcopy Transcript for</span><span> £9.99</span><span>. Select according to your needs, and we assure </span><span>timely delivery</span><span> of your chosen certificate.</span></p><br /><br /><p><span>Requirements</span></p><p><span>This professionally designed </span><span>Machine Learning for Predictive Maps in Python and Leaflet </span><span>course does not require you to have any prior qualifications or experience. It is open to everyone. You will be able to access the course from anywhere at any time. Just enrol and start learning!</span></p><br /><br /><p><span>Career Path:</span></p><p><span>Our Machine Learning course will help you to </span><span>pursue a range of career paths</span><span>, such as:</span></p><br /><ul><li><p><span>Junior Data Analyst: £25,000 - £35,000 annually.</span></p></li><li><p><span>Data Scientist: £40,000 - £60,000 annually.</span></p></li><li><p><span>GIS Analyst: £30,000 - £45,000 annually.</span></p></li><li><p><span>Geospatial Software Developer: £35,000 - £55,000 annually.</span></p></li><li><p><span>Machine Learning Engineer: £50,000 - £80,000 annually.</span></p></li><li><p><span>Lead Data Scientist (GIS speciality): £70,000 - £100,000+ annually.</span></p></li></ul></span></h3>					</div>
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				<h3>
	<span>Course Curriculum</span>
</h3>

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					<td colspan="4">Section 01: Introduction</td>
				</tr>
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					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
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					<td colspan="4">Section 02: Setup and Installations</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Installation</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Creating a Python Virtual Environment</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
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					<td>Installing Django</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
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					<td><i></i></td>
					<td>Installing Visual Studio Code IDE</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
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					<td><i></i></td>
					<td>Installing PostgreSQL Database Server Part 1</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
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					<td><i></i></td>
					<td>Installing PostgreSQL Database Server Part 2</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
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					<td colspan="4">Section 03: Writing the Django Server-Side Code</td>
				</tr>
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					<td><i></i></td>
					<td>Adding the settings.py Code</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
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					<td><i></i></td>
					<td>Creating a Django Model</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
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					<td><i></i></td>
					<td>Adding the admin.py Code</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
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					<td colspan="4">Section 04: Writing the Application Front-end Code</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Template Files</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Django Views</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating URL Patterns for the REST API</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Adding the index.html code</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Adding the layout.html code</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating our First Map</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Adding Markers</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 05: Machine Learning</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Installing Jupyter Notebook</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Pre-processing</td>
					<td> </td>
					<td><span><i></i> 00:31:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Model Selection</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Model Evaluation and Building a Prediction Dataset</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 06: Automating the Machine Learning Pipeline</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating a Django Model</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Embedding the Machine Learning Pipeline in the Application</td>
					<td> </td>
					<td><span><i></i> 00:42:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating a URL Endpoint for our Prediction Dataset</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 07: Leaflet Programming</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating Multiple Basemaps</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating the Marker Layer Group</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating the Point Layer Group</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating the Predicted Point Layer Group</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating the Predicted High Risk Point Layer Group</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating the Legend</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating the Prediction Score Legend</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 08: Project Source Code</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Resource</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Assignment</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assignment - Machine Learning for Predictive Maps in Python and Leaflet</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Studyhub UK

