Name: Machine Learning for Predictive Maps in Python and Leaflet Course
Price: 25 GBP
Availability: InStock

<div id="course-pills-1">Duration<p>2.75 Days</p><p>16.5 CPD hours</p>This course is intended for<p>Complete beginners who have never programmed before to experienced developers coming from another programming language.</p>Overview<p>You will learn how to leverage the power of Python to solve tasks. You will build games and programs that use Python libraries. You will be able to use Python for your own work problems or personal projects. You will create a portfolio of Python based projects you can share. Learn to use Python professionally, learning both Python 2 and Python 3! Create games with Python, like Tic Tac Toe and Blackjack! Learn advanced Python features, like the collections module and how to work with timestamps! Learn to use Object Oriented Programming with classes! Understand complex topics, like decorators. Understand how to use both the Jupyter Notebook and create .py files Get an understanding of how to create GUIs in the Jupyter Notebook system! Build a complete understanding of Python from the ground up!</p><p></p><p>Our Introduction to Python course is designed to take complete beginners or experienced developers up to speed on Python?s capabilities, setting up students for success in using Python for their specific field of expertise.</p> <p> Whether you have never programmed before, already know basic syntax, or want to learn about the advanced features of Python, this course is for you! In this course we will teach you Python 3. Learn how to use Python for real-world tasks, such as working with PDF Files, sending emails, reading Excel files, scraping websites for information, working with image files, and much more! This course will teach you Python in a practical manner and provides a full coding screencast and a corresponding code notebook to review the concepts and exercises conducted in class.</p>  <p><b>Please note, this course is able to be offered in either 3 full day sessions or 5 partial day sessions.  See the schedule below.</b></p><p>This course includes 6-months access to the full course content in on-demand format to support post-class reference and review.</p><p></p></div><div id="course-pills-2"><ul><li>Command Line Basics</li> <li>Python System Setup</li> <li>Jupyter Notebooks</li> <li>Python Data Types</li> <li>Key Data Structures</li> <li>Logic and Control Flow</li> <li>Functions</li> <li>Debugging</li> <li>Modules</li> <li>Object Oriented Programming</li> <li>File I/O</li> <li>Testing</li> <li>Decorators</li> <li>Generators</li> <li>Automation of Tasks</li> <li>Web Scraping</li> <li>Graphical User Interfaces</li></ul></div><div id="course-pills-3"><h4>Additional course details:</h4><br /><p>Nexus Humans Introduction to Python training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. </p><p></p> This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. <p></p>Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.  <p></p>While we feel this is the best course for the Introduction to Python course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.  <p></p>Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.<p></p></div>

Nexus Human

Online Course Creation

Trainers Course

Introduction to Python

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				<div>
			<h2>Overview</h2>		</div>
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							<p><span>Python Programming for Kids and Beginners Course is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this Python Programming for Kids and Beginners Course and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills.</span></p><p><span>Consisting of several modules, the course teaches you everything you need to succeed in this profession.</span></p><p><span>The course can be studied part-time. You can become accredited within 05 Hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website.</span></p>						</div>
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			<h3><b>Why Choose Teachers Training</b></h3>		</div>
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			<p>Some of our website features are:</p>		</div>
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										<span>This is a dedicated website for teaching</span>
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										<span>Courses accredited by the UK's top awarding bodies</span>
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										<span>100% online </span>
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			<h3><b> Entry Requirements
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			<p>No formal entry requirements. You need to have:</p>		</div>
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			<h3><b>Certification</b></h3>		</div>
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							<p><strong>CPD Certification from The Teachers Training</strong></p><p>Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish.</p><ul><li>You can get your digital certificate (PDF) for £4.99 only</li><li>Hard copy certificates are also available, and you can get one for only £10.99</li><li>You can get both PDF and Hard copy certificates for just £12.99!</li></ul><p>The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs.</p>						</div>
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							</div><table width="100%">				<tbody><tr>
					<td colspan="4">Section 01: Introduction to the Course</td>
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					<td><i></i></td>
					<td>Introduction</td>
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					<td><span><i></i> 00:02:00</span></td>
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					<td>Course Curriculum</td>
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					<td><span><i></i> 00:03:00</span></td>
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					<td>How to Get Pre-Requisites</td>
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					<td><span><i></i> 00:02:00</span></td>
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					<td>Getting started on Windows, Linux or MacOs</td>
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					<td><span><i></i> 00:02:00</span></td>
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					<td>How to ask Great Questions</td>
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					<td><span><i></i> 00:02:00</span></td>
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					<td colspan="4">Section 02: Setting up Local Coding Environment</td>
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					<td>What is Python</td>
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					<td>Installing Python step by step</td>
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					<td>Setting up Pycharm for project</td>
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					<td><span><i></i> 00:04:00</span></td>
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					<td>Installing Pycharm IDE (Code Editor)</td>
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					<td><span><i></i> 00:08:00</span></td>
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					<td>Creating Python .py files</td>
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					<td><span><i></i> 00:03:00</span></td>
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					<td colspan="4">Section 03: Drawing with Python - Level 1</td>
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					<td>Introduction to turtle</td>
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					<td>Move your turtle</td>
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					<td>Create triangle</td>
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					<td><span><i></i> 00:04:00</span></td>
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					<td><span><i></i> 00:01:00</span></td>
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					<td colspan="4">Section 03: Drawing with Python - Level 1</td>
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					<td>Introduction to variables</td>
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					<td><span><i></i> 00:07:00</span></td>
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					<td>Learn Maths with coding</td>
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					<td>Solution for assessment 2</td>
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					<td colspan="4">Section 05: Logical operators</td>
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					<td>Introduction to operators</td>
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					<td><span><i></i> 00:04:00</span></td>
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					<td>AND operator</td>
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					<td><span><i></i> 00:04:00</span></td>
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					<td>OR operator</td>
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					<td>Solution for assessment 3</td>
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					<td colspan="4">Section 06: IF-else Statements</td>
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					<td>If-else Introduction</td>
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					<td><span><i></i> 00:03:00</span></td>
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					<td><span><i></i> 00:05:00</span></td>
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					<td><span><i></i> 00:03:00</span></td>
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					<td>Solution for assessment 4</td>
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					<td><span><i></i> 00:02:00</span></td>
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					<td colspan="4">Section 07: Creating Patterns</td>
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					<td>Creating Patterns</td>
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					<td><span><i></i> 00:03:00</span></td>
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					<td>How to Repeat</td>
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					<td><span><i></i> 00:04:00</span></td>
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					<td>How a For Loop Works</td>
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					<td><span><i></i> 00:03:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Let's Experiment</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
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					<td>Results</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assessment 5</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
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					<td>Solution for Assessment 5</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
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					<td colspan="4">Section 08: Drawing with Python - Level 2</td>
				</tr>
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					<td>Adding colour</td>
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					<td><span><i></i> 00:02:00</span></td>
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					<td>Create circle</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
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					<td>Fill Colors on circles</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
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					<td>Dots, Pensize</td>
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					<td><span><i></i> 00:03:00</span></td>
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					<td>Assessment 6</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution for assessment 6</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
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					<td colspan="4">Section 09: Project</td>
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					<td><i></i></td>
					<td>Project overview</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
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					<td>Project Source Code Solution</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
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				</tbody></table>

