<p><strong>Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £160 as a Gift - Enrol Now</strong></p> <p>Whether you work in machine learning or finance or are pursuing a career in web development or data science, Python is one of the most important skills you can learn.</p> <p>Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization.</p> <p>The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks. Learn how to build a promising and lucrative career by training to become a Computer Programmer without any previous skill needed. By utilising the popular Python programming platform and language, you will swiftly learn how to understand the principles of writing programs and using variables in their construction. You will also be taught how to set up conditional and repeated executions in a routine, alongside the ability to recode and reuse other programs for templates or loops. Code yourself a bright future now.</p> <p>With a single payment you will gain access to <strong>Python Training</strong> including <strong>10</strong> Career development courses, <strong>original hardcopy certificate, transcript</strong> and a <strong>student ID card</strong> which will allow you to get discounts on things like music, food, travel and clothes etc.</p> <p><strong>What other courses are included with this Python?</strong></p> <ol> <li>Level 2 Microsoft Office Essentials</li><li>Microsoft Teams</li><li>Leadership &amp; Management Diploma</li><li>Working from Home Essentials</li><li>Mental Health and Working from Home</li><li>Online Meeting Management</li><li>Effective Communication Skills</li><li>Time Management</li><li>Report Writing</li><li>Emotional Intelligence and Human Behaviour</li></ol> <p><strong>Benefits you'll get from choosing Apex Learning for this Python Training:</strong></p> <ul> <li>Pay once and get lifetime access <strong>to 11 CPD courses </strong>including this Python Training Course</li><li>Free e-Learning App for engaging reading materials &amp; helpful assistance</li><li>Certificates, student ID for the course included in a one-time fee</li><li>Free up your time - don't waste time and money travelling for classes</li><li>Accessible, informative modules of Python Training designed by expert instructors</li><li>Learn about Python Training at your ease - anytime, from anywhere</li><li>Study the Python Training from your computer, tablet or mobile device</li></ul><p>The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Python Training expertise and essential knowledge, which will assist you in reaching your goal. Moreover, you can learn from any place in your own time without travelling for classes.</p> <p><strong>Curriculum:</strong></p> <p><strong>Course 01: Python Programming for Everybody</strong></p> <p><strong>Module 01</strong></p> <ul> <li>A Installing Python</li><li>Documentation</li><li>Command Line</li><li>Variables</li><li>Simple Python Syntax</li><li>Keywords</li><li>Import Module</li></ul> <p><strong>Module 02</strong></p> <ul> <li>Additional Topics</li><li>If Elif Else</li><li>Iterable</li><li>For</li><li>Loops</li><li>Execute</li><li>Exceptions</li></ul> <p><strong>Module 03</strong></p> <ul> <li>Data Types</li><li>Number Types</li><li>More Number Types</li><li>Strings</li><li>More Strings</li><li>Files</li><li>Lists</li><li>Dictionaries</li><li>Tuples</li><li>Sets</li></ul> <p><strong>Module 04</strong></p> <ul> <li>Comprehensions</li><li>Definitions</li><li>Functions</li><li>Default Arguments</li><li>Doc Strings</li><li>Variadic Functions</li><li>Factorial</li></ul> <p><strong>Module 05</strong></p> <ul> <li>Function Objects</li><li>Lambda</li><li>Generators</li><li>Closures</li><li>Classes</li><li>Object Initialization</li><li>Class Static Members</li><li>Classic Inheritance</li><li>Data Hiding</li></ul> <p><strong>How will I get my Certificate?</strong></p> <p>After successfully completing this Training course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p> <ul> <li><strong>PDF Certificate: Free (Previously it was £10 * 11 = £110)</strong></li></ul> <ul> <li><strong>Hard Copy Certificate: Free (For The Title Course)</strong></li></ul> <p>If you want to get hardcopy certificates for other courses, generally you have to pay £20 for each. But this Fall, Apex Learning is offering a<strong> Flat 50% discount </strong>on hard copy certificates, and you can get each for just <strong>£10</strong>!</p> <p><strong>P.S. The delivery charge inside the U.K. is £3.99 and the international students have to pay £9.99. </strong></p><h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="requirements">
                             <p>This course has been designed to be fully compatible with tablets and smartphones.</p> 
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                             <p>Having this expertise will increase the value of your CV and open you up to multiple job sectors.</p> 
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

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

                        </div>

Apex Learning

Python Training - CPD Accredited

General Admission

<p>Introducing the Sales and Marketing with ChatGPT bundle, a powerhouse of knowledge and tools designed to propel your business towards unprecedented growth and success. This comprehensive package offers a range of valuable resources to enhance your marketing efforts. Harness the cutting-edge capabilities of ChatGPT, an AI-powered tool that revolutionises productivity and customer engagement. With automated tasks, content generation, and seamless customer interactions, ChatGPT is a game-changer for your marketing strategy.</p><p>Elevate your business with the Sales and Marketing with ChatGPT bundle. Refine your persuasive techniques through Sales Training, master SEO for top rankings, and unleash compelling Copywriting Secrets. Craft impactful email campaigns with the Email Marketing Masterclass. Acquire essential knowledge and tools for success in sales and marketing. Invest in this comprehensive bundle to supercharge your brand and embrace new heights of achievement.</p><p><strong>The CPD Accredited eight courses are: </strong></p><ul><li><strong>Course 01: </strong>ChatGPT for Marketing and Productivity with AI Tools</li><li><strong>Course 02: </strong>ChatGPT Complete Guide with Expertise</li><li><strong>Course 03: </strong>Project on Deep Learning - Artificial Neural Network</li><li><strong>Course 04: </strong>Learn AI with Python</li><li><strong>Course 05: </strong>Sales Training</li><li><strong>Course 06: </strong>SEO - Search Engine Optimisation</li><li><strong>Course 07: </strong>Copywriting Secrets</li><li><strong>Course 08: </strong>Email Marketing Masterclass</li></ul><p><strong>Learning Outcomes:</strong></p><p>By completing this bundle, you will:</p><ul><li>Refine persuasive techniques for remarkable sales results.</li><li>Master SEO strategies for top search engine rankings.</li><li>Craft compelling copy that drives conversions.</li><li>Harness AI tools to automate tasks and enhance marketing productivity.</li><li>Create impactful email campaigns that resonate with subscribers.</li><li>Supercharge your business with advanced marketing skills.</li></ul><p>The Sales and Marketing with ChatGPT bundle is the ultimate package designed to empower you with a comprehensive skill set and essential tools to excel in the dynamic world of sales and marketing.</p><p>Let's dive into what this bundle includes:</p><p><strong>ChatGPT for Marketing and Productivity with AI Tools:</strong> Revolutionise your marketing and productivity with ChatGPT. Harnessing the power of artificial intelligence, it automates tasks, generates compelling content, and enhances customer engagement. ChatGPT streamlines processes and delivers exceptional customer experiences from chatbots to content creation.</p><p><strong>ChatGPT Complete Guide with Expertise: </strong>Discover how to create captivating chatbots, generate content, and engage customers, propelling your marketing efforts to the next level.</p><p><strong>Project on Deep Learning - Artificial Neural Network: </strong>Apply your AI knowledge practically with a real-world project focused on artificial neural networks. Gain hands-on experience in deep learning, allowing you to tackle complex marketing challenges with data-driven solutions.</p><p><strong>Learn AI with Python: </strong>Acquire practical AI skills using Python, including data analysis, machine learning, and predictive analytics. Understand how AI can be integrated into marketing strategies for data-driven decision-making.</p><p><strong>Sales Training</strong>: Elevate your sales game with expert Sales Training. Refine your persuasive techniques, master communication and negotiation skills, and build strong customer relationships. Gain confidence, close deals, and achieve remarkable sales results.</p><p><strong>SEO - Search Engine Optimisation: </strong>Achieve top search engine rankings and enhance your online visibility with SEO. Learn the techniques and strategies to optimise your website, increase organic traffic, and effectively reach your target audience. Master the art of SEO, from keyword research to on-page and off-page optimisation, and dominate search engine rankings.</p><p><strong>Copywriting Secrets:</strong> Master the art of persuasive copywriting and captivate your audience with compelling messages that drive conversions. Unlock the power of words to elevate your marketing campaigns and achieve remarkable results.</p><p><strong>Email Marketing Masterclass:</strong> Master the art of highly effective email marketing campaigns that resonate with subscribers. Boost open rates, click-through rates, and drive conversions with expert insights on engaging subject lines, personalisation, and automation techniques.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        50 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 bundle is for:</p><ul><li>Sales professionals</li><li>Marketing professionals</li><li>Copywriters</li><li>Business owners and entrepreneurs</li><li>Marketing managers</li><li>Individuals are seeking advanced sales and marketing skills.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>Without any formal requirements, you can delightfully enrol in this bundle. Study for the bundle using any internet-connected device, such as a computer, tablet, or mobile device.<br /><br /></p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This bundle opens career paths in:</p><ul><li>Sales and Business Development</li><li>Digital Marketing</li><li>Marketing Management</li><li>Entrepreneurship</li><li>AI and Marketing Technology</li><li>AI Product Manager</li><li>AI Content Strategist</li><li>Virtual Assistant Developer</li><li>Customer Support Automation Specialist</li></ul><p><strong>Please note</strong> that salaries can range from £25,000 to £70,000 annually.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Quality Standard Certificate</h4>
        <p>
            Digital certificate -
            £4.99
        </p>
        <h4>Hardcopy Certificate (FREE UK Delivery)</h4>
        <p>
            Hard copy certificate -
            £9.99
        </p>
            <div><p>Hardcopy Transcript: £9.99</p></div>

                        </div>

NextGen Learning

Online Course Marketing

Digital Marketing

Video Marketing

Email Marketing

Google Digital Marketing

Salesforce Certified Marketing Cloud Email Specialist

Sales and Marketing with ChatGPT (SEO, Copywriting, Email Marketing)