Learning & Development

Machine Learning for Predictive Maps in Python and Leaflet

<div>
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				<div>
			<h2>Overview
</h2>		</div>
				</div>
				<div>
				<div>
								<div>
					<p><span>This comprehensive course on </span><b><span>Web Scraping and Mapping Dam Levels in Python and Leaflet Level 4</span></b> will deepen your understanding on this topic.</p><p><span><span>After successful completion of this course you can acquire the required skills in this sector. This </span><b>Web Scraping and Mapping Dam Levels in Python and Leaflet Level 4</b> comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.</span></p><p><span><span>So enrol in this course today to fast track your career ladder.</span></span></p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p><span>After successfully completing the course you will be able to order your certificate, these are included in the price.</span></p>					</div>
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				</div>
				<div>
				<div>
			<h2>Who is This course for?</h2>		</div>
				</div>
				<div>
				<div>
								<div>
					<p><span>There is no experience or previous qualifications required for enrolment on this </span><b><span>Web Scraping and Mapping Dam Levels in Python and Leaflet Level 4</span></b>. It is available to all students, of all academic backgrounds.</p>					</div>
						</div>
				</div>
				<div>
				<div>
			<h2>Requirements</h2>		</div>
				</div>
				<div>
				<div>
								<div>
					<p><span>Our </span><b><span>Web Scraping and Mapping Dam Levels in Python and Leaflet Level 4</span></b> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</p><p><span><span>There is no time limit for completing this course, it can be studied in your own time at your own pace.</span></span></p>					</div>
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				</div>
				<div>
				<div>
			<h2>Career Path</h2>		</div>
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					<p><span>Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business &amp; Management, Admin, Accountancy &amp; Finance, Secretarial &amp; PA, Teaching &amp; Mentoring etc.</span></p>					</div>
						</div>
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		</section>
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						</div>
					</div> <h3>Course Curriculum</h3><div><p>8 sections • 22 lectures • 04:20:00 total length</p></div><div><div><div><div><div><div><div><p>•Introduction: 00:16:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Installing PostgreSQL and PostGIS: 00:08:00</p></div><div><div><p>•Creating the Application Database: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Installing Django in a Python Virtual Environment: 00:08:00</p></div><div><div><p>•Installing the ATOM IDE: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Creating the Django Base Project: 00:08:00</p></div><div><div><p>•Adding the Database Configuration to the settings.py File: 00:09:00</p></div><div><div><p>•Creating a Model in the models.py File: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Extracting Data from the Web: 00:24:00</p></div><div><div><p>•Cleaning and Transforming the Data Part 1: 00:18:00</p></div><div><div><p>•Cleaning and Transforming the Data Part 2: 00:10:00</p></div><div><div><p>•Loading the Data into the Model: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Adding the Web Map Tile Service Link in settings.py: 00:08:00</p></div><div><div><p>•Reading from the Model and Creating a GeoJSON Dataset: 00:12:00</p></div><div><div><p>•Adding Template Files (HTML): 00:10:00</p></div><div><div><p>•Adding a Layout and the Base Map: 00:25:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Plotting Circle Markers: 00:16:00</p></div><div><div><p>•Creating a Sliding Sidebar: 00:14:00</p></div><div><div><p>•Creating a Doughnut Chart: 00:19:00</p></div><div><div><p>•Creating a Multi-Bar Bar Chart: 00:12:00</p></div><div><div><p>•Creating a Multi-Bar Bar Chart: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Resource: 00:00:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Apex Learning

Professional Skills Course (PSC)

ICDL (International Certification of Digital Literacy)