The Teachers Training

Certificate in Teaching Program (CTP)

Coding For Kids

Teaching Online

Teaching & Training

Python Programming for Kids and Beginners

General Admission

Janets

Data Science

Data Science and Machine Learning using Python : A Bootcamp

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			<h2><b>Course Overview</b></h2>		</div>
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				<div>
					<div><p><span>Make the most of the plotting and AI capabilities of the world's benchmark programming language by taking this course to create </span><b>Spatial Data Visualisation and Machine Learning in Python Level 4. </b><span>Using the intuitive syntax available to you, you will be amazed at the results you can achieve with the power of its libraries and mapping potential for all manner of complex projects.  </span></p><p><span>This comprehensive </span>Python <span>tutorial is an excellent way to learn the important and potentially ground-breaking aspects of machine learning. With the benefit of expert guidance and step-by-step training, IT technology, you will be taken from quick installations to complex coding. You will learn how to become proficient with coding capabilities that will put you at the forefront of advanced programming techniques and the aptitude to envisage AI projects that will impress and be used for practical and useful purposes. </span></p></div>
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					<div><p>This best selling <strong>Spatial Data Visualization and Machine Learning in Python Level 4 </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Spatial Data Visualization and Machine Learning in Python Level 4 </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p>
<p>The <strong>Spatial Data Visualization and Machine Learning in Python Level 4 </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>Spatial Data Visualization and Machine Learning in Python Level 4 </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> Spatial Data Visualization and Machine Learning in Python Level 4</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>Spatial Data Visualization and Machine Learning in Python Level 4 </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>Spatial Data Visualization and Machine Learning in Python Level 4 </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

Spatial Data Visualization and Machine Learning in Python Level 4

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			<div>
					<div>
				<div>
				<div>
					<div>
			<div></div>
		</div>
				</div>
				</div>
				<div>
				<div>
			
				</div>
				<div>
				<div>
					<div><p>Gain the skills and credentials to kickstart a successful career in the technology industry and learn from the experts with this step-by-step training course. This The Complete Python 3 Course: Beginner to Advanced! has been specially designed to help learners gain a good command of Python 3, providing them with a solid foundation of knowledge to become a qualified professional.</p><p>Through this The Complete Python 3 Course: Beginner to Advanced! you will gain both practical and theoretical understanding of Python 3 that will increase your employability in this field, help you stand out from the competition and boost your earning potential in no time.</p><p>Not only that, but this training includes up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the industry. This qualification is fully accredited, broken down into several manageable modules, ideal for aspiring professionals.</p></div>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</div></section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2><b> Learning outcome</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Familiar yourself with the recent development and updates of the relevant industry</span>
									</li>
								<li>
											<span>
													</span>
										<span>Know how to use your theoretical knowledge to adapt in any working environment</span>
									</li>
								<li>
											<span>
													</span>
										<span>Get help from our expert tutors anytime you need</span>
									</li>
								<li>
											<span>
													</span>
										<span>Access to course contents that are designed and prepared by industry professionals</span>
									</li>
								<li>
											<span>
													</span>
										<span>Study at your convenient time and from wherever you want</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
					</div>
				</div>
				<div>
				<div>
					