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Get ready for an exceptional online learning experience with the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Security Specialist</strong> bundle! This carefully curated collection of<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"> 30 premium courses</strong> is designed to cater to a variety of interests and disciplines. Dive into a sea of knowledge and skills, tailoring your learning journey to suit your unique aspirations.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The IT Security Specialist is a dynamic package, blending the expertise of industry professionals with the flexibility of digital learning. It offers the perfect balance of foundational understanding and advanced insights. Whether you&#39;re looking to break into a new field or deepen your existing knowledge, the<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"> IT Security Specialist </strong>package has something for everyone.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">As part of the IT Security Specialist package, you will receive complimentary PDF certificates for all courses in this bundle at no extra cost. Equip yourself with the IT Security Specialist bundle to confidently navigate your career path or personal development journey. Enrol today and start your career growth!</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This Bundle Comprises the Following </strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Security Specialist</strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"> CPD Accredited Courses:</strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 01</strong>: IT Administration and Networking</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 02</strong>: Start an IT Asset Department</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 03</strong>: IT Helpdesk Administrator Training</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 04</strong>: CompTIA IT Fundamentals ITF+ (FCO-U61)</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 05</strong>: CompTIA Network+ Certification (N10-007)</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 06</strong>: Information Management</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 07</strong>: IT For Recruiters</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 08</strong>: The Complete Front-End Web Development Course!</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 09</strong>: Data Science &amp; Machine Learning with R from A-Z</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 10</strong>: SQL for Data Science, Data Analytics and Data Visualization</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 11</strong>: Masterclass Bootstrap 5 Course - Responsive Web Design</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 12</strong>: Web Application Penetration Testing Course</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 13</strong>: Cloud Computing / CompTIA Cloud+ (CV0-002)</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 14</strong>: CompTIA PenTest+ (Ethical Hacking)</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 15</strong>: Computer Networks Security from Scratch to Advanced</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 16</strong>: Learn Ethical Hacking From A-Z: Beginner To Expert</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 17</strong>: SQL Database Basics for Everyone</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 18</strong>: GDPR</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 19</strong>: Cyber Security Incident Handling and Incident Response</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 20</strong>: Digital Product Management</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 21</strong>: Career Development Plan Fundamentals</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 22</strong>: CV Writing and Job Searching</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 23</strong>: Learn to Level Up Your Leadership</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 24</strong>: Networking Skills for Personal Success</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 25</strong>: Ace Your Presentations: Public Speaking Masterclass</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 26</strong>: Learn to Make a Fresh Start in Your Life</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 27</strong>: Motivation - Motivating Yourself &amp; Others</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 28</strong>: Excel: Top 50 Microsoft Excel Formulas in 50 Minutes!</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 29</strong>: Decision Making and Critical Thinking</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 30</strong>: Time Management Training - Online Course</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">What will make you stand out?</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Upon completion of this online IT Security Specialist bundle, you will gain the following:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">CPD QS Accredited Proficiency with this <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Security Specialist</strong> bundle</li><li fr-original-style="" style="box-sizing: border-box;">After successfully completing the IT Security Specialist bundle, you will receive a FREE CPD PDF Certificates as evidence of your newly acquired abilities.</li><li fr-original-style="" style="box-sizing: border-box;">Lifetime access to the whole collection of learning materials of this <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Security Specialist</strong> bundle</li><li fr-original-style="" style="box-sizing: border-box;">The online test with immediate results</li><li fr-original-style="" style="box-sizing: border-box;">You can study and complete the IT Security Specialist bundle at your own pace.</li><li fr-original-style="" style="box-sizing: border-box;">Study for the IT Security Specialist bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Each course in this IT Security Specialist bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Embrace the future of learning with the IT Security Specialist, a rich anthology of 30 diverse courses. Each course in the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Security Specialist</strong> bundle is handpicked by our experts to ensure a wide spectrum of learning opportunities. ThisIT Security Specialist bundle will take you on a unique and enriching educational journey.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The bundle encapsulates our mission to provide quality, accessible education for all. Whether you are just starting your career, looking to switch industries, or hoping to enhance your professional skill set, the IT Security Specialist bundle offers you the flexibility and convenience to learn at your own pace. Make the IT Security Specialist package your trusted companion in your lifelong learning journey.</p><h2 fr-original-style="" style="box-sizing: border-box;">
        
        <div fr-original-style="" style="box-sizing: border-box;">CPD</div>
    </h2>

                        <div id="cpd" fr-original-style="" style="box-sizing: border-box;">
                            <div fr-original-style="" style="box-sizing: border-box;">
                                <div fr-original-style="" style="box-sizing: border-box;">
                                    <div fr-original-style="" style="box-sizing: border-box;">
                                        300 CPD hours / points
                                    </div>
                                        <div fr-original-style="" style="box-sizing: border-box;">
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2 fr-original-style="" style="box-sizing: border-box;">
        
        <div fr-original-style="" style="box-sizing: border-box;">Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for" fr-original-style="" style="box-sizing: border-box;">
                            <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Security Specialist</strong> bundle is perfect for:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Lifelong learners looking to expand their knowledge and skills.</li><li fr-original-style="" style="box-sizing: border-box;">Professionals seeking to enhance their career with CPD certification.</li><li fr-original-style="" style="box-sizing: border-box;">Individuals wanting to explore new fields and disciplines.</li><li fr-original-style="" style="box-sizing: border-box;">Anyone who values flexible, self-paced learning from the comfort of home.</li></ul>
                        </div><h2 fr-original-style="" style="box-sizing: border-box;">
        
        <div fr-original-style="" style="box-sizing: border-box;">Requirements</div>
    </h2>

                        <div id="requirements" fr-original-style="" style="box-sizing: border-box;">
                            <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">You are cordially invited to enroll in this <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Security Specialist </strong>bundle; please note that there are no formal prerequisites or qualifications required. We&#39;ve designed this curriculum to be accessible to all, irrespective of prior experience or educational background.</p>
                        </div><h2 fr-original-style="" style="box-sizing: border-box;">
        
        <div fr-original-style="" style="box-sizing: border-box;">Career path</div>
    </h2>

                        <div id="career_path" fr-original-style="" style="box-sizing: border-box;">
                            <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Unleash your potential with the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Security Specialist </strong>bundle. Acquire versatile skills across multiple fields, foster problem-solving abilities, and stay ahead of industry trends. Ideal for those seeking career advancement, a new professional path, or personal growth. Embrace the journey with the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Security Specialist</strong>bundle package.</p>
                        </div><h2 fr-original-style="" style="box-sizing: border-box;">
        
        <div fr-original-style="" style="box-sizing: border-box;">Certificates</div>
    </h2>

                        <div id="optional_extras" fr-original-style="" style="box-sizing: border-box;">
                                    <h4 fr-original-style="" style="box-sizing: border-box;">CPD Quality Standard Certificate</h4>
        <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">
            Digital certificate -
            Included
        </p>
            <div fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">30 CPD Quality Standard Certificates - Free</p></div>

                        </div>

Certified in Cybersecurity (CC)

IT Certifications

Certificate in Information Security Management Principles (CISMP)

Cyber Security

Professional Skills Course (PSC)

CompTIA Security+

IT Security Specialist Bundle (30 in 1)

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				<div>
					<div><p>Have you ever envisioned molding digital worlds with just lines of code, but felt lost about where to begin? Enter Python For Beginners Part 1 Course, your gateway to the digital realm. Every epic saga has its genesis, and in the world of programming, this course is yours. With Module 01, you'll be introduced to the very essence of Python, laying a robust foundation for what's to come.</p><p>Python is one of the most in-demand programming languages in the world today, and for good reason. It's easy to learn, powerful, and versatile. Whether you want to build websites, create data science applications, or automate tasks, Python can help you do it.</p><p>By Module 02, you won't just be learning about Python, you'll be actively crafting with it, initiating your first Python scripts. It's one thing to know a language, but entirely another to converse fluently. Modules 03 and 04 are all about that fluency. Here, you'll decipher the language of Data Types and Operators, and understand the art of organizing with Data Structures. These modules ensure you're not just coding, but conversing, making your digital canvas come alive.</p><p>However, what's an artist without control over their palette? Module 05, focusing on Control Flow, gives you the reins to guide your program's direction. Just as a river's flow is directed by its banks, with control flow, you decide where your program's logic flows. By the end, you won't just be a passive observer but an active creator, shaping digital landscapes and setting forth on an unforgettable coding adventure.</p><p>Enrol in the Python For Beginners Part 1 Course and boost up your skills!</p></div>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</div></section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2><b> Learning outcome</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Gain proficiency in Python programming language.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Master basic to advanced Python concepts and syntax.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Develop problem-solving skills using Python.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Understand Python data types and how to manipulate them.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Learn to create reusable codes with functions and classes.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Why should I take this course?</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Learn a versatile and widely used language for effective coding.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Enhance your problem-solving and logical thinking skills.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Expand your career opportunities in tech, data science, and AI.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Develop a skill set that allows you to automate tasks and analyze data.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Increase your confidence in coding and algorithm development.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Career Path</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Python Developer</span>
									</li>
								<li>
											<span>
													</span>
										<span>Data Scientist</span>
									</li>
								<li>
											<span>
													</span>
										<span>Machine Learning Engineer</span>
									</li>
								<li>
											<span>
													</span>
										<span>Software Engineer (specialising in Python)</span>
									</li>
								<li>
											<span>
													</span>
										<span>DevOps Engineer (using Python scripting)</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Requirements</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>A computer with internet access.</span>
									</li>
								<li>
											<span>
													</span>
										<span>No prior knowledge of Python or programming is required.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Eagerness to learn and explore Python programming.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section><div>
                            <div>
                                <h2>Course Curriculum</h2>
                            </div>
                            			<div>
				

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4"><strong>Module 01: Introduction to the Python for Beginners Course</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Introduction to the Python for Beginners Course</td><td><span>🕐 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 02: Getting Started with Python</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Getting Started with Python</td><td><span>🕐 00:53:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 03: Data Types and Operators</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Data Types and Operators</td><td><span>🕐 01:54:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 04: Data Structures</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Data Structures</td><td><span>🕐 01:59:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Module 05: Control Flow</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Control Flow</td><td><span>🕐 01:14:00</span></td>
				</tr>
				</tbody></table></div>

			</div>
		                        </div>

Skill Up

Dip yourself in the dynamic world of Python programming with our Python for Beginners Online Course. Master Python's key concepts, its syntax, data types, and much more.