Web Scraping and Mapping Dam Levels in Python and Leaflet Level 4

London

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Why Learn&nbsp;Sketchup and Stable Diffusion Rendering Course?</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="https://www.londondesigntrainingcourse.co.uk/product-page/sketchup-and-stable-diffusion-rendering-course" target="_blank" rel="noopener noreferrer" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Link</strong></a></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">SketchUp and Stable Diffusion Rendering Course.&nbsp;An AI image creation course designed to explore AI image creation techniques and master the use of advanced AI technology. You&#39;ll learn Ai 3D modeling, advanced rendering, and lighting techniques.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Duration:&nbsp;</strong>16 hrs.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Method:</strong>&nbsp;1-on-1</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><u fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Online Over Zoom is also available.</strong></u></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Schedule:&nbsp;</strong>Tailor your own schedule by pre-booking a convenient hour of your choice, available from Mon&nbsp;to Sat&nbsp;between 9 am and 7 pm.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The Sketchup and Stable Diffusion Rendering Course equips students with comprehensive skills for visually stunning <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Ai (Artificial intelligence)</strong> 3D models and renderings.<br fr-original-style="" style="box-sizing: border-box;">
Master Sketchup&#39;s user-friendly interface, advanced rendering techniques, and stable diffusion rendering.<br fr-original-style="" style="box-sizing: border-box;">
Hands-on exercises and real-world projects enhance learning. Ideal for architecture, interior design, product development, and visualization careers.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The Sketchup and Stable Diffusion Rendering Course equips students with comprehensive skills for visually stunning <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Ai (Artificial intelligence)</strong> 3D models and renderings.<br fr-original-style="" style="box-sizing: border-box;">
Master Sketchup&#39;s user-friendly interface, advanced rendering techniques, and stable diffusion rendering.<br fr-original-style="" style="box-sizing: border-box;">
Hands-on exercises and real-world projects enhance learning. Ideal for architecture, interior design, product development, and visualization careers.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Sketchup and Stable Diffusion Rendering Course (16 hours)</strong></p>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 1: Introduction to Sketchup (2 hours)</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Overview of Sketchup software and interface navigation</li>
<li fr-original-style="" style="box-sizing: border-box;">Basic drawing tools and geometry creation techniques</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 2: Texturing and Materials (2 hours)</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Applying textures and customizing materials</li>
<li fr-original-style="" style="box-sizing: border-box;">Exploring texture mapping and material libraries</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 3: Lighting and Shadows (2 hours)</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Understanding lighting principles and light placement</li>
<li fr-original-style="" style="box-sizing: border-box;">Creating realistic shadows and reflections</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 4: Advanced Modeling Techniques (3 hours)</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Creating complex shapes and utilizing advanced tools</li>
<li fr-original-style="" style="box-sizing: border-box;">Working with groups, components, and modifiers</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 5: Stable Diffusion Rendering (2 hours)</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Introduction to stable diffusion rendering</li>
<li fr-original-style="" style="box-sizing: border-box;">Configuring rendering settings for optimal results</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 6: Scene Composition and Camera Setup (2 hours)</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Exploring composition principles and camera perspectives</li>
<li fr-original-style="" style="box-sizing: border-box;">Managing scenes and creating walkthrough animations</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 7: Rendering Optimization (2 hours)</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Optimizing models for faster rendering</li>
<li fr-original-style="" style="box-sizing: border-box;">Using render passes and post-processing techniques</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 8: Project Work and Portfolio Development (1 hour)</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Applying skills to complete a real-world project</li>
<li fr-original-style="" style="box-sizing: border-box;">Showcasing work in a professional portfolio</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Optional: Installing Stable Diffusion and Python (Additional 10 hours)</strong></p>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 1: Introduction to Stable Diffusion and Python</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Overview of Stable Diffusion and Python&#39;s significance</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 2: System Requirements</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Hardware and software prerequisites for installation</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 3: Installing Python</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Step-by-step installation process for different OS</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 4: Configuring Python Environment</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Setting up environment variables and package managers</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 5: Installing Stable Diffusion</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Downloading and installing the Stable Diffusion package</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 6: Setting Up Development Environment</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Configuring IDEs for Python and Stable Diffusion</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 7: Troubleshooting and Common Issues</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Identifying and resolving common installation errors</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 8: Best Practices and Recommendations</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Managing Python and Stable Diffusion installations</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 9: Practical Examples and Projects</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Hands-on exercises demonstrating usage of Stable Diffusion and Python</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Module 10: Advanced Topics (Optional)</strong></p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">Exploring advanced features and techniques</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Stable Diffusion UI v2 | A simple 1-click way to install and use</strong> <a href="https://stable-diffusion-ui.github.io" target="_blank" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">https://stable-diffusion-ui.github.io</a><br fr-original-style="" style="box-sizing: border-box;">
A simple 1-click way to install and use&nbsp;<em fr-original-style="" style="box-sizing: border-box;">Stable Diffusion</em>&nbsp;on your own computer. ... Get started by&nbsp;<em fr-original-style="" style="box-sizing: border-box;">downloading</em>&nbsp;the software and running the simple installer.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Learning Outcomes:</strong></p>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Upon completing the Sketchup and Stable Diffusion Rendering Course, with a focus on AI image rendering, participants will:</p>

