Name: CNC (Computer Numerical Control) Programming
Price: 79 GBP
Availability: InStock

<p><strong>24 Hour Flash Deal **33-in-1 Data Protection and Data Security Mega Bundle**<br /><br /> Data Protection and Data Security Enrolment Gifts  **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter **</strong><br /><br />Take the initial steps toward a successful long-term career by studying the <strong>Data Protection and Data Security</strong> package online with <strong>Studyhub </strong>through our online learning platform. The Data Protection and Data Security bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass.<br /><br />This <strong>Data Protection and Data Security</strong> course provides complete 360-degree training on Data Protection and Data Security. You'll get not one, not two, not three, but <strong>thirty-three</strong> Data Protection and Data Security courses included in this course. Plus Studyhub's signature <strong>Forever Access</strong> is given as always, meaning these <strong>Data Protection and Data Security</strong> courses are yours for as long as you want them once you enrol in this course<br /><strong>This Data Protection and Data Security Bundle consists the following career oriented courses:</strong></p><ul><li>Course 01: Cyber Security Awareness Training</li><li>Course 02: Web Application Penetration Testing</li><li>Course 03: Data Protection Level 3 and Data Security (GDPR) Training Certification</li><li>Course 04: Cyber Security Law</li><li>Course 05: Cyber Security Incident Handling and Incident Response</li><li>Course 06: GDPR Training</li><li>Course 07: Information Architecture (IA) Fundamentals for Website Design</li><li>Course 08: Financial Crime Officer</li><li>Course 09: Transaction Monitoring in Financial Services: Ensuring Security</li><li>Course 10: Financial Statements Fraud Detection Training</li><li>Course 11: CompTIA CySA+ Cybersecurity Analyst Course</li><li>Course 12: Machine Learning Basics</li><li>Course 13: Python Basic Programming for Absolute Beginners</li><li>Course 14: Data Analysis &amp; Forecasting</li><li>Course 15: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 16: Microsoft Excel Complete Course 2019</li><li>Course 17: VLOOKUP: Master Excel Formula VLOOKUP in 60 minutes!</li><li>Course 18: Excel: Top 50 Microsoft Excel Formulas in 50 Minutes!</li><li>Course 19: JavaScript Foundations</li><li>Course 20: jQuery Masterclass Course: JavaScript and AJAX Coding Bible</li><li>Course 21: PHP Web Development with MySQL</li><li>Course 22: Node JS: API Development with Swagger Interface Description Language</li><li>Course 23: Digital Marketing for Beginners to Advanced</li><li>Course 24: Google Analytics</li><li>Course 25: Content Management</li><li>Course 26: Info Graphics Web Design - Affinity Designer Training</li><li>Course 27: Responsive Web Design</li><li>Course 28: MVC and Entity Framework</li><li>Course 29: Web Design with Adobe XD</li><li>Course 30: Diploma in Adobe Illustrator</li><li>Course 31: Digital Art - Sketching In Photoshop</li><li>Course 32: AutoCAD VBA Programming - Beginner course</li><li>Course 33: Learn MySQL from Scratch</li></ul><p><strong>In this exclusive Data Protection and Data Security bundle, you really hit the jackpot. Here's what you get:</strong></p><ul><li>Step by step Data Protection and Data Security lessons</li><li>One to one assistance from Data Protection and Data Security professionals if you need it</li><li>Innovative exams to test your knowledge after the Data Protection and Data Security course</li><li>24/7 customer support should you encounter any hiccups</li><li>Top-class learning portal</li><li>Unlimited lifetime access to all thirty-three Data Protection and Data Security courses</li><li>Digital Certificate, Transcript and student ID are all included in the price</li><li>PDF certificate immediately after passing</li><li>Original copies of your Data Protection and Data Security certificate and transcript on the next working day</li><li>Easily learn the Data Protection and Data Security skills and knowledge you want from the comfort of your home</li></ul> <p>The <strong>Data Protection and Data Security</strong> course has been prepared by focusing largely on Data Protection and Data Security career readiness. It has been designed by our Data Protection and Data Security <strong>specialists </strong>in a manner that you will be likely to find yourself head and shoulders above the others. For better learning, one to one assistance will also be provided if it's required by any learners.<br /><br />The <strong>Data Protection and Data Security</strong> Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This <strong>Data Protection and Data Security</strong> bundle course has been created with thirty-three premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field.<br /><br />This <strong>Data Protection and Data Security</strong> Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Data Protection and Data Security Elementary modules, allowing our students to grasp each lesson quickly.<br /><br />The <strong>Data Protection and Data Security</strong> course is self-paced and can be taken from the comfort of your home, office, or on the go! With our Student ID card you will get discounts on things like music, food, travel and clothes etc.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        330 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 <strong>Data Protection and Data Security </strong>training is suitable for -</p><ul><li>Students</li><li>Recent graduates</li><li>Job Seekers</li><li>Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Data Protection and Data Security</li></ul><p>After completing this course you can progress towards-</p><ul><li>BCS Foundation Certificate in Data Protection</li><li>BCS Practitioner Certificate in Data Protection</li><li>NCFE Level 2 Certificate in Understanding Data Protection and Data Security</li></ul><p><strong>Please Note:</strong> Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To participate in this <strong>Data Protection and Data Security </strong>course, all you need is -</p><ul><li>A smart device</li><li>A secure internet connection</li><li>And a keen interest in Data Protection and Data Security</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>You will be able to kickstart your <strong>Data Protection and Data Security </strong>career because this course includes various courses as a bonus. This Data Protection and Data Security is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Data Protection and Data Security career opportunities.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><ul><li>CPD Accredited e-Certificate - Free</li><li>CPD Accredited Hardcopy Certificate - Free</li><li>Enrolment Letter - Free</li><li>Student ID Card - Free</li></ul></div>

                        </div>

Studyhub UK

Data Protection

Cyber Security

Data Security

Cyber Security Foundation

Certified in Data Protection (CDP)

ICDL (International Certification of Digital Literacy)

Level 2 Certificate in Understanding Data Protection and Data Security - CPD Certified

