Name: MongoDB-Mastering MongoDB for Beginners (Theory and Projects)
Price: 101.99 GBP
Availability: InStock

<p>Embark on a transformative journey into the realm of programming with our <strong>Intermediate Python Coding</strong> course. Picture yourself delving deeper into the world of Python, a language known for its versatility and efficiency. This course begins with a refresher introduction, setting a solid foundation before advancing to more complex concepts. It's designed not just to teach but to immerse you in the intricacies of Python. From understanding the fundamentals of classes and methods to unraveling the complexities of Object-Oriented Programming (OOP), each section is a step towards mastering this powerful programming language. Whether you're looking to enhance your coding skills for professional growth or personal satisfaction, this course bridges the gap between basic understanding and advanced proficiency.</p>
<p>As you progress, you'll explore the sophisticated elements of Python, including inheritance, polymorphism, encapsulation, and abstraction. These concepts are not just taught theoretically; you'll see them come to life through practical applications, especially in the creation of Python games. This hands-on approach ensures that you're not just learning concepts but also applying them in real-world scenarios. The course also delves into Python's extensive libraries as you learn about modules, packages, and data handling with Pandas. Completing the course with error and exception handling, you emerge not just as someone who can code but as a problem-solver who can navigate through challenges and create efficient, elegant solutions.</p>
<p><strong>Learning Outcomes</strong></p>
<ul>
<li>Gain a deeper understanding of Python classes, methods, and OOP principles.</li>
<li>Develop skills in implementing inheritance, polymorphism, encapsulation, and abstraction in Python.</li>
<li>Create interactive Python games and applications to apply coding skills practically.</li>
<li>Learn to manage and utilise Python modules, packages, and the Pandas library.</li>
<li>Master error and exception handling in Python for robust coding.</li>
</ul>
<h3><b>Why choose this Intermediate Python Coding<span> course</span>?</b></h3>
<ol>
<li>Unlimited access to the course for a lifetime.</li>
<li>Opportunity to earn a certificate accredited by the <b>CPD Quality Standards</b> and <b>CIQ </b>after completing this course.</li>
<li>Structured lesson planning in line with industry standards.</li>
<li>Immerse yourself in innovative and captivating course materials and activities.</li>
<li>Assessments designed to evaluate advanced cognitive abilities and skill proficiency.</li>
<li>Flexibility to complete the Course at your own pace, on your own schedule.</li>
<li>Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience.</li>
<li>Unlock career resources for CV improvement, interview readiness, and job success.</li>
</ol>
<h3><b>Who is this Intermediate Python Coding<span> </span></b><b><span>course </span></b><b>for?</b></h3>
<ul>
<li>Programmers looking to advance from basic to intermediate Python skills.</li>
<li>Computer science students seeking a deeper understanding of Python.</li>
<li>Software developers aiming to enhance their proficiency in Python.</li>
<li>Data analysts and scientists interested in leveraging Python's capabilities.</li>
<li>Hobbyists and tech enthusiasts keen on developing Python applications.</li>
</ul>
<h3><b>Career path</b></h3>
<ul>
<li><strong>Software Developer</strong>: £30,000 - £60,000</li>
<li><strong>Data Analyst</strong>: £25,000 - £50,000</li>
<li><strong>Python Developer</strong>: £28,000 - £55,000</li>
<li><strong>Machine Learning Engineer</strong>: £32,000 - £70,000</li>
<li><strong>Data Scientist</strong>: £35,000 - £75,000</li>
<li><strong>Back-end Developer</strong>: £27,000 - £53,000</li>
</ul>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>Beginner to Intermediate Python Coding</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning.This </span><b>Beginner to Intermediate Python Coding</b><span> was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.</span></p>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8.</span></p><div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4">Section 01: Introduction</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Course Introduction</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Course Curriculum</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to get Pre-requisites</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Getting Started on Windows, Linux or Mac</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to ask Great Questions</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 02: Class</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Class</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Create a Class</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Calling a Class Object</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Class Parameters - Objects</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Access Modifiers(theory)</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 03: Methods</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to methods</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Create a method</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Method with parameters</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Method default parameter</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Multiple parameters.</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Method return keyword.</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Method Overloading.</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 04: OOPs Object-Oriented Programming</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to OOPs</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Classes and Objects</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Class Constructors</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assessment Test1</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution for Assessment Test1</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 05: Inheritance and Polymorphism</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Inheritance</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Getter and Setter Methods</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Polymorphism</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assessment Test2</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution for Assessment Test2</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 06: Encapsulation and Abstraction</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Access Modifiers (public, protected, private)</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Encapsulation</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Abstraction</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 07: Python Games for Intermediate</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Dice Game</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Card and Deck Game Playing</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 08: Modules and Packages</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>PIP command installations</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Modules</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Naming Module</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Built-in Modules</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Packages</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>List Packages</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 09: Working Files with Pandas</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Reading CSV files</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Writing CSV files</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 10: Error and ExceptionHandling</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Errors - Types of Errors</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Try - ExceptExceptions Handling</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Creating User-Defined Message</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Try-Except-FinallyBlocks</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Studyhub UK

Beginner to Intermediate Python Coding

General Admission

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Introduction to data with python is a 30 hour course, delivered online using SpatialChat (a collaborative online, social space). We use Agile scrum methodology with Trello to manage our learning.</p>
<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The course will usually take place over a number of weeks (e.g. 1 day a week for 5 weeks).&nbsp;&nbsp;</p>
<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You will learn how to&nbsp;</p>
<ul fr-original-style="" style="box-sizing: border-box;">
<li style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;"><span style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;">read data sets from spreadsheets, databases and a range of other data sources</span></li>
<li style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;"><span style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;">&lsquo;clean&rsquo; the data so that reports and statistics are more accurate</span></li>
<li style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;"><span style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;">manipulate the data so that you can present it in different ways</span></li>
<li style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;"><span style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;">run statistical models and to use the result to predict trends</span></li>
<li style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;"><span style="font-weight: 400; box-sizing: border-box;" fr-original-style="font-weight: 400;">visualise data using a range of charts and graphs.&nbsp; </span></li>
</ul>
<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">On completion of this course you could work on real world project analysing and visualising data for a charity.</p>

futureCoders SE

Introduction to web development with React. 
30 Hour course over 5 weeks.