<ul fr-original-style="" style="box-sizing: border-box;">
<li fr-original-style="" style="box-sizing: border-box;">
<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Master AI Image Rendering:</strong> Gain expertise in using AI-powered rendering techniques to create realistic and high-quality visualizations.</p>
</li>
<li fr-original-style="" style="box-sizing: border-box;">
<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Utilize Sketchup for 3D Modeling:</strong> Navigate the software, proficiently use drawing tools, and create detailed 3D models.</p>
</li>
<li fr-original-style="" style="box-sizing: border-box;">
<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Optimize Renderings:</strong> Apply AI-based rendering to optimize model visuals, achieving faster rendering times and superior image quality.</p>
</li>
<li fr-original-style="" style="box-sizing: border-box;">
<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Implement AI-driven Lighting and Shadows:</strong> Utilize AI algorithms for lighting placement, shadows, and reflections, enhancing realism in renderings.</p>
</li>
<li fr-original-style="" style="box-sizing: border-box;">
<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Create Professional Portfolio: </strong>Showcase AI-rendered projects in a professional portfolio, highlighting advanced image rendering skills.</p>
</li>
</ul>

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Note:</strong> The course focuses on AI image rendering using Sketchup and Stable Diffusion techniques, empowering participants with cutting-edge skills for creating exceptional visual representations.</p>

London Design Training Courses

SketchUp

Sketchup and Stable Diffusion Rendering

A course by  Sekhar Metla  IT Industry Expert RequirementsNo programming experience needed. You will learn everything you need to knowNo software is required in advance of the course (all software used in the course is free)No pre-knowledge is required - you will learn from basic Audience  Beginner JavaScript, Python and MSSQL developers curious about data science development  Anyone who wants to generate new income streams  Anyone who wants to build websites  Anyone who wants to become financially independent  Anyone who wants to start their own business or become freelance  Anyone who wants to become a Full stack web developer<h3> Audience</h3><ul><li> <span></span> <span>Beginner JavaScript, Python and MSSQL developers curious about data science development</span></li><li> <span></span> <span>Anyone who wants to generate new income streams</span></li><li> <span></span> <span>Anyone who wants to build websites</span></li><li> <span></span> <span>Anyone who wants to become financially independent</span></li><li> <span></span> <span>Anyone who wants to start their own business or become freelance</span></li><li> <span></span> <span>Anyone who wants to become a Full stack web developer</span></li></ul>

