Name: Computer Vision: C++ and OpenCV with GPU support - CPD Certified
Price: 279 GBP
Availability: InStock

<p><strong>&gt;&gt; 12-Hour Knowledge Knockdown! Prices Reduced Like Never Before &lt;&lt;</strong></p><p>In the era of big data, the demand for skilled data science professionals has skyrocketed in the UK. According to a recent report, the data science job market in the UK is expected to grow by over <strong>25% by 2026</strong>. Aside from that, Candidates with data science skills have a <strong>96% </strong>employment rate and can earn on average <strong>£40,000 per year.</strong> Our Complete Data Science bundle is about to take you on a tour starting from the beginning.</p><p><strong>This CCTV Operator Training Bundle Contains 4</strong><strong> of Our Premium Courses for One Discounted Price:</strong></p><ul><li><strong> Course 01: </strong>Complete Data Science</li><li><strong> Course 02:</strong> Data Science with Python</li><li><strong> Course 03: </strong>Information Management</li><li><strong> Course 04:</strong> GDPR Data Protection</li></ul><p>Take our Complete Data Science Bundle to learn how to maximise your potential and climb your chosen professional ladder. By participating in these popular courses, you can learn the fundamentals of Python. Discover Python data types. Loops, list comprehension, functions, lambda expressions, maps, and filters should all be taught. Learn about the numpy. Indexing, slicing, broadcasting, and boolean masking are all covered in our Complete Data Science course. Recognise arithmetic and universal functions. Discover everything there is to know about pandas. Learn how to use Python to become an expert in data analysis and visualisation.</p><p><strong>Learning Outcomes of Data Science</strong></p><ul><li>Develop a comprehensive understanding of the data science lifecycle.</li><li>Master data analysis techniques and Python programming for data manipulation.</li><li>Gain proficiency in information management and data organization strategies.</li><li>Understand data protection regulations, including GDPR, and their implications.</li><li>Learn to build robust data-driven applications and predictive models.</li><li>Enhance data visualization skills for effective communication of insights.</li></ul><p>Invest in your future by enrolling today and gain a competitive edge in the rapidly evolving field of data science.</p><p><strong>Why Choose Our Data Science </strong>b<strong>und;e?</strong></p><ul><li>Get a <strong>Free CPD Accredited Certificate</strong> upon completion of Data Science</li><li>Get a <strong>free student ID card</strong> with Data Science Training</li><li>The Data Science is affordable and simple to understand</li><li><strong>Lifetime access</strong> to the Data Science course materials</li><li>The Data Science 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: Complete Data Science</strong></p><ul><li>Welcome, Course Introduction &amp; overview, and Environment set-up</li><li>Python Essentials</li><li>Python for Data Analysis using NumPy</li><li>Python for Data Analysis using Pandas</li><li>Python for Data Visualization using matplotlib</li><li>Python for Data Visualization using Seaborn</li><li>Python for Data Visualization using pandas</li><li>Python for interactive &amp; geographical plotting using Plotly and Cufflinks</li><li>Capstone Project - Python for Data Analysis &amp; Visualization</li><li>Python for Machine Learning (ML) - scikit-learn - Linear Regression Model</li><li>Python for Machine Learning - scikit-learn - Logistic Regression Model</li><li>Python for Machine Learning - scikit-learn - K Nearest Neighbors</li><li>Python for Machine Learning - scikit-learn - Decision Tree and Random Forests</li><li>Python for Machine Learning - scikit-learn - Support Vector Machines (SVMs)</li><li>Python for Machine Learning - scikit-learn - K Means Clustering</li><li>Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA)</li><li>Recommender Systems - (Additional Topic)</li><li>Natural Language Processing (NLP) - NLTK - (Additional Topic)</li></ul><p><strong> Course 02: Data Science with Python</strong></p><ul><li>Unit 01: Introduction To Python Data Science</li><li>Unit 02: Data Cleaning Packages</li><li>Unit 03: Data Visualization Packages</li></ul><p><strong> Course 03: Information Management</strong></p><ul><li>Module 01: Introduction To Information Management</li><li>Module 02: Information Management Strategy</li><li>Module 03: Databases And Information Management</li><li>Module 04: Management Information Systems (MIS)</li><li>Module 05: Auditing Information Systems</li><li>Module 06: Ethical And Social Issues And Data Protection</li></ul><p><strong> Course 04: GDPR Data Protection</strong></p><ul><li>Module 01: Basics Of GDPR</li><li>Module 02: Principles Of GDPR</li><li>Module 03: Legal Foundation For Processing</li><li>Module 04: Rights Of Individuals</li><li>Module 05: Accountability And Governance</li><li>Module 06: Data Protection Officer</li><li>Module 07: Security Of Data</li><li>Module 08: Personal Data Breaches</li><li>Module 09: International Data Transfers After The Brexit</li><li>Module 10: Exemptions - Part One</li></ul><p>and much more...</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: Free</strong> (Previously it was £12.99*4 = £51)</li><li><strong>CPD Hard Copy Certificate: </strong><strong>£29.99 </strong>(Each)</li></ul> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        40 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 Science bundle is suitable for everyone. This bundle is ideal for:</p><ul><li>Data scientist</li><li>Data analyst-statistician</li><li>CSE Students</li><li>Interns</li><li>App Developer</li><li>Coders'</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise to enrol in this Data Science bundle.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Data Science Training bundle will allow you to kickstart or take your career in the related sector to the next stage.</p><ul><li>Data Analyst</li><li>Data Scientist</li><li>Business Analyst</li><li>Marketing Analyst</li><li>Data Engineer</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 -
            £29
        </p>
            <div><p><em>Please note that International students have to pay an additional £10 as a shipment fee.</em><em><br /></em></p></div>