Data with python for improvers

Intro to ... taster

<div><h2> About Course</h2><div><div><div><div><div><div><div><div><p><strong>Master the Fundamentals of Programming with Python</strong></p><p><strong>Course Description</strong></p><p>Embark on an exciting journey into the world of programming with this comprehensive Python course, designed to equip you with the essential skills and knowledge to become a proficient Python programmer. Whether you're a complete beginner or seeking to enhance your existing Python skills, this course caters to all levels of expertise.</p><p><strong>What will be discussed in detail?</strong></p><ul><li><p><strong>Introduction to Python:</strong> Delve into the basics of Python programming, including variables, data types, operators, and control flow statements.</p></li><li><p><strong>Working with Data Types:</strong> Explore the fundamental data types in Python, including numbers, strings, booleans, and lists.</p></li><li><p><strong>Python Strings:</strong> Master the art of manipulating strings, including slicing, concatenation, and string formatting techniques.</p></li><li><p><strong>Python Lists:</strong> Discover the power of lists, one of Python's most versatile data structures, and learn how to create, access, modify, and iterate over lists.</p></li><li><p><strong>Python Casting and Input:</strong> Understand the concept of type casting and learn how to take user input from the console.</p></li><li><p><strong>Python Dictionary:</strong> Uncover the usefulness of dictionaries, another essential data structure in Python, and learn how to store and retrieve data using key-value pairs.</p></li><li><p><strong>Python Date and Time:</strong> Learn how to handle date and time operations in Python, including creating, formatting, and manipulating date and time objects.</p></li><li><p><strong>Python Loop Part 1:</strong> Master the 'for' loop, a fundamental looping construct in Python, to iterate over sequences and perform repetitive tasks.</p></li><li><p><strong>Python Loop Part 2:</strong> Expand your understanding of loops by exploring the 'while' loop, used to execute a block of code repeatedly while a condition remains true.</p></li><li><p><strong>Creating a Function:</strong> Discover the power of functions, reusable blocks of code that perform specific tasks, and learn how to define, call, and pass arguments to functions.</p></li><li><p><strong>Python OOP Part 1:</strong> Delve into the world of Object-Oriented Programming (OOP) with Python, and learn the concepts of classes, objects, inheritance, and polymorphism.</p></li><li><p><strong>Python OOP Part 2:</strong> Enhance your OOP skills by exploring advanced concepts such as abstract classes, multiple inheritance, and operator overloading.</p></li><li><p><strong>Python Advanced OOP Part 1:</strong> Discover more advanced OOP techniques, including class methods, static methods, and decorators.</p></li><li><p><strong>Python Advanced OOP Part 2:</strong> Master the concept of exception handling, a crucial aspect of robust programming, and learn how to handle errors and exceptions effectively.</p></li><li><p><strong>Error Handling:</strong> Understand the importance of error handling in Python programming and learn how to identify, handle, and prevent errors.</p></li><li><p><strong>Python File Handling:</strong> Learn how to read, write, and manipulate files in Python, enabling you to store and retrieve data from external sources.</p></li><li><p><strong>Python Modules:</strong> Explore the concept of modules, reusable code libraries, and discover how to import, use, and create your own modules.</p></li></ul><p><strong>Why should you enroll into it?</strong></p><ul><li><p><strong>Gain a comprehensive understanding of Python programming:</strong> Master the fundamentals of Python programming, from basic syntax to advanced OOP concepts.</p></li><li><p><strong>Develop practical coding skills:</strong> Apply your theoretical knowledge to hands-on coding exercises, solidifying your understanding and building your confidence.</p></li><li><p><strong>Prepare for a career in programming:</strong> Equip yourself with the essential skills required for entry-level programming positions.</p></li><li><p><strong>Enhance your problem-solving abilities:</strong> Learn to think algorithmically and develop effective problem-solving techniques using Python programming.</p></li><li><p><strong>Expand your skillset and knowledge:</strong> Whether you're a beginner or an experienced programmer, this course will broaden your understanding of Python and its capabilities.</p></li></ul><p><strong>What will be taught? (Learning Outcomes/Learning Objectives)</strong></p><ul><li>Understand the fundamental concepts of Python programming</li><li>Work with different data types, including numbers, strings, lists, dictionaries, and Booleans</li><li>Master control flow statements such as 'if', 'elif', and 'else'</li><li>Create and manipulate Python functions</li><li>Implement Object-Oriented Programming (OOP) concepts using classes, objects, inheritance, and polymorphism</li><li>Handle errors and exceptions effectively</li><li>Read, write, and manipulate files in Python</li><li>Import, use, and create Python modules</li></ul></div></div></div></div></div></div><div></div></div></div></div> <div><h3> What Will You Learn?</h3><ul><li> <span></span> <span>Understand the fundamental concepts of Python programming</span></li><li> <span></span> <span>Work with different data types, including numbers, strings, lists, dictionaries, and Booleans</span></li><li> <span></span> <span>Master control flow statements such as 'if', 'elif', and 'else'</span></li><li> <span></span> <span>Create and manipulate Python functions</span></li><li> <span></span> <span>Implement Object-Oriented Programming (OOP) concepts using classes, objects, inheritance, and polymorphism</span></li><li> <span></span> <span>Handle errors and exceptions effectively</span></li><li> <span></span> <span>Read, write, and manipulate files in Python</span></li><li> <span></span> <span>Import, use, and create Python modules</span></li></ul></div><div><h3> Course Content</h3><div><div><h4> Introduction to Python</h4><div><div><ul><li><div> <span></span><h5> Introduction to Python</h5></div><div> </div></li></ul></div></div></div><div><h4> Working with Data Types</h4><div><div><ul><li><div> <span></span><h5> Working with Data Types</h5></div><div> </div></li></ul></div></div></div><div><h4> Python Strings</h4><div><div><ul><li><div> <span></span><h5> Python Strings</h5></div><div> </div></li></ul></div></div></div><div><h4> Python List</h4><div><div><ul><li><div> <span></span><h5> Python List</h5></div><div> </div></li></ul></div></div></div><div><h4> Python Casting and Input</h4><div><div><ul><li><div> <span></span><h5> Python Casting and Input</h5></div><div> </div></li></ul></div></div></div><div><h4> Python Dictionary</h4><div><div><ul><li><div> <span></span><h5> Python Dictionary</h5></div><div> </div></li></ul></div></div></div><div><h4> Python Date and Time</h4><div><div><ul><li><div> <span></span><h5> Python Date and Time</h5></div><div> </div></li></ul></div></div></div><div><h4> Python Loop (Part - 1)</h4><div><div><ul><li><div> <span></span><h5> Python Loop (Part - 1)</h5></div><div> </div></li></ul></div></div></div><div><h4> Python Loop (Part - 2)</h4><div><div><ul><li><div> <span></span><h5> Python Loop (Part - 2)</h5></div><div> </div></li></ul></div></div></div><div><h4> Python While Loop</h4><div><div><ul><li><div> <span></span><h5> Python While Loop</h5></div><div> </div></li></ul></div></div></div><div><h4> Creating a Function</h4><div><div><ul><li><div> <span></span><h5> Creating a Function</h5></div><div> </div></li></ul></div></div></div><div><h4> Python OOP (Part - 1)</h4><div><div><ul><li><div> <span></span><h5> Python OOP (Part - 1)</h5></div><div> </div></li></ul></div></div></div><div><h4> Python OOP (Part - 2)</h4><div><div><ul><li><div> <span></span><h5> Python OOP (Part - 2)</h5></div><div> </div></li></ul></div></div></div><div><h4> Python Advanced OOP (Part - 1)</h4><div><div><ul><li><div> <span></span><h5> Python Advanced OOP (Part - 1)</h5></div><div> </div></li></ul></div></div></div><div><h4> Python Advanced OOP (Part - 2)</h4><div><div><ul><li><div> <span></span><h5> Python Advanced OOP (Part - 2)</h5></div><div> </div></li></ul></div></div></div><div><h4> Error Handling</h4><div><div><ul><li><div> <span></span><h5> Error Handling</h5></div><div> </div></li></ul></div></div></div><div><h4> Python File Handling</h4><div><div><ul><li><div> <span></span><h5> Python File Handling</h5></div><div> </div></li></ul></div></div></div><div><h4> Python Modules</h4><div><div><ul><li><div> <span></span><h5> Python Modules</h5></div><div> </div></li></ul></div></div></div></div></div>A course by  Uditha Bandara  Microsoft Most Valuable Professional (MVP) RequirementsA basic understanding of computers and operating systemsA willingness to learn and practice codingA computer with internet access and the ability to install Python Audience  Beginners with no prior programming experience  Programmers seeking to transition to Python  Individuals looking to enhance their programming skills and knowledge  Anyone interested in pursuing a career in programming<h3> Audience</h3><ul><li> <span></span> <span>Beginners with no prior programming experience</span></li><li> <span></span> <span>Programmers seeking to transition to Python</span></li><li> <span></span> <span>Individuals looking to enhance their programming skills and knowledge</span></li><li> <span></span> <span>Anyone interested in pursuing a career in programming</span></li></ul>