Xpert Learning

Data Engineering

Salesforce Certified JavaScript Developer

Big Data Analytics

Data Skills

Learn Data Science with Python, JavaScript, and Microsoft SQL

School of Business and Technology London

QUALIFI Level 3 Diploma in Data Science

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.</p><p></p>Overview<p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.</p><p></p><p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.</p><p></p>Prerequisites<p></p><li>Creating cloud resources in Microsoft Azure.</li>  <li>Using Python to explore and visualize data.</li>  <li>Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.</li>  <li>Working with containers</li>  <li>AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience.</li><p></p></div><div id="course-pills-2"><h3>1 - Design a data ingestion strategy for machine learning projects</h3> <ul> <li>Identify your data source and format</li> <li>Choose how to serve data to machine learning workflows</li> <li>Design a data ingestion solution</li> </ul> <h3>2 - Design a machine learning model training solution</h3> <ul> <li>Identify machine learning tasks</li> <li>Choose a service to train a machine learning model</li> <li>Decide between compute options</li> </ul> <h3>3 - Design a model deployment solution</h3> <ul> <li>Understand how model will be consumed</li> <li>Decide on real-time or batch deployment</li> </ul> <h3>4 - Design a machine learning operations solution</h3> <ul> <li>Explore an MLOps architecture</li> <li>Design for monitoring</li> <li>Design for retraining</li> </ul> <h3>5 - Explore Azure Machine Learning workspace resources and assets</h3> <ul> <li>Create an Azure Machine Learning workspace</li> <li>Identify Azure Machine Learning resources</li> <li>Identify Azure Machine Learning assets</li> <li>Train models in the workspace</li> </ul> <h3>6 - Explore developer tools for workspace interaction</h3> <ul> <li>Explore the studio</li> <li>Explore the Python SDK</li> <li>Explore the CLI</li> </ul> <h3>7 - Make data available in Azure Machine Learning</h3> <ul> <li>Understand URIs</li> <li>Create a datastore</li> <li>Create a data asset</li> </ul> <h3>8 - Work with compute targets in Azure Machine Learning</h3> <ul> <li>Choose the appropriate compute target</li> <li>Create and use a compute instance</li> <li>Create and use a compute cluster</li> </ul> <h3>9 - Work with environments in Azure Machine Learning</h3> <ul> <li>Understand environments</li> <li>Explore and use curated environments</li> <li>Create and use custom environments</li> </ul> <h3>10 - Find the best classification model with Automated Machine Learning</h3> <ul> <li>Preprocess data and configure featurization</li> <li>Run an Automated Machine Learning experiment</li> <li>Evaluate and compare models</li> </ul> <h3>11 - Track model training in Jupyter notebooks with MLflow</h3> <ul> <li>Configure MLflow for model tracking in notebooks</li> <li>Train and track models in notebooks</li> </ul> <h3>12 - Run a training script as a command job in Azure Machine Learning</h3> <ul> <li>Convert a notebook to a script</li> <li>Run a script as a command job</li> <li>Use parameters in a command job</li> </ul> <h3>13 - Track model training with MLflow in jobs</h3> <ul> <li>Track metrics with MLflow</li> <li>View metrics and evaluate models</li> </ul> <h3>14 - Perform hyperparameter tuning with Azure Machine Learning</h3> <ul> <li>Define a search space</li> <li>Configure a sampling method</li> <li>Configure early termination</li> <li>Use a sweep job for hyperparameter tuning</li> </ul> <h3>15 - Run pipelines in Azure Machine Learning</h3> <ul> <li>Create components</li> <li>Create a pipeline</li> <li>Run a pipeline job</li> </ul> <h3>16 - Register an MLflow model in Azure Machine Learning</h3> <ul> <li>Log models with MLflow</li> <li>Understand the MLflow model format</li> <li>Register an MLflow model</li> </ul> <h3>17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning</h3> <ul> <li>Understand Responsible AI</li> <li>Create the Responsible AI dashboard</li> <li>Evaluate the Responsible AI dashboard</li> </ul> <h3>18 - Deploy a model to a managed online endpoint</h3> <ul> <li>Explore managed online endpoints</li> <li>Deploy your MLflow model to a managed online endpoint</li> <li>Deploy a model to a managed online endpoint</li> <li>Test managed online endpoints</li> </ul> <h3>19 - Deploy a model to a batch endpoint</h3> <ul> <li>Understand and create batch endpoints</li> <li>Deploy your MLflow model to a batch endpoint</li> <li>Deploy a custom model to a batch endpoint</li> <li>Invoke and troubleshoot batch endpoints</li> </ul></div>