                        </div>

Academy for Health and Fitness

Complete Data Science - CPD Certified

General Admission

<p><strong>24 Hour Flash Deal **25-in-1 </strong><strong>Cloud Solutions Architect Diploma </strong><strong>Mega Bundle**</strong></p><p><strong> </strong><strong>Cloud Solutions Architect Diploma </strong><strong>Enrolment Gifts  **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter **</strong></p><p>Take the initial steps toward a successful long-term career by studying the <strong>Cloud Solutions Architect Diploma</strong> package online with <strong>Studyhub </strong>through our online learning platform. The Cloud Solutions Architect Diploma bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass.</p><p>This <strong>Cloud Solutions Architect Diploma </strong>course provides complete 360-degree training on Cloud Solutions Architect Diploma. You'll get not one, not two, not three, but <strong>twenty-five </strong>Cloud Solutions Architect Diploma courses included in this course. Plus Studyhub's signature <strong>Forever Access</strong> is given as always, meaning these Cloud Solutions Architect Diploma courses are yours for as long as you want them once you enrol in this course</p><p><strong>This Cloud Solutions Architect Diploma Bundle consists the following career oriented courses:</strong></p><ul><li>Course 01: AWS Certified Solutions Architect Associate Preparation</li><li>Course 02: CompTIA Cloud+ (CV0-002)</li><li>Course 03: IT Administration and Networking</li><li>Course 04: CompTIA Network+ Certification (N10-007)</li><li>Course 05: Cyber Security Awareness Training</li><li>Course 06: Information Governance and Data Management Training</li><li>Course 07: Internet of Things (IoT)</li><li>Course 08: Data Center Training Essentials: General Introduction</li><li>Course 09: Network Security and Risk Management</li><li>Course 10: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 11: Data Science &amp; Machine Learning with R</li><li>Course 12: Python Basic Programming for Absolute Beginners</li><li>Course 13: Machine Learning Basics</li><li>Course 14: Data Analysis &amp; Forecasting</li><li>Course 15: SQL Database Management</li><li>Course 16: CompTIA Security+</li><li>Course 17: Cyber Security Advanced Training</li><li>Course 18: Data Analytics with Tableau</li><li>Course 19: Geospatial Technology, Remote Sensing and Web Mapping</li><li>Course 20: Digital Forensic Science: Unraveling Cybercrime Mysteries Course</li><li>Course 21: CompTIA PenTest+ (Ethical Hacking) course</li><li>Course 22: Microsoft Excel Complete Course 2019</li><li>Course 23: Python Data Science with Numpy, Pandas and Matplotlib</li><li>Course 24: Computer Networks Security from Scratch to Advanced</li><li>Course 25: Learn Fundamentals of WordPress</li></ul> <p>The <strong>Cloud Solutions Architect Diploma </strong>course has been prepared by focusing largely on Cloud Solutions Architect Diploma career readiness. It has been designed by our Cloud Solutions Architect Diploma 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.</p><p>The Cloud Solutions Architect Diploma Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Cloud Solutions Architect Diploma bundle course has been created with <strong>twenty-five </strong>premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field.</p><p>This Cloud Solutions Architect Diploma Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Cloud Solutions Architect Diploma Elementary modules, allowing our students to grasp each lesson quickly.</p><p>The Cloud Solutions Architect Diploma 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><p><strong>In this exclusive </strong><strong>Cloud Solutions Architect Diploma </strong><strong>bundle, you really hit the jackpot. Here's what you get:</strong></p><ul><li>Step by step Cloud Solutions Architect Diploma lessons</li><li>One to one assistance from Cloud Solutions Architect Diplomaprofessionals if you need it</li><li>Innovative exams to test your knowledge after the Cloud Solutions Architect Diplomacourse</li><li>24/7 customer support should you encounter any hiccups</li><li>Top-class learning portal</li><li>Unlimited lifetime access to all twenty-five Cloud Solutions Architect Diploma 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 Cloud Solutions Architect Diploma certificate and transcript on the next working day</li><li>Easily learn the Cloud Solutions Architect Diploma skills and knowledge you want from the comfort of your home</li></ul> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        250 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>Cloud Solutions Architect Diploma </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 Cloud Solutions Architect Diploma</li><li>Certified Cloud Professional (CCP)</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To participate in this <strong>Cloud Solutions Architect Diploma </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 Cloud Solutions Architect Diploma</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