Xpert Learning

Programming Fundamentals

Computer Programming

Programming with Python

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					<div><p><span>Be efficient in Python programming &amp; boost your skills with the U&amp;P AI - Natural Language Processing with Python</span><b> </b><span>course.</span> <span>This course has been specially designed to help learners gain a good command of U&amp;P AI - Natural Language Processing with Python, providing them with a solid foundation of knowledge to become a qualified professional.</span></p><p><span>With this course, containing on-demand video lectures and downloadable resources and affordable premium-quality E-learning content, you can learn at your own pace. The U&amp;P AI - Natural Language Processing with Python </span><span>covers the NPL, WordNet, Word2Vec applications which will allow you to enhance your CV, impress potential employers, and stand out from the crowd. The course will equip you with everything you need to succeed.</span></p><p><span>If you are looking for up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the tech industry, this is the right place. Enrol in U&amp;P AI - Natural Language Processing with Python</span><span> course today and learn from the very best the industry has to offer!</span></p></div>
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										<span>Explore and represent the Topic of Natural Language Text</span>
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Skill Up

Online Course Marketing

NLP Practitioner

Be efficient in Python programming & boost your skills with the U&P AI - Natural Language Processing with

U&P AI - Natural Language Processing with Python

<h3><strong>Overview</strong></h3>
This comprehensive course on <strong>Python for Data Analysis</strong> will deepen your understanding on this topic.

After successful completion of this course you can acquire the required skills in this sector. This <strong>Python for Data Analysis</strong> comes with accredited certification, which will enhance your CV and make you worthy in the job market.

So enrol in this course today to fast track your career ladder.
<h3><strong>How will I get my certificate?</strong></h3>
You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.
<h3><strong>Who is this course for?</strong></h3>
There is no experience or previous qualifications required for enrolment on this <strong>Python for Data Analysis</strong>. It is available to all students, of all academic backgrounds.
<h3><strong>Requirements</strong></h3>
Our <strong>Python for Data Analysis</strong> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.