Python For Beginners Part 1

<strong>Welcome to this beginner's level course on Microsoft SQL Servers. Understand the concepts of SQL and learn to create a new database and table to perform various operations on it, with live running queries as examples. Work on hands-on exercises and understand database concepts in a real-world scenario.</strong>
        <p>SQL Server is a relational database management system (RDBMS) developed by Microsoft. SQL Server also allows user-defined composite types (UDTs) to be used. The SQL Server services operate within SQL server instances, allowing people to do machine learning and data analytics.

In this course, you will understand the difference between SQL and NoSQL. You will query SQL and learn about built-in SQL functions. You will create and modify databases and tables using the CREATE DATABASE and CREATE TABLE statements. You will create, select, and modify records and create constraints in SQL. You will advance to create indexes, drop tables, and databases in SQL. You will learn about operators (AND, OR, NOT, LIKE, BETWEEN, IN, LIKE), functions, statements, and constraints in SQL. You will look at stored procedures and aliases, and learn to back up databases in SQL. You will use the WHERE clause to query and learn about the SELECT and DISTINCT functions. You will arrange data using the ORDER BY keyword and ASC and DESC keywords.

After completing the course, you will thoroughly understand SQL's features and components. You will create complex databases and maintain existing databases. Finally, you will acquire complex SQL query capabilities and write complex queries.

All resources are available at: https://github.com/PacktPublishing/SQL-Server-Course-for-Beginners-with-100-examples</p>
        <h2>What You Will Learn</h2><p>Create databases and tables from the start<br>Learn to handle MySQL queries<br>Learn to query SQL to manipulate records in tables<br>Explore functions, statements, and constraints in SQL<br>Create and maintain complex databases and table structures<br>Write complex query statements for maximum data optimization</p>
        <h2>Audience</h2><p>This course delivers a substantial learning experience for database creators, web developers, application developers, and programmers who must operate with SQL and database structures. Database analysts and administrators who are looking to advance/refresh their knowledge skillsets can benefit from this course. The course has no additional prerequisites besides basic computer use knowledge.</p>
        <h2>Approach</h2><p>Well-structured and high-quality video lectures provide step-by-step explanations in a tutorial-like environment, making it easily understandable for beginners about a new database, tables, and their features with live running queries as examples. The course also provides carefully created quizzes to refresh and hone your SQL skillsets.</p>
        <h2>Key Features</h2><p>Understand the SQL query process and the role of databases in real-world applications * Create new databases and tables and perform operations to manipulate records using SQL queries * Master SQL querying and write complex query statements to enhance your understanding of MySQL</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/SQL-Server-Course-for-Beginners-with-100-examples</p>
        <h2>About the Author</h2><h3>Amit Diwan</h3><p>Studyopedia was founded by Amit Diwan in 2018 after working for Tutorialspoint , IIT, IASRI, Sitepoint, DU, and C# Corner. Studyopedia sells courses on Udemy, Tutorialspoint, Geeksforgeeks, and Skillshare, providing video courses to master various technologies and programming languages, databases, frameworks, Python, data science, machine learning, Java, Android, C/C++, HTML5, Bootstrap, JavaScript, jQuery, PHP, CSS, WordPress, Drupal, Joomla, Magento, osCommerce, OpenCart, PrestaShop, and other disciplines. Studyopedia delivers high-quality video courses to millions of students and professionals enrolled through their website on multiple programming languages and technologies.</p>
        <h2>Course Outline</h2><h4>1. SQL Introduction</h4><p>This section focuses on a cursory introduction to SQL, the benefits of using SQL, and also the features of SQL.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Learn what SQL is and how it is based on RDBMS. We will discuss the features and Microsoft SQL Server and SQL Server Management Studio.</p></td></tr><tr><td style='padding: 15px;'><p>2. SQL Versus NoSQL</p><p style='margin: 0'>Learn the difference between SQL and NoSQL. We have considered the example of MySQL (SQL-based) and MongoDB (NoSQL-based) to understand the concept.</p></td></tr></tbody></table><br><h4>2. SQL Installation and Setup</h4><p>This section focuses on the installation and setup process of SQL server over Windows 10 and 11 and also to fix installation errors.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Install SQL Server on Windows 10</p><p style='margin: 0'>Learn how to download and install Microsoft SQL Server on Windows 10. We will also install SQL Server Management Studio (SSMS).</p></td></tr><tr><td style='padding: 15px;'><p>2. Install SQL Server on Windows 11</p><p style='margin: 0'>Learn how to download and install Microsoft SQL Server on Windows 11. We will also install SQL Server Management Studio (SSMS).</p></td></tr><tr><td style='padding: 15px;'><p>3. Fix SQL Server Installation Error</p><p style='margin: 0'>While installing SQL Server, you may get the following error: Learn how to fix the following error while installing Microsoft SQL Server 2019: A required file could not be downloaded. This could mean the version of the installer is no longer supported.</p></td></tr></tbody></table><br><h4>3. Create and Insert</h4><p>This section focuses over creating a database and table and adding records or populating the table and database.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Create a Database</p><p style='margin: 0'>Learn how to create a new database in SQL Server. The CREATE DATABASE statement is used to create a new SQL server database.</p></td></tr><tr><td style='padding: 15px;'><p>2. Create a Table</p><p style='margin: 0'>Learn how to create a new table with SQL Server. The CREATE TABLE statement is used to create a new table in SQL Server.</p></td></tr><tr><td style='padding: 15px;'><p>3. Insert Records</p><p style='margin: 0'>Use the INSERT INTO Statement in SQL to learn how to insert records in a table.</p></td></tr></tbody></table><br><h4>4. Select Records in SQL</h4><p>This section delves over records in SQL, how to select them, how to select distinct elements, and use the where clause to segregate records.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. SELECT Statement in SQL</p><p style='margin: 0'>Learn how to select records in SQL using the SELECT statement. We will also see how to choose multiple columns in a single query.</p></td></tr><tr><td style='padding: 15px;'><p>2. SELECT DISTINCT Statement in SQL</p><p style='margin: 0'>Learn how to select and return only distinct values from a table using the SQL SELECT DISTINCT statement.</p></td></tr><tr><td style='padding: 15px;'><p>3. WHERE Clause in SQL</p><p style='margin: 0'>Learn how to work with the WHERE clause in SQL. WHERE clause filters records based on condition(s).</p></td></tr></tbody></table><br><h4>5. Order Records in SQL</h4><p>This section focuses on the order records function of SQL using the ORDER BY keyword.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. ORDER BY Keyword in SQL</p><p style='margin: 0'>Learn how to order records in SQL using the ORDER BY keyword. The default sorts in ascending order. We will see examples of both ASC and DESC keywords as well.</p></td></tr></tbody></table><br><h4>6. Operators in SQL</h4><p>This section focuses on the arithmetic and logical operators used in SQL, including AND, OR, NOT, IN, BETWEEN, and LIKE.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. AND Operator</p><p style='margin: 0'>Learn how to work with the AND operator in SQL to display records only if both conditions are TRUE. These two conditions should be separated by the AND operator.</p></td></tr><tr><td style='padding: 15px;'><p>2. OR Operator</p><p style='margin: 0'>Learn how to work with the OR operator in SQL to display records only if one condition is TRUE. The OR operator should separate these two conditions.</p></td></tr><tr><td style='padding: 15px;'><p>3. NOT Operator</p><p style='margin: 0'>Learn how to work with the NOT operator in SQL to display records only if the condition isn't met, that is, FALSE.</p></td></tr><tr><td style='padding: 15px;'><p>4. IN Operator</p><p style='margin: 0'>Learn how to implement the IN operator in SQL. We will check whether a specific value matches.</p></td></tr><tr><td style='padding: 15px;'><p>5. BETWEEN Operator</p><p style='margin: 0'>Learn how to implement the BETWEEN operator in SQL. We will find values in a range.</p></td></tr><tr><td style='padding: 15px;'><p>6. LIKE Operator</p><p style='margin: 0'>Learn how to implement the LIKE operator in SQL. We will find values based on a specific pattern using percentages and underscore.</p></td></tr></tbody></table><br><h4>7. Built-In Functions in SQL</h4><p>This section focuses on the built-in functions in SQL and helps us understand maximum, minimum, sum, average, and count functions in detail.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. MAX() Function</p><p style='margin: 0'>Learn how to implement the MAX() function in SQL. We will find the maximum of column values.</p></td></tr><tr><td style='padding: 15px;'><p>2. MIN() Function</p><p style='margin: 0'>Learn how to implement the MIN() function in SQL. We will find the minimum of column values.</p></td></tr><tr><td style='padding: 15px;'><p>3. SUM() Function</p><p style='margin: 0'>Learn how to implement the SUM() function in SQL. We will find the sum of column values.</p></td></tr><tr><td style='padding: 15px;'><p>4. AVG() Function</p><p style='margin: 0'>Learn how to implement the AVG() function in SQL. We will find the average of column values.</p></td></tr><tr><td style='padding: 15px;'><p>5. COUNT() Function</p><p style='margin: 0'>Learn how to implement the COUNT() function in SQL. We will find the count of the number of rows.</p></td></tr></tbody></table><br><h4>8. Constraints in SQL</h4><p>This section focuses on constraints in SQL and the different types of constraints that can be used to manipulate data.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. NOT NULL Constraint</p><p style='margin: 0'>Learn how to work with the NOT NULL constraint in SQL to enforce a column with values, that is, not null. Remember, as columns can have NULL by default, we use the NOT NULL constraint to enforce a column NOT to accept values.</p></td></tr><tr><td style='padding: 15px;'><p>2. UNIQUE Constraint</p><p style='margin: 0'>Learn how to work with the UNIQUE constraint in SQL to uniquely identify each record in a database table. It enforces the uniqueness of column values.</p></td></tr><tr><td style='padding: 15px;'><p>3. PRIMARY KEY Constraint</p><p style='margin: 0'>Learn how to work with the PRIMARY KEY constraint in SQL. A PRIMARY KEY uniquely identifies each record. Not a Primary Key column can never have NULL values.</p></td></tr><tr><td style='padding: 15px;'><p>4. FOREIGN KEY Constraint</p><p style='margin: 0'>Learn how to work with the FOREIGN KEY constraint in SQL. A FOREIGN KEY is a field in one table that refers to the PRIMARY KEY in another. A child table is a table with a foreign key.</p></td></tr><tr><td style='padding: 15px;'><p>5. CHECK Constraint</p><p style='margin: 0'>Learn how to work with the CHECK constraint in SQL to allow only specific values for a column. You can limit the value range set in a column, for example, Age > 18, Marks > 75, and so on.</p></td></tr></tbody></table><br><h4>9. Alter and Update in SQL</h4><p>This section focuses on the ALTER TABLE and UPDATE TABLE functions in SQL that allow us to manipulate records in a table.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. ALTER TABLE Statement</p><p style='margin: 0'>Learn how to work with the ALTER TABLE in SQL to add or delete columns in the existing table. To add a column to an existing table, use the ALTER TABLE with ADD command. To delete a column from an existing table, use the ALTER TABLE with DROP COLUMN.</p></td></tr><tr><td style='padding: 15px;'><p>2. UPDATE Statement</p><p style='margin: 0'>Learn how to work with the UPDATE statement in SQL to update existing records in a table. Use the WHERE clause with the UPDATE statement to avoid updating all records in the table.</p></td></tr><tr><td style='padding: 15px;'><p>3. Aliases</p><p style='margin: 0'>Learn how to work with Aliases in SQL to give a temporary name to a table or column. The AS keyword creates an alias, making column names more readable. Remember that the alias's existence expires when that query's duration ends.</p></td></tr></tbody></table><br><h4>10. Advanced SQL</h4><p>This advanced section delves deep into stored procedures, indexes, and other advanced statements. We will also look at backing up a database and removing tables from a database.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Stored Procedures in SQL</p><p style='margin: 0'>Use the CREATE PROCEDURE statement to learn how to work with stored procedures in SQL. If you want to reuse a query again and again, then create a procedure and save the query in it. Call the procedure whenever you need that same query. Therefore, stored procedures work like a function.</p></td></tr><tr><td style='padding: 15px;'><p>2. Indexes in SQL</p><p style='margin: 0'>Learn how to work with the CREATE INDEX statement in SQL to create indexes in a table. Indexes retrieve data quickly from the database. We will also see how to delete indexes using the DROP INDEX statement.</p></td></tr><tr><td style='padding: 15px;'><p>3. SELECT INTO Statement in SQL</p><p style='margin: 0'>Learn how to work with the SELECT INTO statement in SQL to create a backup copy of your table to a new table. The new table will have the same type and columns as in the first.</p></td></tr><tr><td style='padding: 15px;'><p>4. SELECT TOP Clause in SQL</p><p style='margin: 0'>Learn how to implement the SELECT TOP statement in SQL. We will work with the SELECT TOP PERCENT statement as well.</p></td></tr><tr><td style='padding: 15px;'><p>5. Back Up a Database in SQL</p><p style='margin: 0'>Learn how to back up a database in SQL. We will back up the database in a local directory with the extension .bak.</p></td></tr><tr><td style='padding: 15px;'><p>6. SQL Views</p><p style='margin: 0'>Learn how to work with Views in SQL. A view is a virtual table created from the actual table, displaying the current result set. We will use the CREATE VIEW and DROP VIEW statements to develop and delete views.</p></td></tr><tr><td style='padding: 15px;'><p>7. Drop a Table in SQL</p><p style='margin: 0'>Learn how to drop a table in SQL. Dropping will delete all the records of the table. It will also obliterate the existence of the table.</p></td></tr></tbody></table>