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

Finance Cert & Exam Prep

IT Certifications

AWS Certified Developer

Cloud Architecture

AWS Certified Cloud Practitioner

AWS Certified Solutions Architect

Cloud Solutions Architect Diploma - CPD Certified

<p><strong>24 Hour Flash Deal **25-in-1 </strong><strong>Data Engineering Advanced Diploma </strong><strong>Mega Bundle**</strong></p><p><strong> </strong><strong>Data Engineering Advanced Diploma </strong><strong>Enrolment Gifts  **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter **</strong></p><p>Take the initial steps toward a successful long-term career by studying the <strong>Data Engineering Advanced Diploma</strong> package online with <strong>Studyhub </strong>through our online learning platform. The Data Engineering Advanced Diploma bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass.</p><p>This <strong>Data Engineering Advanced Diploma </strong>course provides complete 360-degree training on Data Engineering Advanced Diploma. You'll get not one, not two, not three, but <strong>twenty-five </strong>Data Engineering Advanced Diploma courses included in this course. Plus Studyhub's signature <strong>Forever Access</strong> is given as always, meaning these Data Engineering Advanced Diploma courses are yours for as long as you want them once you enrol in this course</p><p><strong>This Data Engineering Advanced Diploma Bundle consists the following career oriented courses:</strong></p><ul><li>Course 01: Data Analysis</li><li>Course 02: Data Science &amp; Machine Learning with R</li><li>Course 03: Data Analytics with Tableau</li><li>Course 04: SQL Programming</li><li>Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines</li><li>Course 06: Data Analytics</li><li>Course 07: Python Data Science with Numpy, Pandas and Matplotlib</li><li>Course 08: Google Analytics</li><li>Course 09: Business Intelligence and Data Mining</li><li>Course 10: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li>Course 11: JavaScript Functions</li><li>Course 12: Data Protection and Data Security (GDPR) Training Certification</li><li>Course 13: GDPR Training</li><li>Course 14: Diploma in Python Programming</li><li>Course 15: Data Center Training Essentials: General Introduction</li><li>Course 16: Quick Data Science Approach from Scratch</li><li>Course 17: Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>Course 18: Master JavaScript with Data Visualization</li><li>Course 19: Data Analysis and Forecasting in Excel</li><li>Course 20: AWS Certified Solutions Architect Associate Preparation</li><li>Course 21: Statistical Analysis Course</li><li>Course 22: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 23: Learn MySQL from Scratch for Data Science and Analytics</li><li>Course 24: Data Analysis &amp; Forecasting</li><li>Course 25: Data Structure</li></ul> <p>The <strong>Data Engineering Advanced Diploma </strong>course has been prepared by focusing largely on Data Engineering Advanced Diploma career readiness. It has been designed by our Data Engineering Advanced Diploma 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.</p><p>The Data Engineering Advanced Diploma Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Data Engineering Advanced Diploma bundle course has been created with <strong>twenty-five </strong>premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field.</p><p>This Data Engineering Advanced Diploma Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Data Engineering Advanced Diploma Elementary modules, allowing our students to grasp each lesson quickly.</p><p>The Data Engineering Advanced Diploma 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><p><strong>In this exclusive </strong><strong>Data Engineering Advanced Diploma </strong><strong>bundle, you really hit the jackpot. Here's what you get:</strong></p><ul><li>Step by step Data Engineering Advanced Diploma lessons</li><li>One to one assistance from Data Engineering Advanced Diplomaprofessionals if you need it</li><li>Innovative exams to test your knowledge after the Data Engineering Advanced Diplomacourse</li><li>24/7 customer support should you encounter any hiccups</li><li>Top-class learning portal</li><li>Unlimited lifetime access to all twenty-five Data Engineering Advanced Diploma 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 Engineering Advanced Diploma certificate and transcript on the next working day</li><li>Easily learn the Data Engineering Advanced Diploma skills and knowledge you want from the comfort of your home</li></ul> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        250 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 Engineering Advanced Diploma </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 Engineering Advanced Diploma</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To participate in this <strong>Data Engineering Advanced Diploma </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 Engineering Advanced Diploma</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

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

Data Engineering

Diploma in Education & Training (DET)

European Computer Driving Licence (ECDL)

Diploma in Management Studies (DMS)

Diploma in Professional Studies (DPS)

Nursing Diploma

Data Engineering Advanced Diploma - CPD Certified

Packt

Computer Vision

Python

Programming

Deep Learning

Dive into the world of image segmentation with PyTorch. From tensors to UNet and FPN architectures, grasp the theory behind convolutional neural networks, loss functions, and evaluation metrics. Learn to mold data and tackle real-world projects, equipping developers and data scientists with versatile deep-learning skills.