There is no time limit for completing this course, it can be studied in your own time at your own pace.
<h3><strong>Career path</strong></h3>
Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business &amp; Management, Admin, Accountancy &amp; Finance, Secretarial &amp; PA, Teaching &amp; Mentoring etc. <h3>Course Curriculum</h3><div><p>19 sections • 99 lectures • 00:08:00 total length</p></div><div><div><div><div><div><div><div><p>•Welcome &amp; Course Overview: 00:07:00</p></div><div><div><p>•Set-up the Environment for the Course (lecture 1): 00:09:00</p></div><div><div><p>•Set-up the Environment for the Course (lecture 2): 00:25:00</p></div><div><div><p>•Two other options to setup environment: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Python data types Part 1: 00:21:00</p></div><div><div><p>•Python Data Types Part 2: 00:15:00</p></div><div><div><p>•Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00</p></div><div><div><p>•Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00</p></div><div><div><p>•Python Essentials Exercises Overview: 00:02:00</p></div><div><div><p>•Python Essentials Exercises Solutions: 00:22:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•What is Numpy? A brief introduction and installation instructions.: 00:03:00</p></div><div><div><p>•NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00</p></div><div><div><p>•NumPy Essentials - Indexing, slicing, broadcasting &amp; boolean masking: 00:26:00</p></div><div><div><p>•NumPy Essentials - Arithmetic Operations &amp; Universal Functions: 00:07:00</p></div><div><div><p>•NumPy Essentials Exercises Overview: 00:02:00</p></div><div><div><p>•NumPy Essentials Exercises Solutions: 00:25:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•What is pandas? A brief introduction and installation instructions.: 00:02:00</p></div><div><div><p>•Pandas Introduction: 00:02:00</p></div><div><div><p>•Pandas Essentials - Pandas Data Structures - Series: 00:20:00</p></div><div><div><p>•Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00</p></div><div><div><p>•Pandas Essentials - Handling Missing Data: 00:12:00</p></div><div><div><p>•Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00</p></div><div><div><p>•Pandas Essentials - Groupby: 00:10:00</p></div><div><div><p>•Pandas Essentials - Useful Methods and Operations: 00:26:00</p></div><div><div><p>•Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00</p></div><div><div><p>•Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00</p></div><div><div><p>•Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00</p></div><div><div><p>•Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Matplotlib Essentials (Part 1) - Basic Plotting &amp; Object Oriented Approach: 00:13:00</p></div><div><div><p>•Matplotlib Essentials (Part 2) - Basic Plotting &amp; Object Oriented Approach: 00:22:00</p></div><div><div><p>•Matplotlib Essentials (Part 3) - Basic Plotting &amp; Object Oriented Approach: 00:22:00</p></div><div><div><p>•Matplotlib Essentials - Exercises Overview: 00:06:00</p></div><div><div><p>•Matplotlib Essentials - Exercises Solutions: 00:21:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Seaborn - Introduction &amp; Installation: 00:04:00</p></div><div><div><p>•Seaborn - Distribution Plots: 00:25:00</p></div><div><div><p>•Seaborn - Categorical Plots (Part 1): 00:21:00</p></div><div><div><p>•Seaborn - Categorical Plots (Part 2): 00:16:00</p></div><div><div><p>•Seborn-Axis Grids: 00:25:00</p></div><div><div><p>•Seaborn - Matrix Plots: 00:13:00</p></div><div><div><p>•Seaborn - Regression Plots: 00:11:00</p></div><div><div><p>•Seaborn - Controlling Figure Aesthetics: 00:10:00</p></div><div><div><p>•Seaborn - Exercises Overview: 00:04:00</p></div><div><div><p>•Seaborn - Exercise Solutions: 00:19:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Pandas Built-in Data Visualization: 00:34:00</p></div><div><div><p>•Pandas Data Visualization Exercises Overview: 00:03:00</p></div><div><div><p>•Panda Data Visualization Exercises Solutions: 00:13:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Plotly &amp; Cufflinks - Interactive &amp; Geographical Plotting (Part 1): 00:19:00</p></div><div><div><p>•Plotly &amp; Cufflinks - Interactive &amp; Geographical Plotting (Part 2): 00:14:00</p></div><div><div><p>•Plotly &amp; Cufflinks - Interactive &amp; Geographical Plotting Exercises (Overview): 00:11:00</p></div><div><div><p>•Plotly &amp; Cufflinks - Interactive &amp; Geographical Plotting Exercises (Solutions): 00:37:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00</p></div><div><div><p>•Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00</p></div><div><div><p>•Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00</p></div><div><div><p>•Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00</p></div><div><div><p>•Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction to ML - What, Why and Types..: 00:15:00</p></div><div><div><p>•Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00</p></div><div><div><p>•scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00</p></div><div><div><p>•scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00</p></div><div><div><p>•Good to know! How to save and load your trained Machine Learning Model!: 00:01:00</p></div><div><div><p>•scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00</p></div><div><div><p>•scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00</p></div><div><div><p>•scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00</p></div><div><div><p>•scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00</p></div><div><div><p>•scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00</p></div><div><div><p>•scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00</p></div><div><div><p>•scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00</p></div><div><div><p>•scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00</p></div><div><div><p>•scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00</p></div><div><div><p>•scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Theory: D-Tree &amp; Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00</p></div><div><div><p>•scikit-learn - Decision Tree and Random Forests - Hands-on  (Part 1): 00:19:00</p></div><div><div><p>•scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00</p></div><div><div><p>•scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00</p></div><div><div><p>•scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00</p></div><div><div><p>•scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00</p></div><div><div><p>•scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00</p></div><div><div><p>•scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Theory: K Means Clustering, Elbow method ..: 00:11:00</p></div><div><div><p>•scikit-learn - K Means Clustering - Hands-on: 00:23:00</p></div><div><div><p>•scikit-learn - K Means Clustering (Project Overview): 00:07:00</p></div><div><div><p>•scikit-learn - K Means Clustering (Project Solutions): 00:22:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Theory: Principal Component Analysis (PCA): 00:09:00</p></div><div><div><p>•scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00</p></div><div><div><p>•scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00</p></div><div><div><p>•scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Theory: Recommender Systems their Types and Importance: 00:06:00</p></div><div><div><p>•Python for Recommender Systems - Hands-on (Part 1): 00:18:00</p></div><div><div><p>•Python for Recommender Systems - - Hands-on (Part 2): 00:19:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Natural Language Processing (NLP) - (Theory Lecture): 00:13:00</p></div><div><div><p>•NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00</p></div><div><div><p>•NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00</p></div><div><div><p>•NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00</p></div><div><div><p>•NLTK - BoW, TF-IDF, Machine Learning, Training &amp; Evaluation, Naive Bayes : 00:13:00</p></div><div><div><p>•NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Resources- Python for Data Analysis: 00:00:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Apex Learning