			</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Why should I take this course?</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Affordable premium-quality E-learning content, you can learn at your own pace.</span>
									</li>
								<li>
											<span>
													</span>
										<span>You will receive a completion certificate upon completing the course.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Internationally recognized Accredited Qualification will boost up your resume.</span>
									</li>
								<li>
											<span>
													</span>
										<span>You will learn the researched and proven approach adopted by successful people to transform their careers.</span>
									</li>
								<li>
											<span>
													</span>
										<span>You will be able to incorporate various techniques successfully and understand your customers better.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Requirements</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>No formal qualifications required, anyone from any academic background can take this course.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Access to a computer or digital device with internet connectivity.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>

Skill Up

Gain the skills and credentials to kickstart a successful career in the technology industry and learn from the

The Complete Python 3 Course: Beginner to Advanced!

<p>Unleash your data superpowers! Join our SQL Bootcamp: Database, Python &amp; Javascript Training and go from zero to hero in record time.</p><p><strong>Did you know that </strong><strong>SQL Training</strong><strong> course are now among the top skills in demand worldwide? </strong>With the help of our SQL training course, you will learn how to write the same language as thousands of <strong>database experts</strong>. Enrol in this SQL course to learn how to<strong> handle huge datasets</strong> and evaluate actual data.</p><p>This SQL training course is designed for students who want to become more <strong> proficient with SQL</strong> queries. You will learn about subjects including SQL fundamentals, environment setup, SQL analysis, building databases and tables, statements, and more with this package.</p><p><strong>What Courses You'll Get?</strong></p><ul><li><strong>Course 01:</strong> The Complete SQL from Scratch: Bootcamp</li><li><strong>Course 02: </strong>Python from Scratch</li><li><strong>Course 03:</strong> Javascript Programming for Beginners</li></ul><p><strong>Learning Outcomes of SQL Training course</strong></p><ul><li>Get introduced to the basics of SQL and environment setup.</li><li>Learn how to create a database and table.</li><li>Explore the statement basics and how to group them.</li><li>Discover the most demanding programming language, Python, from scratch.</li><li>Understand the fundamentals of Javascript.</li></ul><p><strong>Key Highlights of the SQL Course:</strong></p><ul><li>Lifetime Access to All SQL Learning Resources</li><li>An Interactive, Online SQL Course</li><li>Created By Experts in the SQL Field</li><li>Self-Paced SQL courseand 24/7 Learning Support</li><li>Free Certificate After SQL Course Completion</li></ul><p><strong>SQL Bootcamp: Python, JavaScript, and Database Training Curriculum Breakdown: </strong></p><p><strong> Course 01:</strong> The Complete SQL from Scratch: Bootcamp</p><ul><li>SQL Introduction</li><li>Environment Setup</li><li>Creating Database and Tables</li><li>Statement Basics</li><li>GROUP BY Statements</li><li>JOINS</li><li>Advanced Commands</li><li>Databases and Tables</li></ul><p><strong> Course 02: </strong><strong>Python from Scratch</strong></p><ul><li>Python Introduction</li><li>Python Curriculum Overview</li><li>Python Whats New</li><li>Command line basics in python</li><li>python installation</li><li>Pycham-ce ide installation</li><li>Setting up environment</li><li>Running python code</li><li>and more...</li></ul><p><strong> Course 03: Javascript Programming for Beginners</strong></p><ul><li>Introduction</li><li>Project Files</li><li>What is JavaScript?</li><li>Running JS Code</li><li>Variables</li><li>Arithmetic Operators</li><li>Conditional Statement</li><li>and more...</li></ul><h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                            <p>This SQL course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in SQL. It is also great for professionals who are already working in SQL and want to get promoted at work.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Query Language Developer</li><li>Server Database Manager</li><li>SQL Database Administrator</li><li>Python Developer</li><li>Technical Consultant</li><li>Project Implementation Manager</li><li>Software Developer (SQL)</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>3 CDP Accerdited HARDCOPY Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>3 CDP Accerdited HARDCOPY Certificate for Free.</p><p><strong>Delivery Charge:</strong></p><ul><li>Inside the UK: £3.99</li><li>Outside UK: £9.99</li></ul></div>
        <h4>3 CDP Accerdited PDF Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><p>3 CDP Accerdited PDF Certificate for Free</p></div>