Mastering Image Segmentation with PyTorch using Real-World Projects

<p><strong>Best Price Of The Market</strong></p> <p>Give a compliment to your career and take it to the next level. This<strong> Database Administrator </strong>bundle will provide you with the essential knowledge to shine in your professional career. Whether you want to develop skills for your next job or elevate your skills for your next promotion, this Database Administrator bundle will help you stay ahead of the pack.</p> <p>Throughout the Database Administrator programme, it stresses how to improve your competency as a person in your chosen field while also outlining essential career insights in the relevant job sector.</p> <p>Along with this Database Administrator course, you will get <strong>10 premium courses, an original</strong><strong>hardcopy</strong>, <strong>11 PDF certificates (Main Course + Additional Courses) </strong>Student ID card as gifts.</p> <p><strong>This Database Administrator Bundle Consists of the following Premium courses: </strong></p> <ul> <li><strong> </strong><strong>Course 01: </strong>Introduction to Data Analysis</li><li><strong> </strong><strong>Course 02: </strong>Data Center Training Essentials: General Introduction</li><li><strong> </strong><strong>Course 03: </strong>Data Analytics with Tableau<strong><br /></strong></li><li><strong> </strong><strong>Course 04: </strong>Basic Google Data Studio</li><li><strong> </strong><strong>Course 05: </strong>Complete Google Analytics Course</li><li><strong> </strong><strong>Course 06: </strong>Python for Data Analysis</li><li><strong> </strong><strong>Course 07: </strong>Data Analysis in Excel Level 3 Course</li><li><strong> </strong><strong>Course 08: </strong>Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li><strong> </strong><strong>Course 09: </strong>GDPR Data Protection Level 5</li><li><strong> </strong><strong>Course 10: </strong>Level 3 Cyber Security</li><li><strong> </strong><strong>Course 11: </strong>Encryption</li></ul> <p>Enrol now in Database Administrator to advance your career, and use the premium study materials from Apex Learning.</p> <p><strong>How will I get my Certificate?</strong></p> <p>After successfully completing the Database Administrator course, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p> <ul> <li><strong></strong><strong> PDF Certificate: Free (Previously it was </strong> <strong>£</strong><strong>10 * 11 = </strong><strong>£</strong><strong>110)</strong></li><li><strong></strong><strong> Hard Copy Certificate: Free (For The Title Course)</strong></li></ul> <p>PS The delivery charge inside the UK is £3.99, and the international students have to pay £9.99.</p><p>The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Database Administrator expertise and essential knowledge, which will assist you in reaching your goal. Moreover, you can learn from any place in your own time without travelling for classes.</p> <p><strong>Curriculum of Bundle</strong></p> <p><strong> Course 01: Introduction to Data Analysis</strong></p> <ul> <li>Module 01: Introduction</li><li>Module 02: Agenda and Principles of Process Management</li><li>Module 03: The Voice of the Process</li><li>Module 04: Working as One Team for Improvement</li><li>Module 05: Exercise: The Voice of the Customer</li><li>Module 06: Tools for Data Analysis</li><li>Module 07: The Pareto Chart</li><li>Module 08: The Histogram</li><li>Module 09: The Run Chart</li><li>Module 10: Exercise: Presenting Performance Data</li><li>Module 11: Understanding Variation</li><li>Module 12: The Control Chart</li><li>Module 13: Control Chart Example</li><li>Module 14: Control Chart Special Cases</li><li>Module 15: Interpreting the Control Chart</li><li>Module 16: Control Chart Exercise</li><li>Module 17: Strategies to Deal with Variation</li><li>Module 18: Using Data to Drive Improvement</li><li>Module 19: A Structure for Performance Measurement</li><li>Module 20: Data Analysis Exercise</li><li>Module 21: Course Project</li><li>Module 22: Test your Understanding</li></ul> <p><strong> Course 02: Data Center Training Essentials: General Introduction</strong></p> <ul> <li>Module 01: Data Center Introduction</li><li>Module 02: Data Center Reliability</li><li>Module 03: Data Center Equipment</li><li>Module 04: Data Center White Space</li><li>Module 05: Data Center Support Spaces</li><li>Module 06: Data Center Security, Safety, Networks and IT</li></ul> <p><strong> Course 03: Data Analytics with Tableau</strong></p> <ul> <li>Module 01: Introduction to the Course</li><li>Module 02: Project 1: Discount Mart (Sales and Profit Analytics)</li><li>Module 03: Project 2: Green Destinations (HR Analytics)</li><li>Module 04: Project 3: Superstore (Sales Agent Tracker)</li><li>Module 05: Northwind Trade (Shipping Analytics)</li><li>Module 06: Project 5: Tesla (Stock Price Analytics)</li><li>Module 07: Bonus: Introduction to Database Concepts</li><li>Module 08: Tableau Stories</li></ul> <p><strong> Course 04: Basic Google Data Studio</strong></p> <ul> <li>Module 01: Introduction to GDS</li><li>Module 02: Data Visualization</li><li>Module 03: Geo-visualization</li><li>Module 04: A Socio-Economic Case Study</li></ul> <p><strong> Course 05: Complete Google Analytics Course</strong></p> <ul> <li>Module 01: Overview</li><li>Module 02: Navigation and Admin</li><li>Module 03: Creating a New Google Analytics Account</li><li>Module 04: Website Account Creation</li><li>Module 05: Connecting To WordPress Website</li><li>Module 06: Connecting To HTML Site</li><li>Module 07: Connect Custom Page and Site Builders</li><li>Module 08: Setting Up Annotations</li><li>Module 09: Setting Up Intelligence Events</li><li>Module 10: Set Up Custom Segments</li><li>Module 11: Export Data for Analysis</li><li>Module 12: Set Up Custom Reports</li><li>Module 13: Set Up Google Integrations</li><li>Module 14: Google Analytics Templates</li><li>Module 15: Real Time Reporting</li><li>Module 16: Setting Up Goals</li><li>Module 17: Third Party Integrations</li><li>Module 18: Audience Menu Overview</li><li>Module 19: Interests and Geography</li><li>Module 20: Conclusion</li></ul> <p><strong> Course 06: Python for Data Analysis</strong></p> <ul> <li>Welcome, Course Introduction &amp; overview, and Environment set-up</li><li>Python Essentials</li><li>Python for Data Analysis using NumPy</li><li>Python for Data Analysis using Pandas</li><li>Python for Data Visualization using matplotlib</li><li>Python for Data Visualization using Seaborn</li><li>Python for Data Visualization using pandas</li><li>Python for interactive &amp; geographical plotting using Plotly and Cufflinks</li><li>Capstone Project - Python for Data Analysis &amp; Visualization</li><li>Python for Machine Learning (ML) - scikit-learn - Linear Regression Model</li><li>Python for Machine Learning - scikit-learn - Logistic Regression Model</li><li>Python for Machine Learning - scikit-learn - K Nearest Neighbors</li><li>Python for Machine Learning - scikit-learn - Decision Tree and Random Forests</li><li>Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs)</li><li>Python for Machine Learning - scikit-learn - K Means Clustering</li><li>Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA)</li><li>Recommender Systems with Python - (Additional Topic)</li><li>Python for Natural Language Processing (NLP) - NLTK - (Additional Topic)</li></ul> <p><strong> Course 07: Data Analysis in Excel Level 3 Course</strong></p> <ul> <li>Modifying a Worksheet</li><li>Working with Lists</li><li>Analyzing Data</li><li>Visualizing Data with Charts</li><li>Using PivotTables and PivotCharts</li><li>Working with Multiple Worksheets and Workbooks</li><li>Using Lookup Functions and Formula Auditing</li><li>Automating Workbook Functionality</li><li>Creating Sparklines and Mapping Data</li><li>Forecasting Data</li></ul> <p><strong> Course 08: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</strong></p> <ul> <li>Introduction</li><li>Prepaid Expenses Models: Resources Download</li><li>Accounting for Prepaid Expenses</li><li>Excel Formulas Detailed: Introduction to three Excel Models</li><li>Formula Based Prepaid Expenses Model</li><li>Calculate Prepaid Expenses Amortisation from Exact Start Date</li><li>Prepaid Expenses Summary with Power Query and Pivot Table</li><li>Advanced VBA Prepaid Expenses Amortisation Model</li><li>BONUS: Dynamic Dashboard for Divisional Profit and Loss statements: Easy Way</li><li>Power Query &amp; Pivot Tables based Dashboard without any Formulas, Fully Dynamic</li><li>Thankyou</li></ul> <p><strong> Course 09: GDPR Data Protection Level 5</strong></p> <ul> <li>Module 01: GDPR Basics</li><li>Module 02: GDPR Explained</li><li>Module 03: Lawful Basis for Preparation</li><li>Module 04: Rights and Breaches</li><li>Module 05: Responsibilities and Obligations</li></ul> <p><strong> Course 10: Level 3 Cyber Security</strong></p> <ul> <li>FUNDAMENTALS OF NETWORKING</li><li>GETTING STARTED WITH CYBER SECURITY</li><li>LET'S BEGIN - THE FUNDAMENTALS OF CYBER SECURITY</li><li>DIVING DEEP INTO CYBER SECURITY</li><li>TYPES OF ACTORS, ATTACKS, MALWARE AND RESOURCES</li><li>FIREWALLS AND ANTIVIRUS</li><li>KEY SECURITY CONCEPTS</li></ul> <p><strong> Course 11: Encryption</strong></p> <ul> <li>Section 01: Introduction</li><li>Section 02: Basics of Common Encryption</li><li>Section 03: Technical Aspects of Encryption</li><li>Section 04: AES Basic Tech Demo</li><li>Section 05: File and System Encryption</li><li>Section 06: Conclusion</li></ul><h2>
        