Online Course Creation

Data Science

Data Analysis

Trainers Course

Data Analyst

Python for Data Analysis

<p>Become a worldwide competitor with skills that are validated for quality by QLS, the most respected high-quality course auditor in the UK.</p><p>Discover data science like an expert! With this premium course, acquire deep insight into the foundations of building and running Python scripts to more complicated capabilities including file operations, regular expressions, and working with binary data. This programming language may be used to store many kinds of data in a variable format. Enrol to obtain the industry-recognized certification required to start your own business or snag the job of your dreams!</p><p>This premium QLS endorsed Diploma in Python Programming course comes with intensive study modules, dedicated tutor assistance, customer support, flexible learning opportunity and a globally recognised certification all-together. Thus, successful completion of our Diploma in Python Programming course will give you limitless opportunities anywhere and everywhere, since the value of QLS endorsed courses are quite high, to say the least!!</p><p>Furthermore, neither we nor you will compromise on the exceptional quality of our first-rate education. With the wealth of knowledge from this outstanding Diploma in Python Programming course, you will be able to seize and seize success from a wide range of options. This course is really an incredible deal, especially considering the price! You should definitely not pass up this investment!</p><p>So, why delay any longer? Benefit your career progression by joining us today and distinguish yourself as, unquestionably, the most skilled one in your workplace!</p><p><strong>Why Learn with us: </strong></p><p>We, as one of the leading eLearning service providers across the globe, strive to provide all our learners with the best eLearning experience possible that can make a real difference in their career progression.</p><p><strong>Our Service for the </strong><strong>Diploma in Python Programming</strong><strong> Includes:</strong></p><ul><li>Intensive Study Notes</li><li>Tutor Support</li><li>Customer Support</li><li>Assignment Help</li><li>QLS Endorsed Certificate</li><li>24/7 Learning Portal Access</li><li>Widely Compatible Study Materials</li></ul><p><strong>Course Curriculum of </strong><strong>Diploma in Python Programming</strong></p><ul><li><strong>Unit 01:</strong> Introduction to Python Programming</li><li><strong>Unit 02:</strong> Getting Started with Python</li><li><strong>Unit 03:</strong> Conditional Branching with Python</li><li><strong>Unit 04:</strong> Importing external/internal library in python</li><li><strong>Unit 05:</strong> Project Rock Paper and Scissors</li><li><strong>Unit 06:</strong> Strings Operation in Python</li><li><strong>Unit 07:</strong> Date and time in Python</li><li><strong>Unit 08:</strong> File Handling, read and write using Python</li><li><strong>Unit 09:</strong> Data Storage Structures, Tuple, List and Dictionary</li><li><strong>Unit 10:</strong> Writing user functions in Python</li><li><strong>Unit 11:</strong> Sending mail</li><li><strong>Unit 12:</strong> Import Tricks in Python</li><li><strong>Unit 13:</strong> Import Operating System and Platform</li><li><strong>Unit 14:</strong> Exceptions handling in python</li><li><strong>Unit 15:</strong> Installing Packages and Scheduling In Python</li><li><strong>Unit 16:</strong> Data Base In Python using sqlite</li><li><strong>Unit 17:</strong> Running Program from Command Prompt and jupyter Notebook</li><li><strong>Unit 18:</strong> Conclusion</li></ul><p><strong>Assessment &amp; Certification</strong></p><p>Students need to finish and turn in a thorough assignment covering all topics in our curriculum. Our expert tutor will review the assignment to make sure it meets Quality Learning Systems (QLS) standards. Once the assessment is successful and passes a quality check, students will be awarded a certificate for completing the Diploma in Python Programming Course.</p><p><strong>Endorsed Certificate of Achievement from the Quality Licence Scheme</strong></p><p>After the course, participants will receive an endorsed certificate as proof of successful completion. The learner may request a certificate if they complete all course assessments.</p><p><strong>Endorsement:</strong></p><p>This certified course is approved by QLS as a well-qualified, non-regulated training program. A trainer will be available to address your inquiries, including guidance on your pathways to higher education.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        10 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>Our course is available to everyone. The Diploma in Python Programming Course is perfect for those who want to acquire detailed knowledge and effective skills to enter the relevant sector with promising potential.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>There are no specific requirements for enrolling in the Diploma in Python Programming course. Therefore, learners do not need previous qualifications to sign up for this course.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Diploma in Python Programming at QLS Level 5</h4>
        <p>
            Hard copy certificate -
            £75
        </p>

                        </div>

Kingston Open College

Certificate in Further Education & Training (Cert Ed)

Diploma for School Business Leaders (DSBM)

Professional Skills Course (PSC)

Diploma in Professional Studies (DPS)

ICDL (International Certification of Digital Literacy)

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support

Diploma in Python Programming - Level 5 (QLS Endorsed)

<strong>The "YAML Fundamentals" course helps beginners with the required skills to develop YAML documents. It will also help you gain skills to develop a properly structured YAML document in both block style and flow style. The "flow style" is also known as JSON style or compact style. If you are looking forward to adding YAML to your skillset, then this course is what you need. In today's market, every IT professional is expected to know YAML.</strong>
        <p>YAML is a data serialization language. The "YAML Fundamentals" course helps beginners with the required skills to develop YAML documents. Most common languages such as Go, Python, Java, C#, and so on provide support for YAML. You will see YAML being used in various ways in the industry for web service communication, configuration management, configuration files, data storage, and more.

In this course, you will learn about YAML, and compare YAML with HTML, JSON, and XML. You will look at YAML structure, data types in YAML, and complex mapping. After that, you will learn to document multiple YAML documents in a single file, handle multi-line strings, and look at the advanced features of YAML (tags, anchors, chomping, and so on.).

Following that, you will look at representing data using YAML, see different styles of documenting YAML, and tools and technologies leveraging YAML data serialization format. Next, you will be creating and validating YAML using VS Code Editor, using Python to read and extract data from YAML documents, and using Python to determine the data types in YAML documents. Finally, you will be reviewing examples of the Kubernetes YAML document and Ansible YAML playbook.

By the end of this course, you will learn the fundamentals of YAML and build skills to develop a properly structured YAML document from scratch.

All the resource files are uploaded on the GitHub repository at https://github.com/PacktPublishing/YAML-Fundamentals-for-DevOps-Cloud-and-IaC-Engineers</p>
        <h2>What You Will Learn</h2><p>Study about YAML and its structure<br>Explore YAML syntax along with simple and complex YAML documents<br>Understand block and flow style, and use tags to enforce data type<br>Understand and instill the ability to handle long and multi-line strings<br>Look at how to develop professional YAML documents using Anchors<br>Learn to develop YAML documents from scratch</p>
        <h2>Audience</h2><p>This course is designed for cloud engineers, DevOps engineers, software engineers, full-stack web developers, software architects, and software managers. This course will also benefit anyone with an interest in learning YAML.<br><br>Basic IT background is required to grasp the content quickly.</p>
        <h2>Approach</h2><p>This is a crisp, beginner-friendly, and complete course on getting started with YAML. This course is designed for absolute beginners and the content is animated to make it highly engaging. There is a standalone section on real-work examples that would help you write code from scratch. The course is a good mix of theoretical and practical content throughout.</p>
        <h2>Key Features</h2><p>Build skills to develop a properly structured YAML document from scratch * The course is designed for absolute beginners with a step-by-step methodology and animated content * Python codes are provided that can be used to review YAML documents</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/YAML-Fundamentals-for-DevOps-Cloud-and-IaC-Engineers</p>
        <h2>About the Author</h2><h3>Coding Gears | Train Your Brain</h3><p>GlobalETraining (brand name - CodingGears) offers self-paced technical courses and makes them easy to learn.