                        </div>

Compliance Central

SQL Bootcamp: Python, JavaScript, and Database Training

<div>
						<div>
				<div>
									<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
								<div>
				<p><span>Register on the Python 3 Programming Course for Beginners today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career.</span></p><p><span>The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials.</span></p><p><span>Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a certificate as proof of your course completion.</span></p><p><span>The Python 3 Programming Course for Beginners course is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablets, and smartphones.</span></p><p><span>The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly!</span></p><p><b>What You Get With The Python 3 Programming Course for Beginners course</b></p><ul><li><span>         </span><span>Receive a digital certificate upon successful completion of the course</span></li><li><span>         </span><span>Get taught by experienced, professional instructors</span></li><li><span>         </span><span>Study at a time and pace that suits your learning style</span></li><li><span>         </span><span>Get instant feedback on assessments </span></li><li><span>         </span><span>24/7 help and advice via email or live chat</span></li><li><span>         </span><span>Get full tutor support on weekdays (Monday to Friday)</span></li></ul>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2>Course Design</h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<div id="course-home"><div><p><span>The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.</span></p><p><span>You are taught through a combination of</span></p><ul><li><span>         </span><span>Video lessons</span></li><li><span>         </span><span>Online study materials</span></li></ul></div></div>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2>Certification</h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<p><span>After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post.</span></p>					</div>
						</div>
				</div>
				<div>
				<div>
			<h2>Who Is This Course For:</h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<p><span>The course is ideal for those who already work in this sector or are aspiring professionals. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.</span></p>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2>Requirements:</h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<p><span>The online training is open to all students and has no formal entry requirements. To study the Python 3 Programming Course for Beginners course, all you need is a passion for learning, A good understanding of English, numeracy, and IT skills. You must also be over the age of 16.</span></p>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
									</div>
			</div>
					</div><div>
				<h3>Course Content</h3>

<div id="course_curriculum">
<table width="100%">				<tbody><tr>
					<td colspan="4">Section 01</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>A Installing Python</td>
					<td> </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 colspan="4">Section 02</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><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 colspan="4">Section 03</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><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> 00:14:00</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">Section 04</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 colspan="4">Section 05</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><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>Data Hiding</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
				</tbody></table></div>

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

Python 3 Programming Course for Beginners

<strong>In this self-paced course, you will learn how to use TensorFlow 2 to build deep neural networks. You will learn the basics of machine learning, classification, and regression. We will also discuss the connection between artificial and biological neural networks and how that inspires our thinking in deep 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 and machine learning. So, if you want to do deep learning, you got to know TensorFlow.

In this course, you will learn how to use TensorFlow 2 to build deep neural networks. We will first start by learning the basics of machine learning, classification, and regression. Then in the next section, we will understand the connection between artificial neural networks and biological neural networks and how that inspires our thinking in the field of deep learning.

In the last two sections, you will learn about loss functions to understand mean squared error, binary cross entropy, and categorical cross entropy and gradient descent to understand stochastic gradient descent, momentum, variable and adaptive learning rates, and Adam optimization.