        <div>CPD</div>
    </h2>

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

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

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

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

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div>    <p>P.S. The delivery charge inside the UK is £3.99, and the international students have to pay £9.99.</p>    </div>

                        </div>

Apex Learning

Database Administrator

Anti-Money Laundering (AML):
This comprehensive Anti-Money Laundering (AML) course is designed for individuals interested in safeguarding organizations against financial crime. Through up-to-date knowledge and practical guidance, you will be trained in the essential skills required to identify and prevent suspicious activities within any organization. With step-by-step instructions on conducting client risk assessments, this course equips you with a strong foundation in AML procedures.
Course Overview:
Covering key areas from terrorism financing frameworks to customer due diligence procedures, this AML course is structured to deepen your understanding of the role of a Money Laundering Reporting Officer. You will learn how to implement a risk-based strategy to combat financial crime, as well as the necessary policies and procedures for identifying and reporting suspicious activity.
The course provides practical skills in areas such as problem-solving and data analysis, essential for roles within financial and compliance departments. Whether you’re beginning your career in finance or seeking to expand your expertise in AML practices, this course offers valuable, real-world applications.
Learning Outcomes:
By completing this Anti-Money Laundering course, you will:
Gain a clear understanding of AML fundamentals and legal frameworks.
Explore the three stages of money laundering and review the Proceeds of Crime Act 2002.
Understand the duties of a Money Laundering Reporting Officer (MLRO).
Conduct effective client risk assessments.
Master the core elements of customer due diligence.
Familiarize yourself with AML compliance and record-keeping obligations in the UK.
Identify and respond to unusual transactions and suspicious activities.
Understand the importance of staff training and awareness in AML practices.
Course Features:
Accredited by CPD: Ensuring industry-recognized qualifications.
Fully online: Accessible from any device with interactive elements and voiceover support.
Flexible Learning Anytime, Anywhere: Self-paced, fully online, and accessible on all devices (laptops, tablets, smartphones)
24/7 Learning Support: Assistance is available around the clock.
Instant Certification: Receive your digital certificate upon completion.
Developed by Industry Experts: Practical, real-world AML training delivered by professionals in the field.
Assessment:
Upon completing the course, you’ll take an online assessment to test your understanding. Results are provided instantly, and you can retake the exam as many times as necessary to pass, at no extra cost.
Who Should Take This Course:
This course is perfect for individuals seeking to enhance their understanding of AML practices or those aspiring to work in AML-related roles. Ideal candidates include:
Money Laundering Reporting Officers (MLRO)
AML Analysts
Risk and Compliance Analysts
AML Officers
Compliance Managers
Certification:
Upon successful completion of the course, you will receive an accredited digital certificate immediately. While there is no expiry date on the certification, we recommend renewal every 12 months to stay current with evolving AML regulations.
Course Content:
Introduction to Money Laundering: Overview of money laundering and its three stages.
Proceeds of Crime Act 2002: A detailed look at this key legislation.
Development of AML Regulations: The evolution of anti-money laundering laws and frameworks.
Responsibilities of the MLRO: Roles and duties of the Money Laundering Reporting Officer.
Risk-Based Approach: Implementing a risk-based strategy to combat financial crime.
Customer Due Diligence: Steps involved in thorough customer verification processes.
Record Keeping: Best practices for maintaining compliant records.
Suspicious Conduct and Transactions: Identifying and handling questionable activities.
Awareness and Training: Ensuring proper staff training and awareness on AML procedures.
Join the course today and take the first step towards becoming an AML expert and advancing your career in the highly sought-after compliance field.