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-700

Azure Machine Learning

DP-100T01 Designing and Implementing a Data Science Solution on Azure

"Start your career as a Certified Python Programmer and earn up to £70,000 per Year."
Are you looking to make your mark in the ever-evolving world of Data Analyst? The demand for Python programmers has never been higher. Just in the UK, job postings for Analysts / Python programmers surged by an astounding 70% in 2022. This exponential growth trend signifies the soaring need for skilled Python programmers. Amid this vibrant job market, our Python Programmer online Training is your golden ticket to a prosperous career in programming or Data Analysis. Regardless of your level - beginner or expert - we ensure a comprehensive learning experience that will enhance your current skills and prepare you for the dynamic tech industry.
We envision being your reliable ally throughout your journey - from imparting quality Python training to ensuring your employability in the programming world.
Our Python Certification Program offers more than just technical know-how. We extend comprehensive career mentoring and support designed to mould you into an industry-ready professional. We'll assist you in creating an impressive resume, preparing for interviews, and landing your dream job. With a vast network of partner companies continually looking for Python programmers, we provide an opportunity to get your foot in the door of your desired companies.
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 Programmers, so we can help you get your foot in the door.
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So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Certified Python Programmers:
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 Python.
One-On-One Consultation: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Python programming 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 Certified Python Programmers. 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.
Courses we will provide once you enrol in the program:
Course 01: Computer Science With Python
Course 02: Ultimate Python Training for Beginners
Course 03: Python Intermediate Training
Course 04: Python Advanced Training
Course 05: Deep Learning & Neural Networks Python - Keras
Course 06: Complete Python Machine Learning & Data Science Fundamentals
Course 06: Introduction to Data Analysis
Course 07: Business and Data Analytics for Beginners
Course 08: Data Analytics with Tableau
Course 09: Quick Data Science Approach from Scratch
Course 10: Learn MySQL from Scratch for Data Science and Analytics
Course 11: SQL for Data Science, Data Analytics and Data Visualization
Course 12: Statistics & Probability for Data Science & Machine Learning
Course 13: Basic Google Data Studio
Course 14: Machine Learning with Python Course
Course 15: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 16: Web Scraping and Mapping Dam Levels in Python and Leaflet
Course 17: Coding Essentials - Javascript, ASP. Net, C#
Course 19: Master JavaScript with Data Visualization
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 Python Certification - IT Training is completed in 9 easy steps:
Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Python Certification Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 19 Premium Courses related to Python Programming. These courses will teach you the knowledge and skills required to become a successful Python Prgrammer. 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 programming/development industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.
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We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.
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 Python Programming, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Python Programming begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
This Python Certification Course is suitable for:
Beginners with no prior programming experience who are looking to enter the world of coding.
Intermediate programmers who wish to expand their skills and explore Python's extensive usage.
IT professionals seeking to diversify their skill sets and stay relevant in today's tech-driven market.
Data analysts and scientists who want to leverage Python's powerful libraries for their data processing needs.
Students and recent graduates looking to enhance their employability in the thriving tech industry.
Entrepreneurs who wish to understand and utilise Python to automate tasks and analyse data for their businesses.
Anyone with a keen interest in Python programming and a desire to delve into its applications in diverse fields like web development, data science, machine learning, and more.
 Requirements 
No experience required. Just enrol & start learning python.
 Career path 
Upon completion of our Program, the potential career paths include:
Python Developer: £30,000 - £90,000 annually
Data Scientist: £40,000 - £100,000 annually
Machine Learning Engineer: £50,000 - £110,000 annually
Data Analyst: £35,000 - £85,000 annually
Software Engineer: £35,000 - £95,000 annually
Back-end Developer: £40,000 - £95,000 annually
Web Developer: £30,000 -£85,000 annually
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Academy for Health and Fitness

Career Development

IT Certifications

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


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

Python Certification - IT Job Ready Program with Money Back Guarantee

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

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

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 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

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			<h2><b>Course Overview</b></h2>		</div>
				</div>
				<div>
				<div>
					<div><p><span>Are you looking to secure a career in Python programming or software engineering?</span></p><p><span>The</span><b> Python Programming</b><span> course will take you from beginner to expert in this programming language in no time, with step-by-step instructor-led guidance. Through audiovisual training, you will develop your data analysis, programming and coding skills, learning how to perform a wide range of tasks. It will teach you how to get set up on Mac OS X, Linux, and Ubuntu, best practices for string formatting, handling exceptions, and much more.</span></p><p><span>This course is open to anyone who wants to learn Python programming from the basics to an advanced level. Enrol as a part-time or full-time student today and gain the skills to become a Python programming pro.</span></p></div>
				</div>
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					<div><p>This best selling <strong>Python Programming </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Python Programming </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The <strong>Python Programming </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>Python Programming </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> Python Programming</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>Python Programming </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>Python Programming </strong>to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p><p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Course Cloud

Python Programming

<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.