By the end of this course, we will have understood how to use TensorFlow for artificial neural networks in deep learning.</p>
        <h2>What You Will Learn</h2><p>Understand what machine learning is<br>Build linear models with TensorFlow 2<br>Learn how to build deep neural networks with TensorFlow 2<br>Learn how to perform image classification and regression with ANN<br>Learn loss functions such as mean-squared error and cross-entropy loss<br>Learn about stochastic gradient descent, momentum, and Adam optimization</p>
        <h2>Audience</h2><p>This course is designed for anyone interested in deep learning and machine learning, anyone who wants to implement deep neural networks in TensorFlow 2, or anyone interested in building a foundation for convolutional neural networks, recurrent neural networks, LSTMs (Long Short Term Memory), and transformers.<br><br>One must have decent Python programming skills and should be comfortable 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 artificial neural networks. The course is well-balanced with theory that explains the ANN concepts and hands-on coding exercises for practical understanding.</p>
        <h2>Key Features</h2><p>Understand the utilization of TensorFlow 2 to construct artificial neural networks * The course covers the basics of machine learning, classification, and regression * Explore the connection between artificial neural networks and biological neural networks</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>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><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. Machine Learning and Neurons</h4><p>In this section, we will cover a crash course on machine learning and neurons. You will learn about classification and regression, and their TensorFlow implementations.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What Is Machine Learning?</p><p style='margin: 0'>In this video, we will understand what machine learning is and get a clear idea about ML (machine learning).</p></td></tr><tr><td style='padding: 15px;'><p>2. Code Preparation (Classification Theory)</p><p style='margin: 0'>In this video, we will take a crash course in linear classification for TensorFlow 2.0.</p></td></tr><tr><td style='padding: 15px;'><p>3. Classification Notebook</p><p style='margin: 0'>In this video, we will understand linear classification with the help of breast cancer dataset example.</p></td></tr><tr><td style='padding: 15px;'><p>4. Code Preparation (Regression Theory)</p><p style='margin: 0'>In this video, we will take a crash course in linear regression for TensorFlow 2.0.</p></td></tr><tr><td style='padding: 15px;'><p>5. Regression Notebook</p><p style='margin: 0'>In this video, we will understand linear regression by proving the Mosse law true.</p></td></tr><tr><td style='padding: 15px;'><p>6. The Neuron</p><p style='margin: 0'>In this video, we will understand the neuron.</p></td></tr><tr><td style='padding: 15px;'><p>7. How Does a Model 'Learn'?</p><p style='margin: 0'>In this video, we will understand how a model 'learns'.</p></td></tr><tr><td style='padding: 15px;'><p>8. Making Predictions</p><p style='margin: 0'>In this video, we will be talking about another important part of creating a model, which is making predictions.</p></td></tr><tr><td style='padding: 15px;'><p>9. Saving and Loading a Model</p><p style='margin: 0'>In this video, you will learn how to save a model and then load it later.</p></td></tr><tr><td style='padding: 15px;'><p>10. Why Keras?</p><p style='margin: 0'>In this video, we will understand why we use Keras in this course and not TensorFlow 2.</p></td></tr><tr><td style='padding: 15px;'><p>11. Suggestion Box</p><p style='margin: 0'>In this video, we will have a look at the suggestion box where we can add feedback for this course.</p></td></tr></tbody></table><br><h4>3. Feedforward Artificial Neural Networks</h4><p>In this section, we will cover feedforward artificial neural networks.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Artificial Neural Networks Section Introduction</p><p style='margin: 0'>In this video, we will get introduced to artificial neural networks.</p></td></tr><tr><td style='padding: 15px;'><p>2. Forward Propagation</p><p style='margin: 0'>In this video, you will learn about forward propagation as it is related to neural networks.</p></td></tr><tr><td style='padding: 15px;'><p>3. The Geometrical Picture</p><p style='margin: 0'>In this video, we will understand the geometrical picture by understanding why neural networks are so important instead of a single neural network.</p></td></tr><tr><td style='padding: 15px;'><p>4. Activation Functions</p><p style='margin: 0'>In this video, you will learn about activation functions.</p></td></tr><tr><td style='padding: 15px;'><p>5. Multiclass Classification</p><p style='margin: 0'>In this video, you will learn about multiclass classification.</p></td></tr><tr><td style='padding: 15px;'><p>6. How to Represent Images</p><p style='margin: 0'>In this video, we will discuss data and understand how to represent images.</p></td></tr><tr><td style='padding: 15px;'><p>7. Code Preparation (Artificial Neural Networks)</p><p style='margin: 0'>In this video, we will work with the MNIST dataset and ANN code preparation.</p></td></tr><tr><td style='padding: 15px;'><p>8. ANN for Image Classification</p><p style='margin: 0'>In this video, we will work on image classification with the MNIST dataset.</p></td></tr><tr><td style='padding: 15px;'><p>9. ANN for Regression</p><p style='margin: 0'>In this video, we will understand regression in ANN.</p></td></tr><tr><td style='padding: 15px;'><p>10. How to Choose Hyperparameters</p><p style='margin: 0'>In this video, we will understand how to choose hyperparameters.</p></td></tr></tbody></table><br><h4>4. In-Depth: Loss Functions</h4><p>In this optional section, we will dive deeper into loss functions.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Mean Squared Error</p><p style='margin: 0'>In this video, we will understand MSE (Mean Squared Error) from a probabilistic perspective.</p></td></tr><tr><td style='padding: 15px;'><p>2. Binary Cross Entropy</p><p style='margin: 0'>In this video, you will learn about binary cross entropy, which is the correct loss function to use for binary classification.</p></td></tr><tr><td style='padding: 15px;'><p>3. Categorical Cross Entropy</p><p style='margin: 0'>In this video, you will learn about categorical cross entropy, which is used in multiclass classification.</p></td></tr></tbody></table><br><h4>5. In-Depth: Gradient Descent</h4><p>In this optional section, we will dive deeper into gradient descent.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Gradient Descent</p><p style='margin: 0'>In this video, we will get introduced to gradient descent.</p></td></tr><tr><td style='padding: 15px;'><p>2. Stochastic Gradient Descent</p><p style='margin: 0'>In this video, you will learn about stochastic gradient descent.</p></td></tr><tr><td style='padding: 15px;'><p>3. Momentum</p><p style='margin: 0'>In this video, you will learn about momentum.</p></td></tr><tr><td style='padding: 15px;'><p>4. Variable and Adaptive Learning Rates</p><p style='margin: 0'>In this video, we will discuss variable and adaptive learning rates.</p></td></tr><tr><td style='padding: 15px;'><p>5. Adam Optimization (Part 1)</p><p style='margin: 0'>In this video, we will talk about Adam optimization, get introduced to Adam, and understand its basics.</p></td></tr><tr><td style='padding: 15px;'><p>6. Adam Optimization (Part 2)</p><p style='margin: 0'>In this video, we will understand more about Adam optimization.</p></td></tr></tbody></table>

Packt

Python

TensorFlow

In this self-paced course, you will learn how to use TensorFlow 2 to build deep neural networks. You will learn the basics of machine learning, classification, and regression. We will also discuss the connection between artificial and biological neural networks and how that inspires our thinking in deep learning.