PETM

Legal Compliance

Fraud Analytics

Anti-Money Laundering (AML)

Financial Services Compliance

Risk Assessment

Anti-Money Laundering (AML):

This comprehensive Anti-Money Laundering (AML) course is designed for individuals interested in safeguarding organizations against financial crime. Through up-to-date knowledge and practical guidance, you will be trained in the essential skills required to identify and prevent suspicious activities within any organization. With step-by-step instructions on conducting client risk assessments, this course equips you with a strong foundation in AML procedures.


Anti-Money Laundering (AML) - Level 3

<p><strong>***Limited Time Exclusive Bundle***</strong></p><p><strong>Get Hard Copy + PDF Certificates + Transcript + Student ID Card + e-Learning App as a Gift - Enrol Now</strong></p><p>Tired of browsing and searching for a <strong>Database Administrator </strong> course you are looking for? Can't find the complete package that fulfils all your needs? Then don't worry as you have just found the solution. Take a minute and look through this extensive bundle that has everything you need to succeed.</p><p>After surveying thousands of learners just like you and considering their valuable feedback, this all-in<strong>-</strong>one Database Administrator bundle has been designed by industry experts. We prioritised what learners were looking for in a complete package and developed this in-demand Database Administrator course that will enhance your skills and prepare you for the competitive job market.</p><p>Also, our experts are available for answering your queries on Database Administrator and help you along your learning journey. Advanced audio-visual learning modules of these Database Administrator courses are broken down into little chunks so that you can learn at your own pace without being overwhelmed by too much material at once.</p><p>Furthermore, to help you showcase your expertise in Database Administrator, we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These certificates will enhance your credibility and encourage possible employers to pick you over the rest.</p><p><strong>This Database Administrator Bundle Consists of the following Premium courses:</strong></p><ul><li><strong> </strong><strong>Course 01: </strong>Introduction to Data Analysis</li><li><strong> </strong><strong>Course 02: </strong>Data Center Training Essentials: General Introduction</li><li><strong> </strong><strong>Course 03: </strong>Data Analytics with Tableau<strong><br /></strong></li><li><strong> </strong><strong>Course 04: </strong>Basic Google Data Studio</li><li><strong> </strong><strong>Course 05: </strong>Complete Google Analytics Course</li><li><strong> </strong><strong>Course 06: </strong>Python for Data Analysis</li><li><strong> </strong><strong>Course 07: </strong>Data Analysis in Excel Level 3 Course</li><li><strong> </strong><strong>Course 08: </strong>Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li><strong> </strong><strong>Course 09: </strong>GDPR Data Protection Level 5</li><li><strong> </strong><strong>Course 10: </strong>Level 3 Cyber Security</li><li><strong> </strong><strong>Course 11: </strong>Encryption</li><li><strong> </strong><strong>Course 12: </strong>Windows 10 Pro Complete Training</li><li><strong> </strong><strong>Course 13: </strong>Functional Skills IT</li><li><strong> </strong><strong>Course 14: </strong>Learning Computers and Internet Level 2</li></ul><p><strong>Benefits you'll get choosing Apex Learning:</strong></p><ul><li>Pay once and get lifetime access to 14 CPD courses</li><li>Free e-Learning App for engaging reading materials &amp; helpful assistance</li><li>Certificates, student ID for the title course included in a one-time fee</li><li>Free up your time - don't waste time and money travelling for classes</li><li>Accessible, informative modules designed by expert instructors</li><li>Learn at your ease - anytime, from anywhere</li><li>Study the course from your computer, tablet or mobile device</li><li>CPD accredited course - improve the chance of gaining professional skills</li><li>Gain valuable knowledge without leaving your home</li></ul><p><strong>How will I get my Certificate?</strong></p><p>After successfully completing the course, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p><ul><li><strong> </strong><strong>PDF Certificate: Free (For The Title Course)</strong></li><li><strong> </strong><strong>Hard Copy Certificate: Free (For The Title Course)</strong></li></ul><p>The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Database Administrator expertise and essential knowledge, which will assist you in reaching your goal.</p><p><strong>Curriculum of Bundle </strong></p><p><strong> Course 01: Introduction to Data Analysis</strong></p><ul><li>Module 01: Introduction</li><li>Module 02: Agenda and Principles of Process Management</li><li>Module 03: The Voice of the Process</li><li>Module 04: Working as One Team for Improvement</li><li>Module 05: Exercise: The Voice of the Customer</li><li>Module 06: Tools for Data Analysis</li><li>Module 07: The Pareto Chart</li><li>Module 08: The Histogram</li><li>Module 09: The Run Chart</li><li>Module 10: Exercise: Presenting Performance Data</li><li>Module 11: Understanding Variation</li><li>Module 12: The Control Chart</li><li>Module 13: Control Chart Example</li><li>Module 14: Control Chart Special Cases</li><li>Module 15: Interpreting the Control Chart</li><li>Module 16: Control Chart Exercise</li><li>Module 17: Strategies to Deal with Variation</li><li>Module 18: Using Data to Drive Improvement</li><li>Module 19: A Structure for Performance Measurement</li><li>Module 20: Data Analysis Exercise</li><li>Module 21: Course Project</li><li>Module 22: Test your Understanding</li></ul><p><strong> Course 02: Data Center Training Essentials: General Introduction</strong></p><ul><li>Module 01: Data Center Introduction</li><li>Module 02: Data Center Reliability</li><li>Module 03: Data Center Equipment</li><li>Module 04: Data Center White Space</li><li>Module 05: Data Center Support Spaces</li><li>Module 06: Data Center Security, Safety, Networks and IT</li></ul><p><strong> Course 03: Data Analytics with Tableau</strong></p><ul><li>Module 01: Introduction to the Course</li><li>Module 02: Project 1: Discount Mart (Sales and Profit Analytics)</li><li>Module 