Packt

Database Programming

SQL Server

MySQL

Welcome to this beginner's level course on Microsoft SQL Servers. Understand the concepts of SQL and learn to create a new database and table to perform various operations on it, with live running queries as examples. Work on hands-on exercises and understand database concepts in a real-world scenario.

SQL Server Course for Beginners with 100+ examples

Natural Language Processing (NLP)

Python

Take your first step toward Natural Language Processing with this beginner-to-pro course. Gain an in-depth understanding of deep learning models for NLP with the help of examples. Learn the essential concepts from the absolute beginning with complete unraveling along with examples in Python.

NLP-Natural Language Processing in Python for Beginners

<div>
					<div>
								<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
					</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
							</div>
				</div>
			<p><span>Explore the various concepts and innovative technologies that convert the traditional banking system to digital banking system. Enrol the Digital Banking for Beginners course and learn more about the digitalization process.</span></p>
<p><span>The course presents the latest news about world banking by illustrating the example from nine countries. You will understand the difference between traditional banking and new generation banking. The course also explains the reasons behind the transformation of traditional banking to digital banking. The necessity of embracing the digital banking system will be discussed in the course. The concepts and new innovations in banking, and the examples of web-based platforms such as the Proliferation of Internet Banking, Mobile Banking and 'Direct Banking' concept will also be thoroughly explained in the course. Additionally, the course teaches about innovative technologies such as artificial intelligence, Internet of Things (IOT), Machine Learning, Block-chain, Big Data and more. </span></p>
<p><span>By the end of the course, you will learn the essential front-end and back-end projects that make an organization digital.</span></p>
<h3><strong>What Will I Learn?</strong></h3>
<ul>
<li><span>It just takes 60 minutes or less of your time, to transform you in absorbing the new generation banking knowledge at a base level. As this is shared by a banking Industry veteran, it covers entire banking digital life-journey from front-end to back-end till 2018. Therefore it should generate enough confidence in you, of becoming aware of actual happenings in digital banking world. However, it is important to know that this knowledge is at a base level. But its a great start for your life, as you shall start speaking more confidently on banking innovations and digital banking than ever before . This course helps participant to seek awareness level understanding of Digital Banking in contemporary era both from fancy innovative names and also projects close to CIO's heart such as Back-end Modernization. This course gives practical view of what projects are done in front end as well as Back end to make organization digital.</span></li>
</ul>
<h3><strong>Requirements</strong></h3>
<div>
<ul>
<li>There is no specific banking knowledge needed to attend this course.</li>
</ul>
<h3><strong>Who is the target audience?</strong></h3>
<ul>
<li>Any Aspiring interview candidate who is looking for a new job in banking sector, Any undergraduate, graduate or post-graduate student, any employee of a bank, employee in IT companies working BFS sector, anyone working on banking transaction for his organization or simply people who are interested to learn digital banking. Any school students who would like to take projects or have interest in studying new-generation Banking can also take this course too.</li>
</ul>
</div><table>				<tbody><tr>
					<td colspan="4">Story of Digital Banking -- An overview section</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td><span>FREE</span> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Moving from Traditional Banking to New-gen Banking</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Moving from Traditional Banking to New-gen Banking</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Proliferation of Internet Banking, Mobile Banking and 'direct Banking' concept</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Proliferation of Internet Banking, Mobile Banking and 'direct Banking' concept</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Use of Social media in Banking and arrival of Fintech Firms</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Use of Social media in Banking and arrival of Fintech Firms</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
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					<td colspan="4">Innovative technologies IOT, AI, ML, Block-chain,, Big data etc</td>
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					<td>Innovative technologies IOT, AI, ML, Blockchain,, Big data etc</td>
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					<td><span><i></i> 00:10:00</span></td>
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					<td colspan="4">Illustrative 'CIO Wishlist' to complement or enable comprehensive digital Bank</td>
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					<td><i></i></td>
					<td>Illustrative 'CIO Wishlist' to complement or enable comprehensive digital Bank</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
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					<td colspan="4">Course Certification</td>
				</tr>
				</tbody></table>

iStudy UK

Digital Transformation

Digital Skills

Open Banking

Banking Operations

ICDL (International Certification of Digital Literacy)