They have been in the IT training business for many years, offering training courses in Unix, Windows, C#, Java, Python programming, SQL server, manual testing, automation, and so on. Their instructors have 20+ years of experience in various technical areas such as software development, software testing, Windows systems, and network administration, Unix/Linux systems and network administration, virtualization technologies, storage, shell scripting, database management systems (MS SQL Server, MySQL, IBM DB2, Cassandra), containerization (Dockers), Mesos, Marathon, Jenkins, Jira, Elastic Cloud Storage (ECS), Gluster file system, CoreOS, Ansible, and other areas.

CodingGears/GlobalETraining has mentored thousands of students for over a decade and has extensive experience in delivering training-both in-class and online.</p>
        <h2>Course Outline</h2><h4>1. Introduction to the Course</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course Overview</p><p style='margin: 0'>This video provides an overview of the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Recommendations</p><p style='margin: 0'>This video provides a few recommendations before diving deep into this course.</p></td></tr></tbody></table><br><h4>2. YAML Fundamentals</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Overview</p><p style='margin: 0'>This video provides an overview about the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Why Learn YAML</p><p style='margin: 0'>This video explains why to learn YAML.</p></td></tr><tr><td style='padding: 15px;'><p>3. HTML Versus XML Versus JSON Version YAML</p><p style='margin: 0'>This video demonstrates the difference between HTML, XML, JSON, and YAML.</p></td></tr><tr><td style='padding: 15px;'><p>4. YAML Structure</p><p style='margin: 0'>This video explains the structure of YAML.</p></td></tr><tr><td style='padding: 15px;'><p>5. Datatypes - Scalars - Part 1</p><p style='margin: 0'>This is first of the two-part video that talks about scalars in datatypes.</p></td></tr><tr><td style='padding: 15px;'><p>6. Datatypes - Collections - Part 2</p><p style='margin: 0'>This is second of the two-part video that talks about collections in datatypes.</p></td></tr><tr><td style='padding: 15px;'><p>7. YAML Visualization</p><p style='margin: 0'>This video demonstrates the YAML visualization.</p></td></tr><tr><td style='padding: 15px;'><p>8. Tags</p><p style='margin: 0'>This video explains about the tags.</p></td></tr><tr><td style='padding: 15px;'><p>9. Anchors</p><p style='margin: 0'>This video explains about the Anchors.</p></td></tr><tr><td style='padding: 15px;'><p>10. Complex Mappings</p><p style='margin: 0'>This video explains about the complex mappings.</p></td></tr></tbody></table><br><h4>3. YAML - Hands-On Demos</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Overview</p><p style='margin: 0'>This video provides an overview about the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Demo: Visual Studio Code and YAML Extension</p><p style='margin: 0'>This demo video demonstrates Visual Studio code and YAML extension.</p></td></tr><tr><td style='padding: 15px;'><p>3. Demo: Python Code Review</p><p style='margin: 0'>This demo video demonstrates the review of the Python code. You will install the Python library before working on the code review.</p></td></tr><tr><td style='padding: 15px;'><p>4. Demo: Datatypes</p><p style='margin: 0'>This demo video demonstrates about the datatypes.</p></td></tr><tr><td style='padding: 15px;'><p>5. Demo: Single and Double Quotes</p><p style='margin: 0'>This demo video explains the single and double quotes.</p></td></tr><tr><td style='padding: 15px;'><p>6. Demo: Spaces</p><p style='margin: 0'>This demo video demonstrates about the spaces.</p></td></tr><tr><td style='padding: 15px;'><p>7. Demo: Indentation</p><p style='margin: 0'>This demo video demonstrates about the indentation.</p></td></tr><tr><td style='padding: 15px;'><p>8. Demo: Nulls and Boolean</p><p style='margin: 0'>This demo video demonstrates about the nulls and boolean.</p></td></tr><tr><td style='padding: 15px;'><p>9. Demo: Multiple YAML Documents in One File</p><p style='margin: 0'>This demo video demonstrates about the multiple YAML documents in one file.</p></td></tr><tr><td style='padding: 15px;'><p>10. Demo: Block and Flow Styles</p><p style='margin: 0'>This demo video demonstrates the block and flow styles.</p></td></tr><tr><td style='padding: 15px;'><p>11. Demo: Sets and Nested Maps</p><p style='margin: 0'>This demo video demonstrates about the sets and nested maps.</p></td></tr><tr><td style='padding: 15px;'><p>12. Demo: Multi-Line Strings</p><p style='margin: 0'>This demo video demonstrates about the multi-line strings.</p></td></tr><tr><td style='padding: 15px;'><p>13. Demo: Anchors</p><p style='margin: 0'>This demo video demonstrates about the Anchors.</p></td></tr><tr><td style='padding: 15px;'><p>14. Demo: Tags</p><p style='margin: 0'>This demo video demonstrates about the tags.</p></td></tr><tr><td style='padding: 15px;'><p>15. Demo: Complex Mapping</p><p style='margin: 0'>This demo video demonstrates about the complex mappings.</p></td></tr></tbody></table><br><h4>4. Real-Work Examples</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Overview</p><p style='margin: 0'>This video provides an overview about the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Demo: Writing YAML Documents from Scratch</p><p style='margin: 0'>This demo video helps in writing YAML documents from scratch.</p></td></tr><tr><td style='padding: 15px;'><p>3. Demo: Kubernetes and Ansible YAML Examples</p><p style='margin: 0'>This demo video demonstrates the Kubernetes and Ansible YAML examples.</p></td></tr><tr><td style='padding: 15px;'><p>4. Demo: Using Online Formatters</p><p style='margin: 0'>This demo video demonstrates how to format YAML documents using freely available online formatters.</p></td></tr></tbody></table>

Packt

DevOps

Cloud

Python

The "YAML Fundamentals" course helps beginners with the required skills to develop YAML documents. It will also help you gain skills to develop a properly structured YAML document in both block style and flow style. The "flow style" is also known as JSON style or compact style. If you are looking forward to adding YAML to your skillset, then this course is what you need. In today's market, every IT professional is expected to know YAML.