03: Project 2: Green Destinations (HR Analytics)</li><li>Module 04: Project 3: Superstore (Sales Agent Tracker)</li><li>Module 05: Northwind Trade (Shipping Analytics)</li><li>Module 06: Project 5: Tesla (Stock Price Analytics)</li><li>Module 07: Bonus: Introduction to Database Concepts</li><li>Module 08: Tableau Stories</li></ul><p><strong> Course 04: Basic Google Data Studio</strong></p><ul><li>Module 01: Introduction to GDS</li><li>Module 02: Data Visualization</li><li>Module 03: Geo-visualization</li><li>Module 04: A Socio-Economic Case Study</li></ul><p><strong> Course 05: Complete Google Analytics Course</strong></p><ul><li>Module 01: Overview</li><li>Module 02: Navigation and Admin</li><li>Module 03: Creating a New Google Analytics Account</li><li>Module 04: Website Account Creation</li><li>Module 05: Connecting To WordPress Website</li><li>Module 06: Connecting To HTML Site</li><li>Module 07: Connect Custom Page and Site Builders</li><li>Module 08: Setting Up Annotations</li><li>Module 09: Setting Up Intelligence Events</li><li>Module 10: Set Up Custom Segments</li><li>Module 11: Export Data for Analysis</li><li>Module 12: Set Up Custom Reports</li><li>Module 13: Set Up Google Integrations</li><li>Module 14: Google Analytics Templates</li><li>Module 15: Real Time Reporting</li><li>Module 16: Setting Up Goals</li><li>Module 17: Third Party Integrations</li><li>Module 18: Audience Menu Overview</li><li>Module 19: Interests and Geography</li><li>Module 20: Conclusion</li></ul><p><strong> Course 06: Python for Data Analysis</strong></p><ul><li>Welcome, Course Introduction &amp; overview, and Environment set-up</li><li>Python Essentials</li><li>Python for Data Analysis using NumPy</li><li>Python for Data Analysis using Pandas</li><li>Python for Data Visualization using matplotlib</li><li>Python for Data Visualization using Seaborn</li><li>Python for Data Visualization using pandas</li><li>Python for interactive &amp; geographical plotting using Plotly and Cufflinks</li><li>Capstone Project - Python for Data Analysis &amp; Visualization</li><li>Python for Machine Learning (ML) - scikit-learn - Linear Regression Model</li><li>Python for Machine Learning - scikit-learn - Logistic Regression Model</li><li>Python for Machine Learning - scikit-learn - K Nearest Neighbors</li><li>Python for Machine Learning - scikit-learn - Decision Tree and Random Forests</li><li>Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs)</li><li>Python for Machine Learning - scikit-learn - K Means Clustering</li><li>Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA)</li><li>Recommender Systems with Python - (Additional Topic)</li><li>Python for Natural Language Processing (NLP) - NLTK - (Additional Topic)</li></ul><p><strong> Course 07: Data Analysis in Excel Level 3 Course</strong></p><ul><li>Modifying a Worksheet</li><li>Working with Lists</li><li>Analyzing Data</li><li>Visualizing Data with Charts</li><li>Using PivotTables and PivotCharts</li><li>Working with Multiple Worksheets and Workbooks</li><li>Using Lookup Functions and Formula Auditing</li><li>Automating Workbook Functionality</li><li>Creating Sparklines and Mapping Data</li><li>Forecasting Data</li></ul><p><strong> Course 08: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</strong></p><ul><li>Introduction</li><li>Prepaid Expenses Models: Resources Download</li><li>Accounting for Prepaid Expenses</li><li>Excel Formulas Detailed: Introduction to three Excel Models</li><li>Formula Based Prepaid Expenses Model</li><li>Calculate Prepaid Expenses Amortisation from Exact Start Date</li><li>Prepaid Expenses Summary with Power Query and Pivot Table</li><li>Advanced VBA Prepaid Expenses Amortisation Model</li><li>BONUS: Dynamic Dashboard for Divisional Profit and Loss statements: Easy Way</li><li>Power Query &amp; Pivot Tables based Dashboard without any Formulas, Fully Dynamic</li><li>Thankyou</li></ul><p><strong> Course 09: GDPR Data Protection Level 5</strong></p><ul><li>Module 01: GDPR Basics</li><li>Module 02: GDPR Explained</li><li>Module 03: Lawful Basis for Preparation</li><li>Module 04: Rights and Breaches</li><li>Module 05: Responsibilities and Obligations</li></ul><p><strong> Course 10: Level 3 Cyber Security</strong></p><ul><li>FUNDAMENTALS OF NETWORKING</li><li>GETTING STARTED WITH CYBER SECURITY</li><li>LET'S BEGIN - THE FUNDAMENTALS OF CYBER SECURITY</li><li>DIVING DEEP INTO CYBER SECURITY</li><li>TYPES OF ACTORS, ATTACKS, MALWARE AND RESOURCES</li><li>FIREWALLS AND ANTIVIRUS</li><li>KEY SECURITY CONCEPTS</li></ul><p><strong> Course 11: Encryption</strong></p><ul><li>Section 01: Introduction</li><li>Section 02: Basics of Common Encryption</li><li>Section 03: Technical Aspects of Encryption</li><li>Section 04: AES Basic Tech Demo</li><li>Section 05: File and System Encryption</li><li>Section 06: Conclusion</li></ul><p><strong> Course 12: Windows 10 Pro Complete Training</strong></p><ul><li>Module 01: Course Overview</li><li>Module 02: Building Your Virtual Lab Environment</li><li>Module 03: Upgrading Windows 7, 8, or 8.1 to Windows 10</li><li>Module 04: Building a Microsoft Server 2016 Domain</li><li>Module 05: Windows Deployment Services (WDS)</li><li>Module 06: Windows 10 Firewall, Windows Defender and UAC</li><li>Module 07: Networking</li><li>Module 08: Troubleshooting</li><li>Module 09: User Preferences</li><li>Module 10: Maintenance</li></ul><p><strong> Course 13: Functional Skills IT</strong></p><ul><li>Section 1: Introduction</li><li>Section 2: Information Technology</li><li>Section 3: Components of IT</li><li>Section 4: Hardware</li><li>Section 5: Operating System</li><li>Section 6: Application/Software</li><li>Section 7: Networking</li><li>Section 8: Security</li><li>Section 9: Traffic Flow &amp; Enterprise Level IT Components</li><li>Section 10: Storage</li><li>Section 11: Database</li><li>Section 12: Virtualisation &amp; Cloud</li><li>Section 13: Management &amp; Other IT Jobs</li></ul><p><strong> Course 14: Learning Computers and Internet Level 2</strong></p><ul><li>Module 01 : Computer Operating and Troubleshooting</li><li>Module 02 : Internet and Computing - Key Applications</li><li>Module 03 : Internet and Computing - Tools &amp; Networking</li><li>Module 04 : Windows 8 for PC</li><li>Module 05 : Windows 10 - New Developments</li><li>Module 06 : Cyber Security Awareness</li></ul><h2>
        