General Admission

<p><strong>24 Hour Flash Deal **40-in-1 Financial Modelling &amp; Valuation Analyst (FMVA) Essentials Mega Bundle**<br /><br /> Financial Modelling &amp; Valuation Analyst (FMVA) Essentials Enrolment Gifts  **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter **</strong><br /><br />Take the initial steps towards a successful long-term career by studying the <strong>Financial Modelling &amp; Valuation Analyst (FMVA) Essentials</strong> package online with Studyhub through our online learning platform. The Financial Modelling &amp; Valuation Analyst (FMVA) Essentials bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass.<br /><br />This <strong>Financial Modelling &amp; Valuation Analyst (FMVA) Essentials</strong> course provides complete 360-degree training on Financial Modelling &amp; Valuation Analyst (FMVA) Essentials. You'll get not one, not two, not three, but forty Financial Modelling &amp; Valuation Analyst (FMVA) Essentials courses included in this course. Plus Studyhub's signature Forever Access is given as always, meaning these Financial Modelling &amp; Valuation Analyst (FMVA) Essentials courses are yours for as long as you want them once you enrol in this course.<br /><br /><strong>This Financial Modelling &amp; Valuation Analyst (FMVA) Essentials Bundle consists the following career oriented courses:</strong></p><ul><li>Course 01: Financial Modelling</li><li>Course 02: Financial Modelling Course for a Non-Finance Background</li><li>Course 03: Make Business Plans: Forecasting and Budgeting</li><li>Course 04: Managing Budget: Financial Statements and Money Management</li><li>Course 05: Capital Budgeting &amp; Investment Decision Rules</li><li>Course 06: Raise Money and Valuation for Business</li><li>Course 07: Microsoft Excel Complete Course 2019</li><li>Course 08: VLOOKUP: Master Excel Formula VLOOKUP in 60 minutes!</li><li>Course 09: Excel: Top 50 Microsoft Excel Formulas in 50 Minutes!</li><li>Course 10: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 11: Microsoft PowerPoint for Beginners</li><li>Course 12: Accounting Fundamentals Diploma</li><li>Course 13: Understanding Financial Statements and Analysis</li><li>Course 14: Fundamentals of Corporate Finance</li><li>Course 15: Investment Banking Operations Professional</li><li>Course 16: Fundamentals of Business Analysis</li><li>Course 17: Finance: Financial Risk Management</li><li>Course 18: Credit Control and Compliance Training</li><li>Course 19: AutoCAD VBA Programming - Beginner course</li><li>Course 20: Python Basic Programming for Absolute Beginners</li><li>Course 21: Financial Planning</li><li>Course 22: Cost Control Process and Management</li><li>Course 23: Economics Level 2 Diploma</li><li>Course 24: Actuary Certification: Navigating the Complex World of Risk and Finance</li><li>Course 25: Finance Law Fundamentals: Legal Aspects of Financial Transactions</li><li>Course 26: Accounts Receivable Management: Optimising Financial Processes</li><li>Course 27: Efficient Accounts Payable Processing: Streamlining Financial Transactions</li><li>Course 28: Demystifying Depreciation Accounting: Financial Insights</li><li>Course 29: Mastering Partnership Accounting: Financial Strategies and Reporting</li><li>Course 30: Finance for Non-finance Managers Certification</li><li>Course 31: Corporate Finance: Profitability in a Financial Downturn</li><li>Course 32: Business Strategy Planning</li><li>Course 33: Debt Management, Assessment, Financing &amp; Counselling</li><li>Course 34: Machine Learning Basics</li><li>Course 35: CompTIA CySA+ Cybersecurity Analyst Course</li><li>Course 36: Business Finance</li><li>Course 37: Financial Investigator</li><li>Course 38: Financial Analysis Methods</li><li>Course 39: Personal Financial Management &amp; Wellness</li><li>Course 40: Tax Strategy and Financial Planning for Beginners</li></ul><p><strong>In this exclusive Financial Modelling &amp; Valuation Analyst (FMVA) Essentials bundle, you really hit the jackpot. Here's what you get:</strong></p><ul><li>Step by step Financial Modelling &amp; Valuation Analyst (FMVA) Essentials lessons</li><li>One to one assistance from Financial Modelling &amp; Valuation Analyst (FMVA) Essentials professionals if you need it</li><li>Innovative exams to test your knowledge after the Financial Modelling &amp; Valuation Analyst (FMVA) Essentials course</li><li>24/7 customer support should you encounter any hiccups</li><li>Top-class learning portal</li><li>Unlimited lifetime access to all forty Financial Modelling &amp; Valuation Analyst (FMVA) Essentials courses</li><li>Digital Certificate, Transcript and student ID are all included in the price</li><li>PDF certificate immediately after passing</li><li>Original copies of your Financial Modelling &amp; Valuation Analyst (FMVA) Essentials certificate and transcript on the next working day</li><li>Easily learn the Financial Modelling &amp; Valuation Analyst (FMVA) Essentials skills and knowledge you want from the comfort of your home</li></ul> <p>The <strong>Financial Modelling &amp; Valuation Analyst (FMVA) Essentials</strong> course has been prepared by focusing largely on Financial Modelling &amp; Valuation Analyst (FMVA) Essentials career readiness. It has been designed by our Financial Modelling &amp; Valuation Analyst (FMVA) Essentials specialists in a manner that you will be likely to find yourself head and shoulders above the others. For better learning, one to one assistance will also be provided if it's required by any learners.<br /><br />The <strong>Financial Modelling &amp; Valuation Analyst (FMVA) Essentials</strong> Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Financial Modelling &amp; Valuation Analyst (FMVA) Essentials bundle course has been created with forty premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field.<br /><br />This <strong>Financial Modelling &amp; Valuation Analyst (FMVA) Essentials</strong> Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Financial Modelling &amp; Valuation Analyst (FMVA) Essentials Elementary modules, allowing our students to grasp each lesson quickly.</p><p>The Financial Modelling &amp; Valuation Analyst (FMVA) Essentials course is self-paced and can be taken from the comfort of your home, office, or on the go! With our Student ID card you will get discounts on things like music, food, travel and clothes etc.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        400 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 <strong>Financial Modelling &amp; Valuation Analyst (FMVA) Essentials </strong>training is suitable for -</p><ul><li>Students</li><li>Recent graduates</li><li>Job Seekers</li><li>Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Financial Modelling &amp; Valuation Analyst (FMVA) Essentials.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To participate in this <strong>Financial Modelling &amp; Valuation Analyst (FMVA) Essentials </strong>course, all you need is -</p><ul><li>A smart device</li><li>A secure internet connection</li><li>And a keen interest in Financial Modelling &amp; Valuation Analyst (FMVA) Essentials.</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>You will be able to kickstart your <strong>Financial Modelling &amp; Valuation Analyst (FMVA) Essentials </strong>career because this course includes various courses as a bonus. This bundle is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Financial Modelling &amp; Valuation Analyst (FMVA) Essentials career opportunities.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><ul><li>CPD Accredited e-Certificate - Free</li><li>CPD Accredited Hardcopy Certificate - Free</li><li>Enrolment Letter - Free</li><li>Student ID Card - Free</li></ul></div>
        <h4>Quality Licence Scheme Endorsed Certificate of Achievement</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>Upon successful completion of the course, you will be eligible to order QLS Endorsed Hardcopy Certificate titled 'Financial Modelling at QLS Level 3'</p><p><br />Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses.</p></div>