YAML Fundamentals for DevOps, Cloud and IaC Engineers

<p><strong>Learn Python and see the world of programming open up to you!</strong></p><p>Are you ready to take your Python programming skills to the next level? Our comprehensive Python Programming for Data Science Ultimate Bootcamp course covers all the essential topics you need to <strong>become a proficient Python programmer.</strong></p><p>With our course, you'll learn everything from Python programming basics to more advanced topics like <strong>conditional branching, file handling, data storage structures, and exception handling.</strong> You'll also discover how to import external and internal libraries, use string operations, handle date and time, and write user functions in Python.</p><p>This Python Programming for Data Science Ultimate Bootcamp course is perfect for anyone who wants to learn <strong>Python programming for personal or professional reasons</strong>. Whether you're a complete beginner or an experienced programmer, our expert instructors will guide you through the material step-by-step, providing practical exercises and real-world examples.</p><p>Enrol to our Python Programming for Data Science Ultimate Bootcamp course today and discover how to send emails, run programs from the command prompt or Jupyter Notebook, install packages, schedule tasks, and work with databases using SQLite. With our comprehensive curriculum, hands-on learning experience, and expert instructors, you'll quickly gain the skills and knowledge needed to become a proficient Python programmer.</p><p>This opportunity will <strong>enhance your programming skills</strong> and take your career to the next level. Enrol in our course now and start your journey towards mastering Python programming!</p><p><strong>Learning Outcomes:</strong></p><p><strong>Learners who complete this course will be able to:</strong></p><ul><li>Design IT solutions.</li><li>Employ data structures and algorithms to address IT issues.</li><li>Use Python libraries to create computer programmes.</li><li>Gain expertise in Python code debugging and troubleshooting.</li><li>Combine Python with other technologies relevant to IT.</li><li>Apply Python to create and develop interactive IT applications.</li><li>Have a basic understanding of Python's object-oriented programming language.</li><li>Identify the proper design patterns and use them in IT projects.</li></ul><p><strong>Key Benefits:</strong></p><ul><li>Learning materials of the Python course contain engaging voiceover and visual elements for your comfort.</li><li>Get 24/7 access to all content for a full year.</li><li>Each of our students gets full tutor support on weekdays (Monday to Friday)</li></ul><p><strong><em>FREE Courses:</em></strong></p><ul><li>Clinical Data Management with SAS Programming</li><li>Higher Order Functions in Python</li><li>U&amp;P AI - Natural Language Processing (NLP) with Python</li><li>Machine Learning for Apps</li><li>Start a Web Design Business Step by Step Masterclass</li></ul><p><strong>Curriculum Breakdown: Python Programming</strong></p><ul><li><strong>Unit 01: </strong>Introduction to Python Programming</li><li><strong>Unit 02:</strong> Getting Started with Python</li><li><strong>Unit 03: </strong>Conditional Branching with Python</li><li><strong>Unit 04:</strong> Importing external/internal library in python</li><li><strong>Unit 05:</strong> Project Rock Paper and Scissors</li><li><strong>Unit 06: </strong>Strings Operation in Python</li><li><strong>Unit 07:</strong> Date and time in Python</li><li><strong>Unit 08: </strong>File Handling, read and write using Python</li><li><strong>Unit 09:</strong> Data Storage Structures, Tuple, List and Dictionary</li><li><strong>Unit 10:</strong> Writing user functions in Python</li><li><strong>Unit 11:</strong> Sending mail</li><li><strong>Unit 12:</strong> Import Tricks in Python</li><li><strong>Unit 13:</strong> Import Operating System and Platform</li><li><strong>Unit 14:</strong> Exceptions handling in python</li><li><strong>Unit 15:</strong> Installing Packages and Scheduling In Python</li><li><strong>Unit 16:</strong> Data Base In Python using SQLite</li><li><strong>Unit 17:</strong> Running Program from Command Prompt and Jupyter Notebook</li><li><strong>Unit 18:</strong> Conclusion</li></ul><p><strong>Additionally, you will receive additional informative modules from bonus courses.</strong></p><p><strong>Course Assessment </strong></p><p>To simplify the procedure of evaluation and accreditation for learners, we provide an automated assessment system. Upon completing an online module of Python, you will immediately be given access to a specifically crafted MCQ test. The results will be evaluated instantly, and the score will be displayed for your perusal. For each test, the pass mark will be set to 60%.</p><p><strong>Meet the Accreditation</strong></p><p>CPD Quality Standards (CPD QS) accreditation assures the Python course training and learning activities are relevant, reliable, and upto date.</p><p><strong>Expert Support</strong></p><p>Dedicated tutor support and 24/7 customer support are available to all students with this premium quality Python course.</p><p><strong>Exam &amp; Retakes:</strong></p><p>It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable.</p><p><strong>Certification</strong></p><p>Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery).</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        10 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>Anyone looking to start a career in data science</li><li>Professionals seeking to upskill in Python programming for data analysis</li><li>Students and recent graduates interested in pursuing data science as a career</li><li>Business owners and entrepreneurs looking to gain insights from data analysis</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This Python course is open to all, with no formal entry requirements.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst (£31,000 - £50,000 per year)</li><li>Data Scientist (£40,000 - £70,000 per year)</li><li>Business Intelligence Analyst (£35,000 - £55,000 per year)</li><li>Machine Learning Engineer (£50,000 - £100,000 per year)</li><li>Data Engineer (£45,000 - £75,000 per year)</li><li>Data Consultant (£40,000 - £70,000 per year)</li><li>Big Data Engineer (£50,000 - £100,000 per year)</li><li>Data Architect (£70,000 - £120,000 per year)</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            £9
        </p>
            <div> <p><strong>CPD Accredited PDF Certificate.</strong><br />A PDF Certificate: £9</p> </div>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            £15
        </p>
            <div> <p><strong>CPD Accredited Hard Copy Certificate. </strong><br />A Hardcopy Certificate (within the UK): £15<br />A Hardcopy Certificate (international): £15 + £10 (postal charge) = £25</p> </div>