Digital Banking for Beginners

<div id="course-pills-1">Duration<p>3 Days</p><p>18 CPD hours</p>This course is intended for<p>This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or  anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away.</p>Overview<p>This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll:<br />Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights.<br />Develop the ability to transform raw text into a structured format that machines can understand and analyze.<br />Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects.<br />Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends.<br />Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction.<br />Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback.</p><p>The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots.</p></div><div id="course-pills-2"><h4>Launch into the Universe of Natural Language Processing</h4><ul><li>The journey begins: Unravel the layers of NLP </li><li>Navigating through the history of NLP </li><li>Merging paths: Text Analytics and NLP </li><li>Decoding language: Word Sense Disambiguation and Sentence Boundary Detection </li><li>First steps towards an NLP Project</li></ul><h4>Unleashing the Power of Feature Extraction</h4><ul><li>Dive into the vast ocean of Data Types </li><li>Purification process: Cleaning Text Data </li><li>Excavating knowledge: Extracting features from Texts </li><li>Drawing connections: Finding Text Similarity through Feature Extraction </li></ul><h4>Engineer Your Text Classifier</h4><ul><li>The new era of Machine Learning and Supervised Learning </li><li>Architecting a Text Classifier </li><li>Constructing efficient workflows: Building Pipelines for NLP Projects </li><li>Ensuring continuity: Saving and Loading Models</li></ul><h4>Master the Art of Web Scraping and API Usage</h4><ul><li>Stepping into the digital world: Introduction to Web Scraping and APIs </li><li>The great heist: Collecting Data by Scraping Web Pages </li><li>Navigating through the maze of Semi-Structured Data</li></ul><h4>Unearth Hidden Themes with Topic Modeling</h4><ul><li>Embark on the path of Topic Discovery </li><li>Decoding algorithms: Understanding Topic-Modeling Algorithms </li><li>Dialing the right numbers: Key Input Parameters for LSA Topic Modeling </li><li>Tackling complexity with Hierarchical Dirichlet Process (HDP)</li></ul><h4>Delving Deep into Vector Representations</h4><ul><li>The Geometry of Language: Introduction to Vectors in NLP</li></ul><h4>Text Manipulation: Generation and Summarization</h4><ul><li>Playing the creator: Generating Text with Markov Chains </li><li>Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank </li><li>Peering into the future: Recent Developments in Text Generation and Summarization </li><li>Solving real-world problems: Addressing Challenges in Extractive Summarization</li></ul><h4>Riding the Wave of Sentiment Analysis</h4><ul><li>Unveiling emotions: Introduction to Sentiment Analysis Tools </li><li>Demystifying the Textblob library </li><li>Preparing the canvas: Understanding Data for Sentiment Analysis </li><li>Training your own emotion detectors: Building Sentiment Models</li></ul><h4>Optional: Capstone Project</h4><ul><li>Apply the skills learned throughout the course. </li><li>Define the problem and gather the data. </li><li>Conduct exploratory data analysis for text data. </li><li>Carry out preprocessing and feature extraction. </li><li>Select and train a model. ? Evaluate the model and interpret the results.</li></ul><h4>Bonus Chapter: Generative AI and NLP</h4><ul><li>Introduction to Generative AI and its role in NLP. </li><li>Overview of Generative Pretrained Transformer (GPT) models. </li><li>Using GPT models for text generation and completion. </li><li>Applying GPT models for improving autocomplete features. </li><li>Use cases of GPT in question answering systems and chatbots.</li></ul><h4>Bonus Chapter: Advanced Applications of NLP with GPT</h4><ul><li>Fine-tuning GPT models for specific NLP tasks. </li><li>Using GPT for sentiment analysis and text classification. </li><li>Role of GPT in Named Entity Recognition (NER). </li><li>Application of GPT in developing advanced chatbots. </li><li>Ethics and limitations of GPT and generative AI technologies.</li></ul></div>

Nexus Human

Learning & Development

Neuro-Linguistic Programming (NLP)

NLP Practitioner

Trainers Course

Central Law Training (CLT)

NLP Boot Camp / Hands-On Natural Language Processing  (TTAI3030)

Duco Digital Training

Machine Learning (ML)

IT Skills

Big Data Analytics

IT (Information Technology)

Computing & IT

Big Data

IT Literacy

Thinking about learning more understanding the role of data within an organisation? As data becomes an important currency in the world and an enabler for the future, it is imperative that all organisations have a firm understanding of the data available to them and the power it can hold.

The BCS Foundation Award in Understanding Data in your Organisation teaches the the terminology, principles, concepts and approaches used within data management, and the overall value of data to an organisation.

Understanding Data in Your Organisation - BCS Foundation Award

<div id="course-pills-1">Duration<p>3 Days</p><p>18 CPD hours</p>This course is intended for<p>Senior Executives<br />CIOs and CTOs<br />Business Intelligence Executives<br />Marketing Executives<br />Data &amp; Business Analytics Specialists<br />Innovation Specialists &amp; Entrepreneurs<br />Academics, and other people interested in Big Data</p>Overview<p>More specifically, BDAW addresses advanced big data architecture topics, including, data formats, transformation, real-time, batch and machine learning processing, scalability, fault tolerance, security and privacy, minimizing the risk of an unsound architecture and technology selection.</p><p>Big Data Architecture Workshop (BDAW) is a learning event that addresses advanced big data architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system. Throughout the highly interactive workshop, students apply concepts to real-world examples resulting in detailed synergistic discussions. The workshop is conducive for students to learn techniques for architecting big data systems, not only from Cloudera?s experience but also from the experiences of fellow students.</p></div><div id="course-pills-2"><h4>Workshop Application Use Cases</h4><ul><li>Oz Metropolitan</li><li>Architectural questions</li><li>Team activity: Analyze Metroz Application Use Cases</li></ul><h4>Application Vertical Slice</h4><ul><li>Definition</li><li>Minimizing risk of an unsound architecture</li><li>Selecting a vertical slice</li><li>Team activity: Identify an initial vertical slice for Metroz</li></ul><h4>Application Processing</h4><ul><li>Real time, near real time processing</li><li>Batch processing</li><li>Data access patterns</li><li>Delivery and processing guarantees</li><li>Machine Learning pipelines</li><li>Team activity: identify delivery and processing patterns in Metroz, characterize response time requirements, identify Machine Learning pipelines</li></ul><h4>Application Data</h4><ul><li>Three V?s of Big Data</li><li>Data Lifecycle</li><li>Data Formats</li><li>Transforming Data</li><li>Team activity: Metroz Data Requirements</li></ul><h4>Scalable Applications</h4><ul><li>Scale up, scale out, scale to X<br />Determining if an application will scale<br />Poll: scalable airport terminal designs<br />Hadoop and Spark Scalability<br />Team activity: Scaling Metroz</li></ul><h4>Fault Tolerant Distributed Systems</h4><ul><li>Principles<br />Transparency<br />Hardware vs. Software redundancy<br />Tolerating disasters<br />Stateless functional fault tolerance<br />Stateful fault tolerance<br />Replication and group consistency<br />Fault tolerance in Spark and Map Reduce<br />Application tolerance for failures<br />Team activity: Identify Metroz component failures and requirements</li></ul><h4>Security and Privacy</h4><ul><li>Principles</li><li>Privacy</li><li>Threats</li><li>Technologies</li><li>Team activity: identify threats and security mechanisms in Metroz</li></ul><h4>Deployment</h4><ul><li>Cluster sizing and evolution</li><li>On-premise vs. Cloud</li><li>Edge computing</li><li>Team activity: select deployment for Metroz</li></ul><h4>Technology Selection</h4><ul><li>HDFS</li><li>HBase</li><li>Kudu</li><li>Relational Database Management Systems</li><li>Map Reduce</li><li>Spark, including streaming, SparkSQL and SparkML</li><li>Hive</li><li>Impala</li><li>Cloudera Search</li><li>Data Sets and Formats</li><li>Team activity: technologies relevant to Metroz</li></ul><h4>Software Architecture</h4><ul><li>Architecture artifacts</li><li>One platform or multiple, lambda architecture</li><li>Team activity: produce high level architecture, selected technologies, revisit vertical slice</li><li>Vertical Slice demonstration</li></ul></div><div id="course-pills-3"><h4>Additional course details:</h4><br /><p>Nexus Humans Big Data Architecture Workshop training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. </p><p></p> This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. <p></p>Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.  <p></p>While we feel this is the best course for the Big Data Architecture Workshop course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.  <p></p>Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.<p></p></div>

Data Engineering

Cloud Architecture

Data Architecture

Data Skills

Big Data Architecture Workshop

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

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

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

Data Science

Welcome to the Bootcamp course. You will obtain a firm understanding of machine learning with this course. By doing so, you will be able to develop machine learning solutions for various challenges you might encounter and be prepared to start using machine learning at work or in technical interviews.

Python Machine Learning Bootcamp

Go from Beginner to Super Advance Level in Machine Learning Algorithms using Python and Mathematical Insights

Machine Learning with Real World Projects

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					<div><p><span>Machine learning as a programming technique has shaped the future of technology. In this course, you will learn how to build intelligent handwriting recognition apps from scratch using Python and Core ML.</span></p><p><span>The </span><b>Machine Learning for Apps Level 4 </b><span>course will teach you how to take advantage of machine learning to code like a pro and build incredible apps that can make predictions. Designed by industry experts, it covers best practices for managing projects, core concepts for creating your own ML model, building a convolutional neural network, and much more.</span></p><p><span>On successful completion, you will be able to build an amazing handwriting recognition app and convolutional neural network from scratch, and have an in-depth understanding of the core ML basics. This course is ideal for those with a basic understanding of iOS development.</span></p></div>
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					<div><p>This best selling <strong>Machine Learning for Apps Level 4 </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Machine Learning for Apps Level 4 </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The <strong>Machine Learning for Apps Level 4 </strong>is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The <strong>Machine Learning for Apps Level 4 </strong>is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p><p>After successfully completing the<strong> Machine Learning for Apps Level 4</strong>, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the <strong>Machine Learning for Apps Level 4 </strong>will help you stand out from the crowd. You can also validate your certification on our website.</p><p>We know that you are busy and that time is precious, so we have designed the <strong>Machine Learning for Apps Level 4 </strong>to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p><p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Course Cloud

Machine Learning for Apps Level 4

<strong>The goal of this course is to use Python machine learning to create algorithms that you can use in the real world. You'll start with the basics of machine learning. You'll learn how to create, train, and optimize models and use these models in real-world applications.</strong>
        <p>Machine learning is a field of computer science through which you can create complex models that perform multiple functions using mathematical input. Python is a popular choice to create machine learning models due to a plethora of libraries easily accessible. This course takes you through this impressive combination of Python and machine learning, teaching you the basics of machine learning to create your own projects.

You'll begin learning about different types of machine learning models and how to choose the relevant ones for your project. You'll learn to optimize this model and apply performance metrics to track its performance. You'll also learn topics like regression, classification, and clustering to improve the performance of your model. You'll learn the basics of neural networks and use scikit-learn to perform calculations in your project.

By the end of this course, you'll have created a face recognition application using everything you've learned in this course.