                        </div>

Financial Modelling & Analysis

Finance Cert & Exam Prep

Financial Modelling

Corporate Finance Level 1

Financial Engineering

Finance For Non Finance Managers

Financial Modelling & Valuation Analyst (FMVA) Essentials - CPD Certified

<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 <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau</strong>bundle! This carefully curated collection of 20 premium courses 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;">This Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau is a dynamic package that blends 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;"> Data Analysis </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 Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau package, you will receive complimentary PDF certificates for all courses in <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis</strong> bundle at no extra cost. Equip yourself with the Data Analysis bundle to confidently navigate your career path or personal development journey. Enrol our <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis bundle today</strong> 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 </strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis </strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Bundle Comprises the Following 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 1: </strong>Data Analytics</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 2: </strong>Diploma in Data Analytics with Tableau</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 3: </strong>Google Data Studio: Data Analytics</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 4: </strong>Business Intelligence Analyst</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 5: </strong>Diploma in Business Analysis</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 6: </strong>Data Science &amp; Machine Learning with Python</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 7: </strong>Spatial Data Visualization and Machine Learning in Python</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course 8: </strong>Python Programming: 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 9: </strong>SQL For Data Analytics &amp; Database Development</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>Easy to Advanced Data Structures</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>R Programming for Data Science</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>Data Center Training Essentials: General Introduction</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>Data Analysis In Excel</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>Data Protection</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>Microsoft Excel Complete Course </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>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 17: </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 18: </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 19: </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 20: </strong>Ace Your Presentations: Public Speaking Masterclass</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;">Learning Outcome:</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">By completing the Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau course, you will:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Gain comprehensive insights into multiple fields.</li><li fr-original-style="" style="box-sizing: border-box;">Foster critical thinking and problem-solving skills across various disciplines.</li><li fr-original-style="" style="box-sizing: border-box;">Understand industry trends and best practices through the<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"> Data Analysis</strong> Bundle.</li><li fr-original-style="" style="box-sizing: border-box;">Develop practical skills applicable to real-world situations.</li><li fr-original-style="" style="box-sizing: border-box;">Enhance personal and professional growth with the<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"> Data Analysis </strong>Bundle<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">.</strong></li><li fr-original-style="" style="box-sizing: border-box;">Build a strong knowledge base in your chosen course via the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis </strong>Bundle.</li><li fr-original-style="" style="box-sizing: border-box;">Benefit from the flexibility and convenience of online learning.</li><li fr-original-style="" style="box-sizing: border-box;">With the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis</strong> package, validate your learning with a CPD certificate.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Each course in Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau 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 Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau, a rich anthology of 15 diverse courses. Each course in the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis</strong> bundle is handpicked by our experts to ensure a wide spectrum of learning opportunities. ThisData Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau 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 Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau bundle offers you the flexibility and convenience to learn at your own pace. Make the Data Analysis 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;">
                                        200 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;">Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau</strong> bundle is perfect for:</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;">Data Enthusiasts:</strong> Keen to master data analysis tools like Python, Tableau, and Excel.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Aspiring Business Analysts:</strong> Eager to derive actionable insights using data analysis techniques.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">IT Professionals: </strong>Broadening skills with data analysis, machine learning, and business intelligence.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Career Changers: </strong>Seeking a solid foundation in data analysis for a professional pivot.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Leadership Aspirants: </strong>Complementing data analysis expertise with leadership and presentation skills.</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;">Without any formal requirements, you can delightfully enrol in this <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analysis, Business Intelligence, Business Analysis with Python &amp; Tableau</strong> course.</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;">Our bundle will prepare you for a range of careers, including:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Data Analyst</li><li fr-original-style="" style="box-sizing: border-box;">Business Intelligence Analyst</li><li fr-original-style="" style="box-sizing: border-box;">Data Scientist</li><li fr-original-style="" style="box-sizing: border-box;">Python Developer</li><li fr-original-style="" style="box-sizing: border-box;">SQL Database Developer</li><li fr-original-style="" style="box-sizing: border-box;">Business Analyst</li><li fr-original-style="" style="box-sizing: border-box;">Data Protection Officer</li></ul>
                        </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;">Certificate Of Completion</h4>
        <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">
            Digital certificate -
            Included
        </p>
        <h4 fr-original-style="" style="box-sizing: border-box;">Certificate Of Completion</h4>
        <p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">
            Hard copy 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;">You will get a complimentary Hard Copy Certificate.</p></div>

                        </div>

NextGen Learning

Business Analytics & Intelligence

Big Data Analytics

Data Science

Data Skills

Data Analyst

Business Data Analysis

Data Analysis, Business Intelligence, Business Analysis with Python & Tableau - 20 Courses Bundle

Loughborough

<div>
		

		<div>
			
			<p>In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.</p>
			<div><i></i> 120 minutes</div>
			<div><i></i>  £50.00 incl. VAT</div>
			
			
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			<p>Want to run this event in-house?  Enquire about running this event in-house </p>
			
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		<h3>Description</h3>
		<p></p><p>In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider-it is a truly disruptive force, one that promises to deliver an entirely new level of results for all aspects of the business. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI.</p>
<p>Despite its promises, AI can seem like a daunting concept for business professionals. How can you hope to apply AI to your own business if you can't see beyond the vague buzzwords and hype? That's why this course was created: to give you the essential knowledge of AI you'll need to steer the business forward.</p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is primarily designed for managers, business leaders, and other decision-makers who are interested in growing the business by leveraging the power of AI. Other individuals who wish to explore basic AI concepts are also candidates for this course.</p>
<p></p>
	
		<h3>Prerequisites</h3>
		<p></p><p>To ensure your success in this course, you should have foundational knowledge of business processes and general concepts. You should also have at least a basic understanding of information technology resources and systems, including networks, computers, and other electronic devices used in the enterprise.</p>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4><span><strong>Lesson 1: AI Fundamentals</strong></span></h4>
<p>Topic A: AI Concepts<br />Topic B: Approaches to Machine Learning and Deep Learning</p>
<h4><span><strong>Lesson 2: AI Implementations</strong></span></h4>
<p>Topic A: Data Science<br />Topic B: Search Engines</p>
<h4><span><strong>Lesson 2: AI Implementations (cont.)</strong></span></h4>
<p>Topic C: Natural Language Processing<br />Topic D: Computer Vision<br />Topic E: Robotics</p>
<h4><span><strong>Lesson 4: The Impact of AI</strong></span></h4>
<p>Topic A: Benefits of AI<br />Topic B: Challenges of AI<br />Topic C: Business Use Cases for AI</p>
<p></p>

Mpi Learning - Professional Learning And Development Provider

Online Course Marketing

Generative AI

Business Information Technology

Microsoft AI-900

AI (Artificial Intelligence)

In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.