Deep Learning - Artificial Neural Networks with TensorFlow

<p>Dive deep into the vast realm of Python data science with our meticulously crafted course: '<strong>Python Data Science with Numpy, Pandas and Matplotlib</strong>'. Explore the intricate details of Python, setting the stage with Pandas and Numpy, before delving into the power of Python data structures. With topics ranging from Python Strings to Matplotlib Histograms, you'll gain a holistic insight, ensuring that every dataset you touch unveils its story compellingly. So, if you're keen on transmuting raw data into visual masterpieces or insights, this journey is tailor-made for you.</p>
<p><strong>Learning Outcomes</strong></p>
<ul>
<li>Grasp foundational knowledge of Python and its data structures like strings, lists, and dictionaries.</li>
<li>Understand the potential of NumPy, from basic array operations to handling multi-dimensional arrays.</li>
<li>Master the versatility of Pandas, encompassing everything from dataframe conversions to intricate operations like aggregation and binning.</li>
<li>Efficiently manage, manipulate, and transform data using Pandas' diverse functionalities.</li>
<li>Create visually striking and informative graphs using the power of Matplotlib.</li>
</ul>
<h3><b>Why buy this Python Data Science with Numpy, Pandas and Matplotlib<span> course</span>?</b></h3>
<ol>
<li><span>Unlimited access to the course for forever</span></li>
<li><b>Digital Certificate, Transcript, student ID</b><span> all included in the price</span></li>
<li><span>Absolutely no hidden fees</span></li>
<li><span>Directly receive </span><b>CPD </b><span>accredited qualifications after course completion</span></li>
<li><span>Receive one to one assistance on every weekday from professionals</span></li>
<li><span>Immediately receive the PDF certificate after passing</span></li>
<li><span>Receive the original copies of your certificate and transcript on the next working day</span></li>
<li><span>Easily learn the skills and knowledge from the comfort of your home</span></li>
</ol>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials of the </span><b>Python Data Science with Numpy, Pandas and Matplotlib</b><span> 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 will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60.</span></p>
<h3><b>Who is this Python Data Science with Numpy, Pandas and Matplotlib<span> </span></b><b><span>course </span></b><b>for?</b></h3>
<ul>
<li>Beginners eager to jumpstart their journey in Python data science.</li>
<li>Analysts looking to enhance their data manipulation skills using Python.</li>
<li>Statisticians keen on expanding their toolset with Python-based libraries.</li>
<li>Data enthusiasts desiring a deep dive into Python's data libraries and structures.</li>
<li>Professionals aiming to upgrade their data visualisation techniques.</li>
</ul>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>Python Data Science with Numpy, Pandas and Matplotlib</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning.This </span><b>Python Data Science with Numpy, Pandas and Matplotlib</b><span> was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.</span></p>
<h3><b>Career path</b></h3>
<ul>
<li><strong>Data Scientist</strong>: £40,000 - £80,000</li>
<li><strong>Python Developer</strong>: £35,000 - £70,000</li>
<li><strong>Data Analyst</strong>: £30,000 - £55,000</li>
<li><strong>Business Intelligence Analyst</strong>: £32,000 - £60,000</li>
<li><strong>Research Analyst</strong>: £28,000 - £52,000</li>
<li><strong>Data Visualization Engineer</strong>: £33,000 - £65,000</li>
</ul><div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4">Course Introduction and Table of Contents</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Course Introduction and Table of Contents</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Introduction to Python, Pandas and Numpy</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Python, Pandas and Numpy</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">System and Environment Setup</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>System and Environment Setup</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Python Strings</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Strings - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Strings - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Python Numbers and Operators</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Numbers and Operators - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Numbers and Operators - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Python Lists</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Lists - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Lists - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Lists - Part 3</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Lists - Part 4</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Lists - Part 5</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Tuples in Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Tuples in Python</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Sets in Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Sets in Python - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Sets in Python - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Python Dictionary</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Dictionary - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Python Dictionary - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">NumPy Library - Introduction</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>NumPy Library Intro - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>NumPy Library Intro - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>NumPy Library Intro - Part 3</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">NumPy Array Operations and Indexing</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>NumPy Array Operations and Indexing - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>NumPy Array Operations and Indexing - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">NumPy Multi-Dimensional Arrays</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>NumPy Multi-Dimensional Arrays - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>NumPy Multi-Dimensional Arrays - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>NumPy Multi-Dimensional Arrays - Part 3</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Introduction to Pandas Series</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Pandas Series</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Introduction to Pandas Dataframes</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Pandas Dataframes</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Dataframe conversion and drop</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Dataframe conversion and drop - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Dataframe conversion and drop - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Dataframe conversion and drop - Part 3</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Dataframe summary and selection</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Dataframe summary and selection - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Dataframe summary and selection - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Dataframe summary and selection - Part 3</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Missing Data Management and Sorting</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Missing Data Management and Sorting - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Missing Data Management and Sorting - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Hierarchical-Multi Indexing</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Hierarchical-Multi Indexing</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas CSV File Read Write</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas CSV File Read Write - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas CSV File Read Write - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas JSON File Read Write</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas JSON File Read Write Operations</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Concatenation Merging and Joining</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Concatenation Merging and Joining - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Concatenation Merging and Joining - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Concatenation Merging and Joining - Part 3</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Stacking and Pivoting</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Stacking and Pivoting - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Stacking and Pivoting - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Duplicate Data Management</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Duplicate Data Management</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Mapping</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Mapping</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Grouping</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Groupby</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Aggregation</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Aggregation</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Binning or Bucketing</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Binning or Bucketing</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Re-index and Rename</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Re-index and Rename - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Re-index and Rename - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Replace Values</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Replace Values</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Dataframe Metrics</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Dataframe Metrics</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Random Permutation</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Random Permutation</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Excel sheet Import</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Excel sheet Import</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Condition Selection and Lambda Function</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Condition Selection and Lambda Function - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Condition Selection and Lambda Function - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Ranks Min Max</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Ranks Min Max</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Pandas Cross Tabulation</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Pandas Cross Tabulation</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Matplotlib Graphs and plots</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Graphs and plots using Matplotlib - Part 1</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Graphs and plots using Matplotlib - Part 2</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Matplotlib Histograms</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Matplotlib Histograms</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Resource File</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Resource File - Python Data Science with Numpy, Pandas and Matplotlib</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Studyhub UK