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					<div><p>Basic Python 3.9  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 course today, and learn from the very best the industry has to offer!</p></div>
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					<div><p>This best selling Basic Python 3.9  has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth course is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The Basic Python 3.9  is CPD-accredited, so you can be confident you're completing a quality training course which will boost your CV and enhance your career potential. This 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.</p><p>After successfully completing the Basic Python 3.9 , 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 Basic Python 3.9  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 Basic Python 3.9  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></div>
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Basic Python 3.9

<p><strong>Introducing Coding using Python</strong></p>
<p>This course introduces your child to a very advanced, yet easy to learn programming languages &ndash; Python. It&rsquo;s safe to say that many apps we use today have been built using Python &ndash; Instagram Web, Netflix, YouTube, to name a few! This course teaches the fundamentals of coding, and creates a solid foundation to solve more complex real-life problems.</p>

Riva Learning

Programming Languages

Computing

Choose this course if your child is new to Python or has done a few hours of Python before. Or, they have a good understanding of block-based platforms like Scratch, and would like to start exploring text-based programming languages.

Introducing coding using Python

General admission

Network

Networking

Cisco

This course is an excellent resource to learn network programming using Python. With the help of practical examples, you will learn how to automate networks with Telnet, Secure Shell (SSH), Paramiko, Netmiko, and Network Automation and Programmability Abstraction Layer with Multivendor support (NAPALM).

Start your career as a Data Scientist and earn upto £90,000/ Year
Are you ready to unlock the power of Python and dive into the exciting world of data science? Look no further because we have the ultimate solution for you: Introducing our Data Science with Python Course with Career Support and Job Ready Program!
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 Data Scientist experience, we will guide you towards honing your skills and developing a strong foundation in Data Science.
Tailored CV Building: Crafting an impressive CV is crucial in today's competitive job market. Our team of experts will work closely with you to create a professional CV that showcases your skills and highlights your potential as a Data Scientist. We'll ensure that your CV stands out among the rest, increasing your chances of landing that dream job.
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.
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. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success.
Here are the courses we will provide once you enrol in the program:
Course 01: Ultimate Python Training for Beginners
Course 02: Python Intermediate Training
Course 03: Python Advanced Training
Course 04: SQL for Data Science, Data Analytics and Data Visualization
Course 05: Basic Data Analysis
Course 06: Develop Big Data Pipelines with R & Sparklyr & Tableau
Course 07: Develop Big Data Pipelines with R, Sparklyr & Power BI
Course 08: Customer Analytics Training
Course 09: Google Analytics for Everyone
Course 10: Google Data Studio: Data Analytics
Course 11: Big Data Analytics with PySpark Tableau Desktop and MongoDB
Course 12: Big Data Analytics with PySpark Power BI and MongoDB
Course 13: Excel Data Analysis
Course 14: Introduction to Data Analytics with Tableau
Course 15: Machine Learning with Python Course
Course 16: Python Programming Bible | Networking, GUI, Email, XML, CGI
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 Scientist 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 Scientist. 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 Scientist 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, 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 begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Aspiring data scientists looking to enter the exciting field of data science.
Professionals from other disciplines who want to transition into the data science domain.
Software engineers or programmers interested in expanding their skill set to include data science.
Analysts or researchers who want to enhance their data analysis and modeling capabilities.
Students or graduates seeking to kick-start their careers in data science with a strong foundation.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Analyst: £25,000 - £55,000 per year
Data Scientist: £40,000 - £85,000 per year
Machine Learning Engineer: £50,000 - £100,000 per year
Data Engineer: £45,000 - £80,000 per year
Business Intelligence Analyst: £35,000 - £65,000 per year
Data Science Manager: £70,000 - £120,000 per year.
 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 

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