AI For Leaders

<p>Become a python programmer now at a minimal cost with endorsed certification. The Python course is endorsed by QLS with extra courses in a bundle.</p><p>It doesn't matter if you are a Python programmer or not, a data scientist or not, or even if you can write code or not. This course will guide you through all the necessary topics that are required to become a successful python programmer.</p><p>In today's world maybe you are seeing our courses in spite of the Artificial Intelligence existence and Python is the language that made it easier to write code for Machine Learning, Artificial Intelligence or Neural Networks. In the field of data science python is the tool mostly used.</p><p>If you look into our course contents, it's designed to walk you through basic to advanced topics. Topics that are required to become a python programmer to data science beginning stage. It's not over yet. There is some career guidance also for your future career path.</p><p>We're not leaving you after the guidance also. We'll be providing you with an assessment system that can assist you to judge your python skills.</p><p>Last but not least, the QLS (The Quality Endorsed Scheme) endorsed certificate will be awarded upon successful completion.</p><p>We're welcoming you to take our courses and experience our interactive quizzes, adaptive teaching videos, and personalised learning plans that make us different from other platforms.</p><p>Enrol now today.</p><p>This bundle package includes:</p><ul><li>Python Programming: Beginner To Expert - with endorsed certificate</li><li>5 additional CPD accredited courses -<br /><ol><li>Easy to Advanced Data Structures</li><li>Mastering SQL Programming</li><li>Java Programming: Beginners to Advanced</li><li>SAS Programming Basic to Advanced</li><li>Getting Started with Julia Programming</li></ol></li></ul><p><strong>Why People Enrol This Course from One Education:</strong></p><ul><li>Receive an Quality Licence Scheme-endorsed certificate upon successful completion</li><li>5 additional CPD accredited courses to enrich your knowledge and skills</li><li>Learning materials of our course contains engaging voiceover and visual elements for your comfort</li><li>Get 24/7 access to all course content for a full year</li><li>Complete the course at your own pace</li><li>Each of our students gets full tutor support on weekdays (Monday to Friday)</li><li>Efficient assessments and instant results upon completion of our course</li></ul><p>In this Python course journey will start from the very basics where you'll get the initial knowledge about python and its run time environments. After mastering the basic ideas our course will move on to the data types, iterations, conditional statements, basic data structures and algorithms and their understandings as well. Meanwhile, you're growing your capability to the next level and the course will pivot you to some advanced topics such as sets, tuples lists etc. This you'll recognise some advanced data structures, algorithms and Object Oriented concepts as well. And yes, a clear explanation will be the finishing touch. These data structures are often used in the field of Data Science, Artificial Intelligence and Machine Learning.</p><p>The course will end after providing you with some career suggestions. Please consider the below listings as our course contents and extra courses.</p><p><strong>Course Curriculum:</strong></p><p>Here is a curriculum breakdown of the Python Programming: Beginner To Expert:</p><p><strong>Module 01: Introduction to Python Programming from A-Z</strong></p><ul><li>Intro To Python Section Overview</li><li>What is Python Programming</li><li>Who is This Course For</li></ul><p><strong>Module 02: Getting Familiar with Python</strong></p><ul><li>Getting Familiar with Python Section Overview</li><li>Installing on Windows</li><li>Anaconda and Jupyter Notebooks Part 1</li><li>Anaconda and Jupyter Notebooks Part 2</li><li>Comments</li><li>Line Structure</li><li>Line Structure Exercise</li><li>Joining Lines</li><li>Multiple Statements on a Single Line</li><li>Indentation</li></ul><p><strong>Module 03: Basic Data Types</strong></p><ul><li>Basic Data Types Section Overview</li><li>String Overview</li><li>String Manipulation</li><li>String Indexing</li><li>String Slicing</li><li>Printing</li><li>Integers and Floats</li><li>Booleans</li><li>Mini Project 1 : Letter Counter</li></ul><p><strong>Module 04: Python Operators</strong></p><ul><li>Comparison Operators</li><li>Arithmetic Operators</li><li>Assignment Operators</li><li>Logical Operators</li><li>Identity Operators</li><li>Membership Operators</li><li>Bitwise Operators</li></ul><p><strong>Module 05: Advanced Data Types</strong></p><ul><li>Advanced Data Types Section Overview</li><li>Sets</li><li>List Overview</li><li>List Slicing and Indexing</li><li>Tuples</li><li>Dictionaries</li><li>When to use each one?</li><li>Compound Data Types</li></ul><p><strong>Module 06: Control Flow Part 1</strong></p><ul><li>Control Flow Part 1 Section Overview</li><li>Intro to Control Flow</li><li>Basic Conditional Statements</li><li>More Conditional Statements</li><li>For Loops</li><li>While Loops</li></ul><p><strong>Module 07: Control Flow Part 2</strong></p><ul><li>Control Flow Part 2 Section Overview</li><li>Break Statements</li><li>Continue Statements</li><li>Zip Function</li><li>Enumerate Function</li><li>List Comprehension</li></ul><p><strong>Module 08: Python Functions</strong></p><ul><li>Functions Section Overview</li><li>Intro to Functions</li><li>Defining Functions</li><li>Variable Scope</li><li>Doc Strings</li></ul><p><strong>Module 09: User Input and Error Handling</strong></p><ul><li>User Input and Error Handling Section Overview</li><li>Introduction to error handling</li><li>User Input</li><li>Syntax Errors</li><li>Exceptions</li><li>Handling Exceptions Part 1</li><li>Handling Exceptions Part 2</li></ul><p><strong>Module 10: Python Advanced Functions</strong></p><ul><li>Advanced Functions Section Overview</li><li>Lambda Functions</li><li>Functions args and kwargs</li><li>Iterators</li><li>Generators and Yield</li><li>Map Function</li><li>Filter Function</li></ul><p><strong>Module 11: Python Scripting and Libraries</strong></p><ul><li>Scripting and Libraries Section Overview</li><li>What is a script</li><li>What is an IDE</li><li>What is a text editor?</li><li>From Jupyter Notebook to VScode Part 1</li><li>From Jupyter Notebook to VScode Part 2</li><li>Importing Scripts</li><li>Standard Libraries</li><li>Third Party Libraries</li></ul><p><strong>Module 12: NumPy</strong></p><ul><li>NumPy Section Overview</li><li>Intro to NumPy</li><li>Why use NumPy?</li><li>NumPy Arrays</li><li>Reshaping, Accessing, and Modifying</li><li>Slicing and Copying</li><li>Inserting, Appending, and Deleting</li><li>Array Logical Indexing</li><li>Broadcasting</li></ul><p><strong>Module 13: Pandas</strong></p><ul><li>Intro to Pandas</li><li>Pandas Series</li><li>Pandas Series Manipulation</li><li>Pandas DataFrame</li><li>Pandas DataFrame Manipulation</li><li>Dealing with Missing Values</li></ul><p><strong>Module 14: Introduction to OOP</strong></p><ul><li>Functional vs OOP</li><li>OOP Key Definitions</li><li>Create your First Class</li><li>How to Create and Use Objects</li><li>How to Modify Attributes</li></ul><p><strong>Module 15: Advanced OOP</strong></p><ul><li>Decorators</li><li>Property Decorator</li><li>Class Method Decorator</li><li>Static Methods</li><li>Inheritance from A to Z</li></ul><p><strong>Module 16: Starting a Career in Python</strong></p><ul><li>Career Section Overview</li><li>Getting Started with Freelancing</li><li>Building A Brand</li><li>Personal Branding</li><li>Importance of Having Website/Blog</li><li>Do's and Don'ts of Networking</li><li>Top Freelance Websites</li><li>Creating A Developer Resume</li></ul><p><strong>Certificate of Achievement</strong></p><p><strong>Endorsed Certificate of Achievement from the Quality Licence Scheme</strong></p><p>After successfully completing the course, learners will get an endorsed certificate (included with the course) delivered right at their doorstep by post, without paying a single penny! Note that learners residing outside the UK have to pay a £10 postage charge.</p><p><strong>For Additional Courses</strong></p><p>For the additional Quality Licence Scheme endorsed certificates from the additional courses, you have to pay the fees based on the level of each course:</p><ul><li>No Level- £29</li><li>Level 1 - £29</li><li>Level 2 - £59</li><li>Level 3 - £69</li><li>Level 4 - £79</li><li>Level 5 - £99</li><li>Level 6 - £109</li><li>Level 7 - £119</li></ul><p><strong>CPD Accredited Certification from One Education</strong></p><p>After successfully completing the courses under this course, you will also qualify for CPD Accredited Certificates for each of the courses. Certification is available in PDF format, at the cost of £9, or a hard copy can be sent to you via post at £15.</p><h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                            <ul><li>Just want to start a programming career</li><li>Working with data science but wants to start a journey in python programming</li><li>Individuals who wants to build their career in the python programming industry</li><li>Individuals from any age and any occupations</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>There are no formal entry requirements for the course, with enrollment open to anyone!<strong> Anyone and everyone</strong> with a knack for learning can enrol this course without any hesitation.</p><p>Learn online from any internet device, including your computer, tablet or smartphone. Study when it suits you and complete the course at your own pace.</p><p>All students must have a passion for learning and literacy, as well as being over the age of 16.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Python is among the most famous programming languages. Widely used in different fields of the IT industry. Data science, AI, and ML are putting their footprint in every sector. So, individuals who are capable of python would be standing straight in front of these huge opportunities.</p>
                        </div>