The code bundle for this course is available at https://github.com/PacktPublishing/Python-Machine-Learning-Crash-Course-for-Beginners</p>
        <h2>What You Will Learn</h2><p>Train different types of machine learning models for your project<br>Prepare and clean data for your project<br>Optimize your machine learning model to best suit your project needs<br>Build your own machine learning model from scratch<br>Apply performance metrics to track the performance of your model<br>Use scikit-learn to perform calculations in your project</p>
        <h2>Audience</h2><p>This course is for Python developers who are new in the field of machine learning. No prior knowledge or experience of machine learning is required. A basic understanding of Python programming will be needed here.</p>
        <h2>Approach</h2><p>This is a hands-on course that takes you through all the machine learning concepts step-by-step while showing you real-world applications for each step.</p>
        <h2>Key Features</h2><p>Build a face recognition application from scratch * Prepare and train your data for your projects * Learn real-world applications of your algorithms</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Python-Machine-Learning-Crash-Course-for-Beginners</p>
        <h2>About the Author</h2><h3>AI Sciences</h3><p>AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.

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

Their courses have successfully helped more than 100,000 students master AI and data science.</p>
        <h2>Course Outline</h2><h4>1. Introduction to the Course</h4><p></p><br><h4>2. Why Machine Learning</h4><p></p><br><h4>3. Process of Learning from Data</h4><p></p><br><h4>4. Machine Learning Methods</h4><p></p><br><h4>5. Data Preparation and Preprocessing</h4><p></p><br><h4>6. Machine Learning Models and Optimization</h4><p></p><br><h4>7. Building Machine Learning Model from Scratch</h4><p></p><br><h4>8. Overfitting, Underfitting and Generalization</h4><p></p><br><h4>9. Machine Learning Model Performance Metrics</h4><p></p><br><h4>10. Dimensionality Reduction</h4><p></p><br><h4>11. Deep Learning Overview</h4><p></p><br><h4>12. Hands-on Machine Learning Project Using Scikit-Learn</h4><p></p><br><h4>13. OPTIONAL Section- Mathematics Wrap-up</h4><p></p>

The goal of this course is to use Python machine learning to create algorithms that you can use in the real world. You'll start with the basics of machine learning. You'll learn how to create, train, and optimize models and use these models in real-world applications.

Python Machine Learning Crash Course for Beginners

<strong>Begin your machine learning journey by learning all about linear regression, logistic regression, and cluster analysis</strong>
        <p>Machine Learning is one of the fundamental skills you need to become a data scientist. It's the steppingstone that will help you understand deep learning and modern data analysis techniques. 

In this course, you'll explore the three fundamental machine learning topics - linear regression, logistic regression, and cluster analysis. Even neural networks geeks (like us) can't help but admit that it's these three simple methods that data science revolves around. So, in this course, we will make the otherwise complex subject matter easy to understand and apply in practice. This course supports statistics theory with practical application of these quantitative methods in Python to help you develop skills in the context of data science. 

We've developed this course with not one but two machine learning libraries: StatsModels and sklearn. You'll be eager to complete this course and get ready to become a successful data scientist! 

All the code and supporting files for this course are available at https://github.com/PacktPublishing/Machine-Learning-101-with-Scikit-learn-and-StatsModels</p>
        <h2>What You Will Learn</h2><p>Confidently work with two of the leading ML packages: statsmodels and sklearn <br>Understand how to perform a linear regression <br>Become familiar with the ins and outs of logistic regression <br>Get to grips with carrying out cluster analysis (both flat and hierarchical) <br>Apply your skills to real-life business cases <br>Get insights into the underlying ideas behind ML models</p>
        <h2>Audience</h2><p>If you want to get acquainted with fundamental machine learning methods, become a successful data scientist, or just get started with building valuable skills in machine learning and data science, this course is for you.</p>
        <h2>Approach</h2><p>The course has a perfect blend of theory and practical knowledge to help you gain a solid understand of the concepts covered.</p>
        <h2>Key Features</h2><p>Learn machine learning with StatsModels and sklearn  * Apply machine learning skills to solve real-world business cases  * Get started with linear regression, logistic regression, and cluster analysis</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/machine-learning-101-with-scikit-learn-and-statsmodels</p>
        <h2>About the Author</h2><h3>365 Careers Ltd.</h3><p>365 Careers' courses have been taken by more than 203,000 students in 204 countries. People working at world-class firms such as Apple, PayPal, and Citibank have completed 365 Careers trainings. By choosing 365 Careers, you make sure you will learn from proven experts who have a passion for teaching, and can take you from beginner to pro in the shortest possible amount of time.

If you want to become a financial analyst, a finance manager, an FP&A analyst, an investment banker, a business executive, an entrepreneur, a business intelligence analyst, a data analyst, or a data scientist, 365 Careers' courses are the perfect place to start.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><br><h4>2. Setting Up the Working Environment</h4><p></p><br><h4>3. Linear Regression with StatsModels</h4><p></p><br><h4>4. Linear Regression with Sklearn</h4><p></p><br><h4>5. Linear Regression - Practical Example</h4><p></p><br><h4>6. Logistic Regression</h4><p></p><br><h4>7. Cluster Analysis</h4><p></p><br><h4>8. Cluster Analysis: Additional Topics</h4><p></p>

Begin your machine learning journey by learning all about linear regression, logistic regression, and cluster analysis

Machine Learning 101 with Scikit-learn and StatsModels

<strong>In this course, you will learn Python fundamentals, and the concepts of the amazing pandas data science library needed to pre-process and prepare the data for machine learning algorithms.</strong>
        <p>Machine learning is one of the most exciting fields in the hi-tech industry, gaining momentum in various applications. Companies are looking for data scientists, data engineers, and machine language (ML) experts to develop products, features, and projects that will help them unleash the power of machine learning. This course will show you how to prepare data for machine learning algorithms using Python and pandas library.

The course starts by explaining the installation process of Anaconda and Jupyter. Once you are ready with the setup, you will understand Python fundamentals, such as variables, data types, conditional statements, loops, and modules. Next, you will go through the pandas library and learn how to use it for loading real-world large datasets. Towards the end, you will learn the steps and techniques to clean data and make it ready to move into machine learning algorithms.

By the end of this course, you will be well-versed with Python fundamentals and pandas library and will be ready to take on data science projects.

The code bundle for this course is available at https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners-Level-2</p>
        <h2>What You Will Learn</h2><p>Understand how to use Jupyter Lab for Jupyter notebooks<br>Learn Python fundamentals<br>Load large datasets from files using pandas<br>Uncover techniques to perform data analysis and exploration<br>Group, sort, export, select, filter, and clean data<br>Find out how to preview the data frame</p>
        <h2>Audience</h2><p>This course is designed for beginners looking to understand the theoretical side of machine learning and to enter the practical side of data science. You will understand the fundamentals of Python and learn how to pre-process data before using it in machine learning algorithms. There are no prerequisites for taking up this course; however, it is recommended to finish with the Machine Learning for Absolute Beginners - Level 1 course.</p>
        <h2>Approach</h2><p>With the help of exercises and activities, this course will show you how to use Python and pandas library for cleaning data before moving it into machine learning algorithms.</p>
        <h2>Key Features</h2><p>Learn how to use Python for data science and machine learning projects * Understand the interface of Jupyter lab tool * Discover how to get data ready for machine learning algorithms</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners-Level-2 </p>
        <h2>About the Author</h2><h3>Idan Gabrieli</h3><p>Idan Gabrieli has worked in various engineering positions in Israel's high-tech industry. Idan has gained extensive experience with hundreds of business companies, transforming their challenges and opportunities into practical use cases and leveraging cutting-edge technologies.

Idan's expertise spans multiple domains, including cloud computing, machine learning, data science, and electronics. Since 2014, Idan has created and published online courses on various topics worldwide. Idan is recognized as a high-rated instructor by leading educational providers.

Idan simplifies complex technology and provides high-quality educational content with specific learning objectives that are well-structured, combining various multimedia teaching options.</p>
        <h2>Course Outline</h2><h4>1. Getting Started with Level 2!</h4><p></p><br><h4>2. Python Fundamentals for Data Science</h4><p></p><br><h4>3. Introduction to the Pandas Library</h4><p></p><br><h4>4. Loading Data into a DataFrame</h4><p></p><br><h4>5. Data Cleaning and Transformation</h4><p></p><br><h4>6. Course Summary</h4><p></p>

In this course, you will learn Python fundamentals, and the concepts of the amazing pandas data science library needed to pre-process and prepare the data for machine learning algorithms.