Python Data Science with Numpy, Pandas and Matplotlib

<section>
						<div>
					<div>
			<div>
								<div>
				<div>
			<h2>Overview</h2>		</div>
				</div>
				<div>
				<div>
							<p><span>By enroling in Machine Learning for Predictive Maps in Python and Leaflet, you can kickstart your vibrant career and strengthen your profound knowledge. You can learn everything you need to know about the topic.</span></p><p><span>The Machine Learning for Predictive Maps in Python and Leaflet course includes all of the most recent information to keep you abreast of the employment market and prepare you for your future. The curriculum for this excellent Machine Learning for Predictive Maps in Python and Leaflet course includes modules at all skill levels, from beginner to expert. You will have the productivity necessary to succeed in your organisation once you have completed our Machine Learning for Predictive Maps in Python and Leaflet Program.</span></p><p><span>So enrol in our Machine Learning for Predictive Maps in Python and Leaflet course right away if you're keen to envision yourself in a rewarding career.</span></p>						</div>
				</div>
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		</section>
				<section>
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								<div>
				<div>
			<h2><b>Description</b>
</h2>		</div>
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				<div>
				<div>
							<p><span>Enroling in this Machine Learning for Predictive Maps in Python and Leaflet course can improve your Machine Learning for Predictive Maps in Python and Leaflet perspective, regardless of your skill levels in the Machine Learning for Predictive Maps in Python and Leaflet topics you want to master. If you're already a Machine Learning for Predictive Maps in Python and Leaflet expert, this peek under the hood will provide you with suggestions for accelerating your learning, including advanced Machine Learning for Predictive Maps in Python and Leaflet insights that will help you make the most of your time. This Machine Learning for Predictive Maps in Python and Leaflet course will act as a guide for you if you've ever wished to excel at Machine Learning for Predictive Maps in Python and Leaflet.</span></p>						</div>
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							</div>
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			<h2>Why Choose Us?</h2>		</div>
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							<ul><li><span>After successfully completing the Machine Learning for Predictive Maps in Python and Leaflet Course, you will receive a </span><b>FREE PDF Certificate </b><span>as evidence of your newly acquired abilities.</span></li><li><span>Lifetime access to the whole collection of Machine Learning for Predictive Maps in Python and Leaflet learning materials.</span></li><li><span>Online test with immediate results</span></li><li><span>Enroling in the course has no additional cost.</span></li><li><span>You can study and complete the Machine Learning for Predictive Maps in Python and Leaflet course at your own pace.</span></li><li><span>Study for the Machine Learning for Predictive Maps in Python and Leaflet course using any internet-connected device, such as a computer, tablet, or mobile device.</span></li></ul>						</div>
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		</section>
				<section>
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								<div>
				<div>
			<h2>Who Is This Course For?</h2>		</div>
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				<div>
							<p><span>This Machine Learning for Predictive Maps in Python and Leaflet course is a great place to start if you're looking to start a new career in Machine Learning for Predictive Maps in Python and Leaflet field. This training is for anyone interested in gaining in-demand Machine Learning for Predictive Maps in Python and Leaflet proficiency to help launch a career or their business aptitude. </span></p>						</div>
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		</section>
				<section>
						<div>
					<div>
			<div>
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				<div>
			<h2>Requirements</h2>		</div>
				</div>
				<div>
				<div>
							<p><span>The Machine Learning for Predictive Maps in Python and Leaflet course requires no prior degree or experience. All you require is English proficiency, numeracy literacy and a gadget with stable internet connection. Learn and train for a prosperous career in the thriving and fast-growing industry of Machine Learning for Predictive Maps in Python and Leaflet, without any fuss.</span></p>						</div>
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		</section>
				<section>
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					<div>
			<div>
								<div>
				<div>
			<h2>Career Path</h2>		</div>
				</div>
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							<p><span>This Machine Learning for Predictive Maps in Python and Leaflet training will assist you develop your Machine Learning for Predictive Maps in Python and Leaflet ability, establish a personal brand, and present a portfolio of relevant talents. It will help you articulate a  Machine Learning for Predictive Maps in Python and Leaflet professional story and personalise your path to a new career. Furthermore, developing this Machine Learning for Predictive Maps in Python and Leaflet skillset can lead to numerous opportunities for high-paying jobs in a variety of fields.</span></p>						</div>
				</div>
					</div>
		</div>
							</div>
		</section> <div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table>				<tbody><tr>
					<td colspan="4">Section 01: Introduction</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<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>
								<tr>
					<td><i></i></td>
					<td>Creating a Python Virtual Environment</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Installing Django</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Installing Visual Studio Code IDE</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Installing PostgreSQL Database Server Part 1</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Installing PostgreSQL Database Server Part 2</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 03: Writing the Django Server-Side Code</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Adding the settings.py Code</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating a Django Model</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Adding the admin.py Code</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
				</tr>
								<tr>
					<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>
				</tbody></table></div>