One Education

Python Level 7 QLS Endorsed Course

<p><strong>*** Data Analyst Training ***</strong></p><p>Approximately <strong>3.5 million jobs</strong> are there for professionals with Data Analyst skills. Understanding, harnessing, and using data in business is no longer just a competence for a few groups of highly compensated analysts. Data analysis is increasingly becoming a requirement for many occupations. You can obtain a strong foundation in data analysis and get your foot in the growing data world with this outstanding value, six-course Data Analyst Training bundle.</p><p>You will learn the fundamentals of data analysis from the Data Analyst Training bundle, which also covers process management concepts, numerous tools &amp; techniques for data analysis, dealing with variations tactics, and chart interpretation. Additionally, you will comprehensively understand how to use Excel to analyse and visualise data. This Data Analyst Training course teaches you how to make pivot tables, maps, and forecasting data. You will also learn about Microsoft Power BI.</p><p>Our intention is to give you thorough preparation. This <strong>Data Analyst Training bundle</strong> will prepare you to work as a data analyst. Each of the data analysis topics builds upon the one before it. And this is exactly why our Training is so beneficial. We promise that everything is presented in the proper sequence and that you won't get lost along the way.</p><p><strong>So why wait? Every day is a missed opportunity.</strong></p><p><strong>Enrol Data Analysis today and enjoy a smooth learning experience.</strong></p><p><strong>Learning Outcome of Data Analyst Training bundle</strong></p><ul><li>Get introduced yourself to how to analyse data</li><li>Know more about how to structure data analysis and forecast them</li><li>Become fully aware of how to use Google data studio and Microsoft azure machine learning</li><li>Gain the ability to use JavaScript</li><li>Learn to protect your data by using a Data protection practitioner and Clinical Data Analysis</li><li>Acquire knowledge of Machine Learning and how to use them with Python</li><li>Get <strong>Data Analyst Training</strong> from the experts</li><li>Understand the basics of data science and visualisation so that you can apply them frequently</li></ul><p><strong>Key Features &amp; Benefits:</strong></p><ul><li>Quality Licence Scheme (QLS) endorsed</li><li>CPD Accredited</li><li>Lifetime Access &amp; 24/7 Support on weekdays (Monday to Friday)</li><li>Self-paced course modules</li><li>Course materials feature captivating voice-overs and visuals</li></ul><p><strong>Why Quality Licence Scheme (QLS)?</strong></p><ul><li>Achieving <strong>Quality Licence Scheme</strong> endorsed certificates can provide you with valued and credible evidence of <strong>your skills and knowledge to potential employers.</strong></li><li>Quality Licence Scheme (QLS) endorsements are awarded to training programmes and courses that <strong>meet high quality standards</strong>, ensuring that your certificate represents <strong>a valuable achievement.</strong></li><li>The stringent assessment process involved in achieving Quality Licence Scheme Endorsed Certificates ensures that you have acquired the <strong>necessary skills and knowledge to excel in your chosen field.</strong></li></ul><p>With our Data Analyst (Data Analytics) bundle course, you can gain a solid foundation in data analysis and get your foot in the thriving data world.</p><ol><li>Diploma in Data Analysis Fundamentals <strong>( QLS Level 5 Endorsed )</strong></li><li>Business Data Analysis</li><li>Data Analysis In Excel <strong>( QLS Level 5 Endorsed )</strong></li><li>Diploma in Data Analytics with Tableau <strong>( QLS Level 6 Endorsed )</strong></li><li>Data Protection</li><li>Microsoft Power BI - Master Power BI in 90 Minutes!</li></ol><p>Data Analyst (Data Analytics) bundle course will educate you on the basics of data analysis, including process management principles, various tools &amp; techniques for data analysis, the strategies to deal with variations, and the interpretation of charts. Along with that, you will also gain a clear idea of analysing and visualising data using excel. This Data Analyst course will teach you how to create pivot tables, map and forecasting data.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        150 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 Data Analyst (Data Analytics) Training is ideal for highly motivated individuals who want to enhance their professional skills and train for the job they want!</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>There are no formal entry requirements for the Data Analyst Training, with enrollment open to anyone!</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Data Analyst Training Bundle is ideal for anyone who wants to take their career development to the next level and fast-track their career in any of the following roles:</p><ul><li>Data analytics manager</li><li>Financial analyst</li><li>Marketing analyst</li><li>Systems analyst</li><li>Data scientist</li><li>Machine learning engineer</li><li>Data analytics consultant</li></ul><p>In the UK, these professions' pay scale ranges from <strong>£45,000 to £120,000 </strong>per year.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            £9
        </p>