Machine Learning for Absolute Beginners - Level 2

<strong>Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning &amp; More!</strong>
        <p>Do you ever want to be a data scientist and build Machine Learning projects that can solve real-life problems? If yes, then this course is perfect for you.
You will train machine learning algorithms to classify flowers, predict house price, identify handwritings or digits, identify staff that is most likely to leave prematurely, detect cancer cells and much more!
Inside the course, you'll learn how to:
&bull;	Set up a Python development environment correctly
&bull;	Gain complete machine learning toolsets to tackle most real-world problems
&bull;	Understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix, prevision, recall, etc. and when to use them.
&bull;	Combine multiple models with by bagging, boosting or stacking
&bull;	Make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering etc. to understand your data
&bull;	Develop in Jupyter (IPython) notebook, Spyder and various IDE
&bull;	Communicate visually and effectively with Matplotlib and Seaborn
&bull;	Engineer new features to improve algorithm predictions
&bull;	Make use of train/test, K-fold and Stratified K-fold cross-validation to select the correct model and predict model perform with unseen data
&bull;	Use SVM for handwriting recognition, and classification problems in general
&bull;	Use decision trees to predict staff attrition
&bull;	Apply the association rule to retail shopping datasets
&bull;	And much more!
By the end of this course, you will have a Portfolio of 12 Machine Learning projects that will help you land your dream job or enable you to solve real-life problems in your business, job or personal life with Machine Learning algorithms.</p>
        <h2>What You Will Learn</h2><p>&bull;&nbsp;&nbsp;Learn to Build Powerful Machine Learning Models to Solve Any Problem<br>&bull;&nbsp;&nbsp;Learn to Train machine learning algorithms to predict house prices, identify handwriting, detect cancer cells &amp; more</p>
        <h2>Audience</h2><p>A newbie who wants to learn machine learning algorithm with Python. Anyone who has a deep interest in the practical application of machine learning to real world problems. Anyone wishes to move beyond the basics and develop an understanding of the whole range of machine learning algorithms. Any intermediate to advanced EXCEL users who is unable to work with large datasets. Anyone interested to present their findings in a professional and convincing manner. Anyone who wishes to start or transit into a career as a data scientist. Anyone who wants to apply machine learning to their domain.</p>
        <h2>Approach</h2><p>You'll go from beginner to extremely high-level and your instructor will build each algorithm with you step by step on screen.</p>
        <h2>Key Features</h2><p>&bull;&nbsp;&nbsp;Solve any problem in your business or job with powerful Machine Learning models * &bull;&nbsp;&nbsp;Go from zero to hero in Python, Seaborn, Matplotlib, Scikit-Learn, SVM, and unsupervised Machine Learning etc.</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/the-complete-machine-learning-course-with-python</p>
        <h2>About the Author</h2><h3>Anthony Ng</h3><p>Anthony Ng has spent almost 10 years in the education sector covering topics such as algorithmic trading, financial data analytics, investment, and portfolio management and more. He has worked in various financial institutions and has assisted Quantopian to conduct Algorithmic Trading Workshops in Singapore since 2016. He has also presented in QuantCon Singapore 2016 and 2017. He is passionate about finance, data science and Python and enjoys researching, teaching and sharing knowledge. He holds a Master of Science in Financial Engineering from NUS Singapore and MBA and Bcom from Otago University.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What Does the Course Cover?</p><p style='margin: 0'>Introduction: What Does the Course Cover?</p></td></tr></tbody></table><br><h4>2. Getting Started with Anaconda</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. [Windows OS] Downloading & Installing Anaconda</p><p style='margin: 0'>Getting Started with Anaconda: [Windows OS] Downloading &amp; Installing Anaconda</p></td></tr><tr><td style='padding: 15px;'><p>2. [Windows OS] Managing Environment</p><p style='margin: 0'>Getting Started with Anaconda: [Windows OS] Managing Environment</p></td></tr><tr><td style='padding: 15px;'><p>3. Navigating the Spyder & Jupyter Notebook Interface</p><p style='margin: 0'>Getting Started with Anaconda: Navigating the Spyder &amp; Jupyter Notebook Interface</p></td></tr><tr><td style='padding: 15px;'><p>4. Downloading the IRIS Datasets</p><p style='margin: 0'>Getting Started with Anaconda: Downloading the IRIS Datasets</p></td></tr><tr><td style='padding: 15px;'><p>5. Data Exploration and Analysis</p><p style='margin: 0'>Getting Started with Anaconda: Data Exploration and Analysis</p></td></tr><tr><td style='padding: 15px;'><p>6. Presenting Your Data</p><p style='margin: 0'>Getting Started with Anaconda: Presenting Your Data</p></td></tr></tbody></table><br><h4>3. Regression</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Regression: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Categories of Machine Learning</p><p style='margin: 0'>Regression: Categories of Machine Learning</p></td></tr><tr><td style='padding: 15px;'><p>3. Working with Scikit-Learn</p><p style='margin: 0'>Regression: Working with Scikit-Learn</p></td></tr><tr><td style='padding: 15px;'><p>4. Boston Housing Data - EDA</p><p style='margin: 0'>Regression: Boston Housing Data - EDA</p></td></tr><tr><td style='padding: 15px;'><p>5. Correlation Analysis and Feature Selection</p><p style='margin: 0'>Regression: Correlation Analysis and Feature Selection</p></td></tr><tr><td style='padding: 15px;'><p>6. Simple Linear Regression Modelling with Boston Housing Data</p><p style='margin: 0'>Regression: Simple Linear Regression Modelling with Boston Housing Data</p></td></tr><tr><td style='padding: 15px;'><p>7. Robust Regression</p><p style='margin: 0'>Regression: Robust Regression</p></td></tr><tr><td style='padding: 15px;'><p>8. Evaluate Model Performance</p><p style='margin: 0'>Regression: Evaluate Model Performance</p></td></tr><tr><td style='padding: 15px;'><p>9. Multiple Regression with statsmodel</p><p style='margin: 0'>Regression: Multiple Regression with statsmodel</p></td></tr><tr><td style='padding: 15px;'><p>10. Multiple Regression and Feature Importance</p><p style='margin: 0'>Regression: Multiple Regression and Feature Importance</p></td></tr><tr><td style='padding: 15px;'><p>11. Ordinary Least Square Regression and Gradient Descent</p><p style='margin: 0'>Regression: Ordinary Least Square Regression and Gradient Descent</p></td></tr><tr><td style='padding: 15px;'><p>12. Regularised Method for Regression</p><p style='margin: 0'>Regression: Regularised Method for Regression</p></td></tr><tr><td style='padding: 15px;'><p>13. Polynomial Regression</p><p style='margin: 0'>Regression: Polynomial Regression</p></td></tr><tr><td style='padding: 15px;'><p>14. Dealing with Non-linear relationships</p><p style='margin: 0'>Regression: Dealing with Non-linear relationships</p></td></tr><tr><td style='padding: 15px;'><p>15. Feature Importance Revisited</p><p style='margin: 0'>Regression: Feature Importance Revisited</p></td></tr><tr><td style='padding: 15px;'><p>16. Data Pre-Processing 1</p><p style='margin: 0'>Regression: Data Pre-Processing 1</p></td></tr><tr><td style='padding: 15px;'><p>17. Data Pre-Processing 2</p><p style='margin: 0'>Regression: Data Pre-Processing 2</p></td></tr><tr><td style='padding: 15px;'><p>18. Variance Bias Trade Off - Validation Curve</p><p style='margin: 0'>Regression: Variance Bias Trade Off - Validation Curve</p></td></tr><tr><td style='padding: 15px;'><p>19. Variance Bias Trade Off - Learning Curve</p><p style='margin: 0'>Regression: Variance Bias Trade Off - Learning Curve</p></td></tr><tr><td style='padding: 15px;'><p>20. Cross Validation</p><p style='margin: 0'>Regression: Cross Validation</p></td></tr></tbody></table><br><h4>4. Classification</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Classification: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Logistic Regression 1</p><p style='margin: 0'>Classification: Logistic Regression 1</p></td></tr><tr><td style='padding: 15px;'><p>3. Logistic Regression 2</p><p style='margin: 0'>Classification: Logistic Regression 2</p></td></tr><tr><td style='padding: 15px;'><p>4. MNIST Project 1 - Introduction</p><p style='margin: 0'>Classification: MNIST Project 1 - Introduction</p></td></tr><tr><td style='padding: 15px;'><p>5. MNIST Project 2 - SGDClassifiers</p><p style='margin: 0'>Classification: MNIST Project 2 - SGDClassifier</p></td></tr><tr><td style='padding: 15px;'><p>6. MNIST Project 3 - Performance Measures</p><p style='margin: 0'>Classification: MNIST Project 3 - Performance Measures</p></td></tr><tr><td style='padding: 15px;'><p>7. MNIST Project 4 - Confusion Matrix, Precision, Recall and F1 Score</p><p style='margin: 0'>Classification: MNIST Project 4 - Confusion Matrix, Precision, Recall and F1 Score</p></td></tr><tr><td style='padding: 15px;'><p>8. MNIST Project 5 - Precision and Recall Tradeoff</p><p style='margin: 0'>Classification: MNIST Project 5 - Precision and Recall Tradeoff</p></td></tr><tr><td style='padding: 15px;'><p>9. MNIST Project 6 - The ROC Curve</p><p style='margin: 0'>Classification: MNIST Project 6 - The ROC Curve</p></td></tr></tbody></table><br><h4>5. Support Vector Machine (SVM)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Support Vector Machine (SVM): Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Support Vector Machine (SVM) Concepts</p><p style='margin: 0'>Support Vector Machine (SVM): Support Vector Machine (SVM) Concepts</p></td></tr><tr><td style='padding: 15px;'><p>3. Linear SVM Classification</p><p style='margin: 0'>Support Vector Machine (SVM): Linear SVM Classification</p></td></tr><tr><td style='padding: 15px;'><p>4. Polynomial Kernel</p><p style='margin: 0'>Support Vector Machine (SVM): Polynomial Kernel</p></td></tr><tr><td style='padding: 15px;'><p>5. Gaussian Radial Basis Function</p><p style='margin: 0'>Support Vector Machine (SVM): Gaussian Radial Basis Function</p></td></tr><tr><td style='padding: 15px;'><p>6. Support Vector Regression</p><p style='margin: 0'>Support Vector Machine (SVM): Support Vector Regression</p></td></tr><tr><td style='padding: 15px;'><p>7. Advantages and Disadvantages of SVM</p><p style='margin: 0'>Support Vector Machine (SVM): Advantages and Disadvantages of SVM</p></td></tr></tbody></table><br><h4>6. Tree</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Tree: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Decision Tree</p><p style='margin: 0'>Tree: What is Decision Tree</p></td></tr><tr><td style='padding: 15px;'><p>3. Training a Decision Tree</p><p style='margin: 0'>Tree: Training a Decision Tree</p></td></tr><tr><td style='padding: 15px;'><p>4. Visualising a Decision Trees</p><p style='margin: 0'>Tree: Visualising a Decision Trees</p></td></tr><tr><td style='padding: 15px;'><p>5. Decision Tree Learning Algorithm</p><p style='margin: 0'>Tree: Decision Tree Learning Algorithm</p></td></tr><tr><td style='padding: 15px;'><p>6. Decision Tree Regression</p><p style='margin: 0'>Tree: Decision Tree Regression</p></td></tr><tr><td style='padding: 15px;'><p>7. Overfitting and Grid Search</p><p style='margin: 0'>Tree: Overfitting and Grid Search</p></td></tr><tr><td style='padding: 15px;'><p>8. Where to From Here</p><p style='margin: 0'>Tree: Where to From Here</p></td></tr><tr><td style='padding: 15px;'><p>9. Project HR - Loading and preprocesing data</p><p style='margin: 0'>Tree: Project HR - Loading and preprocesing data</p></td></tr><tr><td style='padding: 15px;'><p>10. Project HR - Modelling</p><p style='margin: 0'>Tree: Project HR - Modelling</p></td></tr></tbody></table><br><h4>7. Ensemble Machine Learning</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Ensemble Machine Learning: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Ensemble Learning Methods Introduction</p><p style='margin: 0'>Ensemble Machine Learning: Ensemble Learning Methods Introduction</p></td></tr><tr><td style='padding: 15px;'><p>3. Bagging Part 1</p><p style='margin: 0'>Ensemble Machine Learning: Bagging Part 1</p></td></tr><tr><td style='padding: 15px;'><p>4. Bagging Part 2</p><p style='margin: 0'>Ensemble Machine Learning: Bagging Part 2</p></td></tr><tr><td style='padding: 15px;'><p>5. Random Forests</p><p style='margin: 0'>Ensemble Machine Learning: Random Forests</p></td></tr><tr><td style='padding: 15px;'><p>6. Extra-Trees</p><p style='margin: 0'>Ensemble Machine Learning: Extra-Trees</p></td></tr><tr><td style='padding: 15px;'><p>7. AdaBoost</p><p style='margin: 0'>Ensemble Machine Learning: Decision Tree Regression</p></td></tr><tr><td style='padding: 15px;'><p>8. Gradient Boosting Machine</p><p style='margin: 0'>Ensemble Machine Learning: Gradient Boosting Machine</p></td></tr><tr><td style='padding: 15px;'><p>9. XGBoost</p><p style='margin: 0'>Ensemble Machine Learning: XGBoost</p></td></tr><tr><td style='padding: 15px;'><p>10. Project HR - Human Resources Analytics</p><p style='margin: 0'>Ensemble Machine Learning: Project HR - Human Resources Analytics</p></td></tr><tr><td style='padding: 15px;'><p>11. Ensemble of ensembles Part 1</p><p style='margin: 0'>Ensemble Machine Learning: Ensemble of ensembles Part 1</p></td></tr><tr><td style='padding: 15px;'><p>12. Ensemble of ensembles Part 2</p><p style='margin: 0'>Ensemble Machine Learning: Ensemble of ensembles Part 2</p></td></tr></tbody></table><br><h4>8. k-Nearest Neighbours (kNN)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. kNN Introduction</p><p style='margin: 0'>K-Nearest Neighbours (kNN): kNN Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. kNN Concepts</p><p style='margin: 0'>K-Nearest Neighbours (kNN): kNN Concepts</p></td></tr><tr><td style='padding: 15px;'><p>3. kNN and Iris Dataset Demo</p><p style='margin: 0'>K-Nearest Neighbours (kNN): kNN and Iris Dataset Demo</p></td></tr><tr><td style='padding: 15px;'><p>4. Distance Metric</p><p style='margin: 0'>K-Nearest Neighbours (kNN): Distance Metric</p></td></tr><tr><td style='padding: 15px;'><p>5. Project Cancer Detection Part 1</p><p style='margin: 0'>K-Nearest Neighbours (kNN): Project Cancer Detection Part 1</p></td></tr><tr><td style='padding: 15px;'><p>6. Project Cancer Detection Part 2</p><p style='margin: 0'>K-Nearest Neighbours (kNN): Project Cancer Detection Part 2</p></td></tr></tbody></table><br><h4>9. Dimensionality Reduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Dimensionality Reduction: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Dimensionality Reduction Concept</p><p style='margin: 0'>Dimensionality Reduction: Dimensionality Reduction Concept</p></td></tr><tr><td style='padding: 15px;'><p>3. PCA Introduction</p><p style='margin: 0'>Dimensionality Reduction: PCA Introduction</p></td></tr><tr><td style='padding: 15px;'><p>4. Dimensionality Reduction Demo</p><p style='margin: 0'>Dimensionality Reduction: Dimensionality Reduction Demo</p></td></tr><tr><td style='padding: 15px;'><p>5. Project Wine 1: Dimensionality Reduction with PCA</p><p style='margin: 0'>Dimensionality Reduction: Project Wine 1: Dimensionality Reduction with PCA</p></td></tr><tr><td style='padding: 15px;'><p>6. Project Wine 2: Choosing the Number of Components</p><p style='margin: 0'>Dimensionality Reduction: Project Wine 2: Choosing the Number of Components</p></td></tr><tr><td style='padding: 15px;'><p>7. Kernel PCA</p><p style='margin: 0'>Dimensionality Reduction: Kernel PCA</p></td></tr><tr><td style='padding: 15px;'><p>8. Kernel PCA Demo</p><p style='margin: 0'>Dimensionality Reduction: Kernel PCA Demo</p></td></tr><tr><td style='padding: 15px;'><p>9. LDA & Comparison between LDA and PCA</p><p style='margin: 0'>Dimensionality Reduction: LDA &amp; Comparison between LDA and PCA</p></td></tr></tbody></table><br><h4>10. Unsupervised Learning: Clustering</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Unsupervised Learning: Clustering: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Clustering Concepts</p><p style='margin: 0'>Unsupervised Learning: Clustering: Clustering Concepts</p></td></tr><tr><td style='padding: 15px;'><p>3. MLextend</p><p style='margin: 0'>Unsupervised Learning: Clustering: MLextend</p></td></tr><tr><td style='padding: 15px;'><p>4. Ward's Agglomerative Hierarchical Clustering</p><p style='margin: 0'>Unsupervised Learning: Clustering: Ward's Agglomerative Hierarchical Clustering</p></td></tr><tr><td style='padding: 15px;'><p>5. Truncating Dendrogram</p><p style='margin: 0'>Unsupervised Learning: Clustering: Truncating Dendrogram</p></td></tr><tr><td style='padding: 15px;'><p>6. k-Means Clustering</p><p style='margin: 0'>Unsupervised Learning: Clustering: k-Means Clustering</p></td></tr><tr><td style='padding: 15px;'><p>7. Elbow Method</p><p style='margin: 0'>Unsupervised Learning: Clustering: Elbow Method</p></td></tr><tr><td style='padding: 15px;'><p>8. Silhouette Analysis</p><p style='margin: 0'>Unsupervised Learning: Clustering: Silhouette Analysis</p></td></tr><tr><td style='padding: 15px;'><p>9. Mean Shift</p><p style='margin: 0'>Unsupervised Learning: Clustering: Mean Shift</p></td></tr></tbody></table>