                        </div>

One Education

Python Programming for Data Science Ultimate Bootcamp Course

<p>Are you looking to enhance your Python from Scratch skills? If yes, then you have come to the right place. Our comprehensive courses on Python from Scratch will assist you in producing the best possible outcome by learning the Python from Scratch skills.</p><p><strong>Get 3 CPD Accredited Courses for only £12! Offer Valid for a Limited Time!! Hurry Up and Enrol Now!!!</strong></p><ul><li><strong></strong><strong> Course 01: </strong>Python from Scratch</li><li><strong></strong><strong> Course 02: </strong>Intermediate Python Coding</li><li><strong></strong><strong> Course 03: </strong>Javascript Programming for Beginners</li></ul><p><strong>So, enrol in our Python from Scratch bundle now!</strong></p><p><strong>Other Benefits</strong></p><ul><li>Lifetime Access to All Learning Resources</li><li>An Interactive, Online Course</li><li>A Product Created By Experts In The Field</li><li>Self-Paced Instruction And Laptop, Tablet, And Smartphone Compatibility</li><li>24/7 Learning Support</li><li>Free Certificate After Completion</li></ul><p>Learn at your own pace from the comfort of your home, as the rich learning materials of this course are accessible from any place at any time. The curriculums are divided into tiny bite-sized modules by industry specialists. And you will get answers to all your queries from our experts.</p><p>So, enrol and excel in your career with Compliance Central.</p><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Anyone from any background can enrol in this Python from Scratch bundle.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To enrol in this Python from Scratch, all you need is a basic understanding of the English Language and an internet connection.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>After completing this course, you can explore trendy and in-demand jobs related to Python from Scratch.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p><strong>CPD Accredited Hard Copy Certificate</strong></p><p><strong>Delivery Charge:</strong></p><p>Inside the UK: £3.99 each</p><p>Outside of the UK: £9.99 each</p></div>
        <h4>CPD Accredited PDF Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><p><strong>3 CPD Accredited PDF Certificate</strong></p></div>

                        </div>

Compliance Central

Python from Scratch and Javascript Programming

<strong>This course on MongoDB is for absolute beginners and provides an interactive learning experience that reflects the most in-demand skills. The content will help you understand the concepts and methodology with regards to MongoDB in an effortless way. The strong basic understanding you gain initially will help you move toward learning more advanced concepts.</strong>
        <p>MongoDB, a fast and scalable NoSQL database, is extremely popular right now. This object-oriented database is simple and dynamic.

In this course, you start by becoming proficient in the elementary concepts of MongoDB, including installing and setting up MongoDB Atlas, and understanding the database structure, collection structure, document structure, and basic Mongo commands.

Next, you'll explore the Basic, Create, Read, Update, and Delete operations in MongoDB. You'll then explore in detail the MongoDB query operators and project operators. Following this, you'll learn about MongoDB update operators. In the concluding modules, you'll explore MongoDB with Node and Python.

In the final module, you'll sharpen your practical knowledge of the theoretical concepts you learned in this course by working on two mini-projects. In the first project, you'll work on MongoDB with Django, in which you'll develop a CRUD-based application using Django and MongoDB. In the second project, you'll implement an ETL pipeline using PySpark to dump the data in MongoDB.

By the end of this course, you will be able to implement any project from scratch that requires MongoDB knowledge.

The complete code bundle for this course is available at https://github.com/PacktPublishing/MongoDB-Mastering-MongoDB-for-Beginners-Theory-and-Projects-</p>
        <h2>What You Will Learn</h2><p>Introduction to MongoDB and understand its importance<br>Understand MongoDB with Node, Python, and Django<br>Perform CRUD operations with Node, Python, Django in MongoDB Atlas<br>Understand different MongoDB CRUD operations<br>Build APIs for CRUD operations in MongoDB through Django<br>Understand MongoDB with PySpark</p>
        <h2>Audience</h2><p>This course is designed for absolute beginners. As a newbie in this field, you will spend sufficient time - in gaining a thorough understanding of the fundamental concepts. You also need a good understanding of SQL.<br><br>If you want to become a data scientist, database administrator, database engineer, or data engineer, then this course is for you.</p>
        <h2>Approach</h2><p>The course is designed for absolute beginners; hence, it is easy to understand, includes practical with live coding, and is full of challenging quizzes with solutions. You will then make steady progress with a lot of practical implementations where each step will be dealt with in detail.</p>
        <h2>Key Features</h2><p>Relate the concepts and practical applications of MongoDB with real-world problems * Implement any project from scratch that requires MongoDB knowledge * Know the theoretical and practical aspects of MongoDB</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/MongoDB-Mastering-MongoDB-for-Beginners-Theory-and-Projects-</p>
        <h2>About the Author</h2><h3>AI Sciences</h3><p>AI Sciences are a group of experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.

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

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

Their courses have successfully helped more than 100,000 students master AI and data science.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><br><h4>2. Overview</h4><p></p><br><h4>3. Basic Mongo Operations</h4><p></p><br><h4>4. Basic Create Operation</h4><p></p><br><h4>5. Basic Update Operation</h4><p></p><br><h4>6. Basic Read Operation</h4><p></p><br><h4>7. Basic Delete Operation</h4><p></p><br><h4>8. Query and projection operators</h4><p></p><br><h4>9. Update Operators</h4><p></p><br><h4>10. Mongo with Node</h4><p></p><br><h4>11. Mongo with Python</h4><p></p><br><h4>12. Django with Mongo</h4><p></p><br><h4>13. Spark With Mongo</h4><p></p>

Programming

MongoDB

This course on MongoDB is for absolute beginners and provides an interactive learning experience that reflects the most in-demand skills. The content will help you understand the concepts and methodology with regards to MongoDB in an effortless way. The strong basic understanding you gain initially will help you move toward learning more advanced concepts.

MongoDB-Mastering MongoDB for Beginners (Theory and Projects)

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

Nexus Human

Microsoft AZ-900

Microsoft AZ-104

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

AWS Certified Solutions Architect

AZ-204T00 Developing Solutions for Microsoft Azure

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

Azure Machine Learning

Microsoft AI-900

Azure Cognitive Services

AI-102T00 Designing and Implementing an Azure AI Solution

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 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
This Python Certification Course is suitable for:
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 Requirements 
No experience required. Just enrol & start learning python.
 Career path 
Upon completion of our Program, the potential career paths include:
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 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Academy for Health and Fitness

Career Development

IT Certifications

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


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

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

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

Python for Beginners: Learn Python Programming (Python 3)

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

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

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

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

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

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

                        </div>

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

Business Analytics & Intelligence

Data Engineering

Big Data Analytics

Data Skills

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

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

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

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

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

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

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

                        </div>

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


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


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


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


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


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


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


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


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

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

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

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

Python Programming

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

Google Data Studio

GDPR

Data Mining

Tableau

Business Intelligence (BI)

ChatGPT

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

Data Analyst (Data Analytics) Diploma - CPD Certified

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

The Ultimate Guide to Python Programming with Python 3.10

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

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

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

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

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

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

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

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