            <div> <p><strong>CPD Accredited Certification from One Education</strong></p><p>Once you have finished the bundle, you will be eligible to apply for CPD QS-accredited certificates. Certification is available in both PDF &amp; hardcopy format, which can be received by paying -</p><ul><li><strong>PDF Certificate: £9</strong></li><li><strong>Hardcopy Certificate (within the UK): £15</strong></li><li><strong>Hardcopy Certificate (international): £15 + £10 (postal charge) = £25</strong></li></ul> </div>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            £109
        </p>
            <div> <p><strong>Endorsed Certificate of Achievement from the Quality Licence Scheme</strong></p><p>After successfully completing the following courses under the bundle, learners will be able to order endorsed certificates as proof of their achievement:</p><ul><li><strong>Diploma in Data Analyst Fundamentals (within the UK: £109, International: £119)</strong></li><li><strong>Data Analyst In Excel (within the UK: £109, International: £119)</strong></li><li><strong>Diploma in Data Analytics with Tableau (within the UK: £119, International: £129</strong></li></ul> </div>

                        </div>

Data Analyst (Data Analytics) Course

<p><em><strong>48-Hour Knowledge Knockdown! Prices Reduced Like Never Before!</strong></em></p><p>Unlock the power of Data Analyst (Data Analytics) with our cutting-edge Data Analyst (Data Analytics) course and transform raw information into strategic insights of Data Analyst (Data Analytics) that drive success.</p><p>Get <strong>Free</strong> 1 QLS Endorsed Course <strong>with Certificate</strong> &amp; 10 Additional CPD Accredited Courses In A Single Payment.</p><p><strong>This Data Analyst (Data Analytics) Bundle Package includes:</strong></p><ul><li><strong>Course 01:</strong> Diploma in Data Analysis <strong>at QLS Level 5</strong></li></ul><p><strong>10 Additional CPD Accredited Premium Courses related to Data Analyst (Data Analytics) -</strong></p><ul><li><strong>Course 01:</strong> Data Analytics with Tableau</li><li><strong>Course 02:</strong> Data Science &amp; Machine Learning with R</li><li><strong>Course 03:</strong> Excel Pivot table for Data analytics</li><li><strong>Course 04</strong>: JavaScript Functions for Data Analyst</li><li><strong>Course 05:</strong> Data analytics with Excel</li><li><strong>Course 06:</strong> Mastering SQL Programming for Data Analyst</li><li><strong>Course 07:</strong> Google Data Studio</li><li><strong>Course 08:</strong> Business Intelligence and Data Mining for Data Analyst</li><li><strong>Course 09:</strong> GDPR Training</li><li><strong>Course 10:</strong> Learn Programming with Python</li></ul><p><strong>Learning outcome of this Data Analyst (Data Analytics) Bundle:</strong></p><ul><li>Apply data analyst techniques to modify worksheets effectively.</li><li>Utilise data analyst strategies for working with lists.</li><li>Demonstrate proficiency in analyzing data as a data analyst.</li><li>Visualize data using charts as a data analyst.</li><li>Employ PivotTables and Pivot Charts for complex Data Analyst</li><li>Manage multiple worksheets and workbooks efficiently as a data analyst.</li><li>Use lookup functions and formula auditing for accurate Data Analyst</li></ul> <p><strong>Why Prefer This Data Analyst (Data Analytics) Bundle?</strong></p><ul><li>FREE certificate on Data Analyst (Data Analytics)accredited by <strong>CPDQS</strong></li><li>Get instant access to this Data Analyst (Data Analytics) course.</li><li>Learn Data Analyst (Data Analytics) from anywhere in the world</li><li>Data Analyst (Data Analytics) is affordable and simple to understand</li><li>Data Analyst (Data Analytics) is an entirely online, interactive lesson with voiceover audio</li><li>Lifetime access to the Data Analyst (Data Analytics) bundle materials</li><li>Data Analyst (Data Analytics) comes with 24/7 tutor support</li><li>Free assessments available with Data Analyst (Data Analytics)</li><li>Get a <strong>free student ID card!</strong> with Data Analyst (Data Analytics)</li></ul><p><strong>Assessment Process of Data Analyst (Data Analytics) Course:</strong></p><p>You have to complete the assignment questions given at the end of the Data Analyst (Data Analytics) course and score a minimum of 60% to pass each exam, after that you can claim your certificate</p> <h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                            <p>This course is for whoever wishes to gain a better understanding of Data Analyst (Data Analytics)</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise to take this Data Analyst (Data Analytics)</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst</li><li>Retail Data Analyst</li><li>Statistical Data Analyst</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited e-Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Diploma in Data Analysis at QLS Level 5</h4>
        <p>
            Hard copy certificate -
            Included
        </p>

                        </div>

Academy for Health and Fitness

Data Analyst (Data Analytics) Endorsed Diploma

<strong>Learn to apply sentiment analysis to your problems through a practical, real-world use case.</strong>
        <p>Do you want to learn how to perform sentiment analysis? The answer should almost always be yes if you are working in any business domain. Every company on the face of the earth wants to know what its customers feel about its products and services - and sentiment analysis is the easiest and most accurate way of finding out the answer to this question.