TensorFlow

Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning &amp; More!

The Complete Machine Learning Course with Python

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					<div><p>This best selling Machine Learning - Use in Flutter has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Machine Learning - Use in Flutter is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The Machine Learning - Use in Flutter is CPD-accredited, so you can be confident you're completing a quality training course which will boost your CV and enhance your career potential. The Machine Learning - Use in Flutter is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p><p>After successfully completing the Machine Learning - Use in Flutter, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Machine Learning - Use in Flutter will help you stand out from the crowd. You can also validate your certification on our website.</p><p>We know that you are busy and that time is precious, so we have designed the Machine Learning - Use in Flutter to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p><p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Learning To Learn

Machine Learning - Use in Flutter

<strong>This course will take you through the fundamental concepts of machine learning (ML) and artificial intelligence (AI). By the end of this course, you will be ready to dive into the advanced concepts of ML.</strong>
        <p>Instead of using hard-coded rules for performing something, artificial intelligence (AI) and machine learning (ML) prepare the machines to learn things from data to decipher the complex patterns automatically and then use it for building multiple use cases. If you too want to make applications and solve complex problems using AI and ML, then this course will help you to get started with the basics.

The course starts by highlighting the learning objectives and explains the rise of AI in today's world. Next, you will be introduced to the concepts of ML. You will learn to understand ML terminologies and learn how to train a model. Towards the end, you will become familiar with the classification of ML systems, including the topics of supervised and unsupervised learning, regression, clustering, and reinforcement.

By the end of this course, you will have a fundamental knowledge of AI and ML.

All the resource for this course are available at https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners---Level-1</p>
        <h2>What You Will Learn</h2><p>Find out why machine learning (ML) is called a black box<br>Get to grips with the features and labels of ML<br>Uncover techniques for training ML models<br>Find out the differences between supervised and unsupervised learning<br>Understand regression, clustering, and dimension reduction</p>
        <h2>Audience</h2><p>If you are a developer, product or project manager, engineer, or a data science enthusiast, who is looking to learn the fundamentals of artificial intelligence (AI) and machine learning (ML), this course is for you. There is no prerequisite to start this course as it is specially designed for absolute beginners.</p>
        <h2>Approach</h2><p>With the help of simple narration, interesting examples, and practical tips, this course helps you to get started with artificial intelligence (AI) and machine learning (ML).</p>
        <h2>Key Features</h2><p>Learn the basics of artificial intelligence (AI), machine learning (ML), and deep learning * Find out how ML helps in training a model * Discover how ML systems are classified</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners---Level-1</p>
        <h2>About the Author</h2><h3>Idan Gabrieli</h3><p>Idan Gabrieli has worked in various engineering positions in Israel's high-tech industry. Idan has gained extensive experience with hundreds of business companies, transforming their challenges and opportunities into practical use cases and leveraging cutting-edge technologies.

Idan's expertise spans multiple domains, including cloud computing, machine learning, data science, and electronics. Since 2014, Idan has created and published online courses on various topics worldwide. Idan is recognized as a high-rated instructor by leading educational providers.

Idan simplifies complex technology and provides high-quality educational content with specific learning objectives that are well-structured, combining various multimedia teaching options.</p>
        <h2>Course Outline</h2><h4>1. Getting Started with Level 1!</h4><p></p><br><h4>2. The Rise of Artificial Intelligence</h4><p></p><br><h4>3. Introduction to Machine Learning</h4><p></p><br><h4>4. Classification of ML Systems</h4><p></p><br><h4>5. Course Summary</h4><p></p>

Deep Learning

This course will take you through the fundamental concepts of machine learning (ML) and artificial intelligence (AI). By the end of this course, you will be ready to dive into the advanced concepts of ML.

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