			</div>

NextGen Learning

Machine Learning for Predictive Maps in Python and Leaflet Course

<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>

Data Engineering

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

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.
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 Python Certification - IT Program today and start your journey to becoming a successful Python Programmer!
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 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.
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 Python Programming, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Python Programming begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
This Python Certification Course is suitable for:
Beginners with no prior programming experience who are looking to enter the world of coding.
Intermediate programmers who wish to expand their skills and explore Python's extensive usage.
IT professionals seeking to diversify their skill sets and stay relevant in today's tech-driven market.
Data analysts and scientists who want to leverage Python's powerful libraries for their data processing needs.
Students and recent graduates looking to enhance their employability in the thriving tech industry.
Entrepreneurs who wish to understand and utilise Python to automate tasks and analyse data for their businesses.
Anyone with a keen interest in Python programming and a desire to delve into its applications in diverse fields like web development, data science, machine learning, and more.
 Requirements 
No experience required. Just enrol & start learning python.
 Career path 
Upon completion of our Program, the potential career paths include:
Python Developer: £30,000 - £90,000 annually
Data Scientist: £40,000 - £100,000 annually
Machine Learning Engineer: £50,000 - £110,000 annually
Data Analyst: £35,000 - £85,000 annually
Software Engineer: £35,000 - £95,000 annually
Back-end Developer: £40,000 - £95,000 annually
Web Developer: £30,000 -£85,000 annually
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Academy for Health and Fitness

Programming Fundamentals

Career Development

IT Certifications

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


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

Python Certification - IT Job Ready Program with Money Back Guarantee

<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 

Big Data Analytics

Data Skills

Data Science with Python - IT Job Ready Program with Career Support & 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)

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			<h2><b>Course Overview</b></h2>		</div>
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					<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>
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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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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>Start your career as a Data Scientist and earn upto £90,000/ Year</strong></p><p>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!</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 <strong>Data 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 <strong>Data Scientist</strong> experience, we will guide you towards honing your skills and developing a strong foundation in <strong>Data Science</strong>.<br /><br /></li><li><strong>Tailored CV Building:</strong> 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.<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 <strong>Data Science</strong> 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. <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. 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.</li></ul><p><strong>Here are the courses we will provide once you enrol in the program:</strong></p><ul><li>Course 01: Ultimate Python Training for Beginners</li><li>Course 02: Python Intermediate Training</li><li>Course 03: Python Advanced Training</li><li>Course 04: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 05: Basic Data Analysis</li><li>Course 06: Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</li><li>Course 07: Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</li><li>Course 08: Customer Analytics Training</li><li>Course 09: Google Analytics for Everyone</li><li>Course 10: Google Data Studio: Data Analytics</li><li>Course 11: Big Data Analytics with PySpark Tableau Desktop and MongoDB</li><li>Course 12: Big Data Analytics with PySpark Power BI and MongoDB</li><li>Course 13: Excel Data Analysis</li><li>Course 14: Introduction to Data Analytics with Tableau</li><li>Course 15: Machine Learning with Python Course</li><li>Course 16: Python Programming Bible | Networking, GUI, Email, XML, CGI</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:</strong></p><p><strong>Step 1: Enrol in the Programme</strong></p><p>Begin your exciting journey with us by enrolling in the <strong>Data Scientist </strong>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 <strong>Data Scientist</strong>. 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.</p><p><strong>Step 3 - </strong><strong>Certification upon Course Completion</strong></p><p>After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.</p><p><strong>Step 4: </strong><strong>CV Revamping</strong></p><p>Our team of professionals will build you a compelling CV and <strong>LinkedIn profile</strong>. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the <strong>Data Scientist</strong> industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.</p><p><strong>Step 5: Building Network and Submitting CV</strong></p><p>We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many<strong> high-profile individuals and companies</strong> through your LinkedIn profile.</p><p><strong>Step 6: Interview Preparation</strong></p><p>With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.</p><p><strong>Step 7: Securing Job Interviews</strong></p><p>Leveraging our partnerships with leading companies, <strong>we'll secure job interviews for you</strong>. We'll ensure you get the opportunity to showcase your skills to potential employers and <strong>get the dream job you want</strong>.</p><p><strong>Step 8: Post-Interview Support</strong></p><p>Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.</p><p><strong>Step 9: Celebrate Your New Job!</strong></p><p>Once you've secured your dream job in Data 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.</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 <strong>Data Science</strong> 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>Aspiring data scientists looking to enter the exciting field of data science.</li><li>Professionals from other disciplines who want to transition into the data science domain.</li><li>Software engineers or programmers interested in expanding their skill set to include data science.</li><li>Analysts or researchers who want to enhance their data analysis and modeling capabilities.</li><li>Students or graduates seeking to kick-start their careers in data science with a strong foundation.</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 Analyst: £25,000 - £55,000 per year</li><li>Data Scientist: £40,000 - £85,000 per year</li><li>Machine Learning Engineer: £50,000 - £100,000 per year</li><li>Data Engineer: £45,000 - £80,000 per year</li><li>Business Intelligence Analyst: £35,000 - £65,000 per year</li><li>Data Science Manager: £70,000 - £120,000 per year.</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

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

                        </div>

Start your career as a Data 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 

Data Analyst

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

<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).

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