By learning to perform sentiment analysis, you will make yourself invaluable to any company, especially those who are interested in quality assurance of their products and those working with business intelligence; and this is almost all sensible companies, large and small, nowadays.

In this course, we make it easy to perform sentiment analysis. In the very first video, we introduce a sentiment analysis engine of fewer than 60 lines that can perform industry-grade sentiment analysis. We then spend the rest of the course explaining these very powerful 60 lines so that you have a thorough understanding of the code. After you are done with this course, you will immediately be able to plug this system into your existing pipelines to perform sentiment analysis of any text you can throw at it.

That is one of the reasons you should use Python for sentiment analysis and not some other data science language such as R. If you work with R for sentiment analysis, you still have to put in a lot of effort to take this skill to the market. If you write your sentiment analysis engine in Python, incorporating your code into your final business product is dead easy.

The second important tip for sentiment analysis is that the latest success stories do not try to do it by hand. Instead, you train a machine to do it for you. That is why we use deep sentiment analysis in this course: you will train a deep-learning model to do sentiment analysis for you. That way, you put in very little effort and get industry-standard sentiment analysis - and you can improve your engine later by simply utilizing a better model as soon as it becomes available with little effort.

All the code files are placed at
https://github.com/PacktPublishing/Sentiment-Analysis-through-Deep-Learning-with-Keras-and-Python</p>
        <h2>What You Will Learn</h2><p>Understanding how to write industry-grade sentiment analysis engines with very little effort<br>Basics of machine learning with minimal math<br>Understand not only the theoretical and academic aspects of sentiment analysis but also how to use it in your field - real-world sentiment analysis<br>Tips on avoiding mistakes made by new-comers to the field and the best practices to get you to your goal with minimal effort</p>
        <h2>Audience</h2><p>Anyone who wants to perform sentiment analysis in the real world<br>Anyone who wants to understand how deep learning can help with sentiment analysis<br>Anyone who is working for a company that wants to see how its products are doing with their customers</p>
        <h2>Approach</h2><p>This course is designed with the step-by-step approach and covers industry-grade sentiment analysis engines topics and best practices to get you to your goal with minimal effort.</p>
        <h2>Key Features</h2><p>You will learn to perform deep sentiment analysis the easy way * You will use Python to perform sentiment analysis * Using Python will allow you to integrate sentiment analysis in your existing solutions</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/sentiment-analysis-through-deep-learning-with-keras-and-python</p>
        <h2>About the Author</h2><h3>Mohammad Nauman</h3><p>Dr. Mohammad Nauman has a PhD in computer science and a PostDoc from the Max Planck Institute for software systems. He has been programming since early 2000 and has worked with many different languages, tools, and platforms. He holds extensive research experience with many state-of-the-art models. His research in Android security has led to some major shifts in the Android permission model.

He loves teaching and the most important reason he teaches online is to make sure that maximum people can learn through his content. Hope you have fun learning with him!</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><br><h4>2. Bare Essentials of Theory</h4><p></p><br><h4>3. Getting Started with Keras</h4><p></p><br><h4>4. Sentiment Analysis Case Study</h4><p></p><br><h4>5. Convolutional Neural Networks with Keras</h4><p></p><br><h4>6. Revisiting the Sentiment Analysis Model</h4><p></p><br><h4>7. Finishing Up</h4><p></p>

Packt

Keras

Python

Deep Learning

Learn to apply sentiment analysis to your problems through a practical, real-world use case.

Sentiment Analysis through Deep Learning with Keras and Python

<p><strong> 24-Hour Knowledge Knockdown! Prices Reduced Like Never Before </strong></p><p>Did you know that the UK manufacturing sector relies heavily on Computer Numerical Control (CNC) programming, with over <strong>2 million</strong> CNC machines in operation? Yet, skilled CNC programmers are in high demand. Are you ready to join this vital industry and shape the future of manufacturing with code?</p><p>This <strong>CNC (Computer Numerical Control) Programming</strong> Bundle aims to teach students the intricacies of CNC programming and enhance their software and coding skills across various languages and platforms, preparing professionals for the surge in manufacturing automation in the UK. The amalgamation of programming languages such as C++, C#, Python, and JavaScript with CNC programming creates a formidable toolset that addresses both the creative and analytical aspects of technological manufacturing and design.</p><p>With our CNC (Computer Numerical Control) Programming exclusive bundle, you will get<strong> a PDF &amp; Hardcopy Certificate, PDF Transcript and Digital Student ID Card (worth £120) Absolutely FREE. </strong></p><p><strong>Courses are Included in This CNC (Computer Numerical Control) Programming Bundle:</strong></p><ul><li><strong> Course 01: </strong>CNC Programming</li><li><strong> Course 02: </strong>C++ Programming for Absolute Beginners</li><li><strong> Course 03: </strong>JavaScript Foundations for Everyone</li><li><strong> Course 04: </strong>Python Programming for Everybody</li><li><strong> Course 05: </strong>Basic C# Coding</li><li><strong> Course 06: </strong>Introduction to Coding with HTML, CSS, &amp; Bootstrap</li><li><strong> Course 07: </strong>Kotlin Programming: Android Coding</li><li><strong> Course 08: </strong>SQL Programming Masterclass</li><li><strong> Course 09: </strong>Master JavaScript with Data Visualization</li><li><strong> Course 10: </strong>Machine Learning with Python</li><li><strong> Course 11: </strong>Solidworks Foundation Training</li><li><strong> Course 12: </strong>CAD Design Course: Assemblies, Modelling And Civil Drawings</li><li><strong> Course 13: </strong>AutoCAD VBA Programming</li><li><strong> Course 14: </strong>Cyber Security Awareness Training</li><li><strong> Course 15: </strong>Cloud Computing / CompTIA Cloud+ (CV0-002)</li><li><strong> Course 16: </strong>CompTIA PenTest+ (Ethical Hacking)</li><li><strong> Course 17: </strong>Industry 4.0 - Automation &amp; Applications</li><li><strong> Course 18: </strong>AutoCAD Programming using C# with Windows Forms</li></ul><p><strong>So enrol now in this CNC (Computer Numerical Control) Programming Today to advance your career!</strong></p><p><strong>Learning Outcomes of CNC (Computer Numerical Control) Programming Bundle:</strong></p><ul><li>Master CNC programming to enhance precision in automated manufacturing processes.</li><li>Develop advanced C++ coding skills for complex problem-solving in technical environments.</li><li>Acquire a solid foundation in JavaScript essential for web-based CNC control interfaces.</li><li>Gain proficiency in Python for automation and scripting within CNC operational frameworks.</li><li>Learn the essentials of HTML, CSS, &amp; Javascript for crafting intuitive CNC machine interfaces.</li><li>Understand SQL database management to maintain robust CNC operational data records.</li></ul><p><strong>Why Choose Our CNC (Computer Numerical Control) Programming Bundle?</strong></p><ul><li><strong>FREE </strong>CNC (Computer Numerical Control) Programming <strong>certificate</strong></li><li>Get a <strong>free student ID card </strong>with CNC (Computer Numerical Control) Programming Training</li><li>Get instant access to this CNC (Computer Numerical Control) Programming course.</li><li>Learn CNC (Computer Numerical Control) Programming from anywhere in the world</li><li>The CNC (Computer Numerical Control) Programming is affordable and simple to understand</li><li>The CNC (Computer Numerical Control) Programming is an entirely online, interactive lesson with voiceover audio</li><li><strong>Lifetime access</strong> to the CNC (Computer Numerical Control) Programming course materials</li><li>The CNC (Computer Numerical Control) Programming comes with 24/7 tutor support</li></ul> <p>Start your learning journey straightaway!</p><p><strong>*** Course Curriculum ***</strong></p><p><strong> Course 01: CNC Programming</strong></p><ul><li>Module 1: Scope of the Course </li><li>Module 2: Numerical Control of Machine Tools</li><li>Module 3: CNC- Computer Numerical Control Syst</li><li>Module 4: Components of CNCs</li><li>Module 5: Point to Point CNC Machines</li><li>Module 6: Incremental &amp; Absolute CNC Machines</li><li>Module 7: Open &amp; Close Control Loop CNC Machines</li><li>Module 8: 2 &amp;3 Axes CNC Machines</li><li>Module 9: Importance of Higher axes Machining</li><li>Module 10: Programming Format</li><li>Module 11: Cartesian Coordinate System</li><li>Module 12: How to Write a Program</li><li>Module 13: Basic CNC Programming (Absolute Mode)</li><li>Module 14: Basic CNC Programming (Incremental)</li><li>Module 15: A Simple Coding Exercise</li><li>Module 16: Applications of CNC</li></ul><p><strong> Course 02: C++ Programming for Absolute Beginners</strong></p><ul><li>Section 01: Getting Started With C++</li><li>Section 02: Setting Up Local Development</li><li>Section 03: C++ Basics</li><li>Section 04: C++ Data Types</li><li>Section 05: C++ Operators</li><li>Section 06: C++ Strings</li><li>Section 07: C++ Decision Making</li><li>Section 08: C++ Control Flow Loops</li><li>Section 09: C++ Arrays</li><li>Section 10: C++ Functions</li></ul><p><strong> Course 03: JavaScript Foundations for Everyone</strong></p><ul><li>Module 01: About the Author </li><li>Module 02: Introduction to JavaScript </li><li>Module 03: Strengths and Weaknesses of JavaScript </li><li>Module 04: Writing JavaScript in Chrome </li><li>Module 05: JavaScript Variables </li><li>Module 06: Demo of JavaScript Variables </li><li>Module 07: Basic Types of JavaScript </li><li>Module 08: JavaScript Boolean </li><li>Module 09: JavaScript Strings </li><li>Module 10: JavaScript Numbers </li><li>Module 11: JavaScript Objects </li><li>Module 12: Demo of JavaScript Objects </li><li>Module 13: JavaScript Arrays </li><li>Module 14: Demo of JavaScript Arrays </li><li>Module 15: JavaScript Functions </li><li>Module 16: Demo of JavaScript Functions </li><li>Module 17: JavaScript Scope and Hoisting </li><li>Module 18: Demo of JavaScript Scope and Hoisting </li><li>Module 19: Currying Functions </li><li>Module 20: Demo of Currying Functions </li><li>Module 21: Timeouts and Callbacks </li><li>Module 22: Demo of Timeouts and Callbacks </li><li>Module 23: JavaScript Promises </li><li>Module 24: Demo of JavaScript Promises </li><li>Module 25: Demo of Javascript Async </li><li>Module 26: Flow Control </li><li>Module 27: Demo of Flow Control </li><li>Module 28: JavaScript For Loop </li><li>Module 29: Demo of JavaScript For Loop </li><li>Module 30: Demo of Switch Statements </li><li>Module 31: Error Handling </li><li>Module 32: Demo Project </li></ul><p><strong>=========&gt;&gt;&gt;&gt;&gt; And 15 More Courses &lt;&lt;&lt;&lt;&lt;=========</strong></p><p><strong>How will I get my Certificate?</strong></p><p>After successfully completing the course, you will be able to order your Certificates as proof of your achievement.</p><ul><li><strong>PDF Certificate:</strong> Free (Previously it was £12.99*18= £233)</li><li><strong>CPD Hard Copy Certificate: </strong>Free ( For The First Course: Previously it was £29.99)</li></ul> <h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                            <p>This CNC (Computer Numerical Control) Programming bundle is suitable for everyone.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise in this CNC (Computer Numerical Control) Programming bundle.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This CNC (Computer Numerical Control) Programming bundle will allow you to kickstart or take your career in the related sector to the next stage.</p><ul><li>CNC Operator</li><li>CAD Technician</li><li>Production Engineer</li><li>Data Analyst</li><li>Software Developer</li><li>Machine Learning Expert</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Digital Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><p>Upon passing the Course, you need to order a <strong>Digital Certificate</strong> for each of the courses inside this bundle as proof of your new skills that are accredited by <strong>CPD QS </strong>for Free.</p></div>
        <h4>CPD Accredited Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>If you are an <strong>international student</strong>, then you have to pay an additional <strong>10 GBP</strong> for each certificate as an international delivery charge.</p></div>

                        </div>

CNC (Computer Numerical Control) Programming

<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>

Nexus Human

Data Engineering

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

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

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 (ML)

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 & Development

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>

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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