        <div>CPD</div>
    </h2>

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

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

                        <div id="requirements">
                            <p>Our Database Administrator course is fully compatible with PCs, Macs, laptops, tablets and Smartphone devices.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

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

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>P.S. The delivery charge inside the UK is £3.99, and the international students have to pay £9.99.</p> </div>

                        </div>

Database Administrator Courses

<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
					<div>
			<div></div>
		</div>
				</div>
				</div>
				<div>
				<div>
			
				</div>
				<div>
				<div>
					<div><p>With the rise of machine learning applications in recent years, demand for python programmers continues to grow correspondingly. Python Data Science - For Beginners covers all the essential knowledge a beginner will need to understand Python data science. Python programming is one of the powering skills and having it in your CV could be most definitely a skyscraping leverage.</p><p>The course is designed by professionals to help our learners in building a both practical and theoretical knowledge of it. Having a good and solid foundation is mandatory to work efficiently in this field and Python Data Science - For Beginners will ensure you just that. It is a self-paced course, meaning the learner can complete the course at his suitable time schedule. Our course is split into 3 units with 2 short modules each under it. Professional certificates will be provided to the learners after the completion of their course.</p><p>Enroll today to get access to the materials and gain an empowering skill to aid your career development. </p></div>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</div></section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2><b> Learning outcome</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Individuals interested in Python Data Science</span>
									</li>
								<li>
											<span>
													</span>
										<span>Students</span>
									</li>
								<li>
											<span>
													</span>
										<span>Job Seekers </span>
									</li>
								<li>
											<span>
													</span>
										<span>Workers wanting pay rise or promotion </span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
					</div>
				</div>
				<div>
				<div>
					
			</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Why should I take this course?</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Affordable premium-quality E-learning content, you can learn at your own pace.</span>
									</li>
								<li>
											<span>
													</span>
										<span>You will receive a completion certificate upon completing the course.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Internationally recognized Accredited Qualification will boost up your resume.</span>
									</li>
								<li>
											<span>
													</span>
										<span>You will learn the researched and proven approach adopted by successful people to transform their careers.</span>
									</li>
								<li>
											<span>
													</span>
										<span>You will be able to incorporate various techniques successfully and understand your customers better.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Requirements</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>No formal qualifications required, anyone from any academic background can take this course.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Access to a computer or digital device with internet connectivity.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section><div>
                            <div>
                                <h2>Course Curriculum</h2>
                            </div>
                            			<div>
				

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4"><strong>Unit 01: Introduction to Python Data Science</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Module 01: Introduction to Python Data Science</td><td><span>🕐 00:03:00</span></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Module 02: Environment Setup</td><td><span>🕐 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Unit 02: Data Cleaning Packages</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Module 01: Numpy package for calculations</td><td><span>🕐 00:16:00</span></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Module 02: Panda package for Data cleaning</td><td><span>🕐 00:19:00</span></td>
				</tr>
								<tr>
					<td colspan="4"><strong>Unit 03: Data Visualization packages</strong></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Module 01: Matplotlib Data Visualization Part 1</td><td><span>🕐 00:16:00</span></td>
				</tr>
								<tr>
					<td>▶</td>
					<td>Module 02: Matplotlib Data Visualization Part 2</td><td><span>🕐 00:11:00</span></td>
				</tr>
				</tbody></table></div>

			</div>
		                        </div>

Skill Up

With the rise of machine learning applications in recent years, demand for python programmers continues to grow correspondingly.

Python Data Science - For Beginners

<p>Give a compliment to your career and take it to the next level. This <strong>SQL (Structured Query Language) </strong>will provide you with the essential knowledge and skills required to shine in your professional career. Whether you want to develop skills for your next job or want to elevate skills for your next promotion, this coursewill help you keep ahead of the pack.</p> <p>The <strong>course </strong>incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can reinforce your professional skills and essential knowledge, reaching out to the level of expertise required for your position. Further, this <strong>SQL (Structured Query Language) </strong>will add extra value to your resume to stand out to potential employers.</p> <p>Throughout the programme, it stresses how to improve your competency as a person in your profession while at the same time it outlines essential career insights in this job sector. Consequently, you'll strengthen your knowledge and skills; on the other hand, see a clearer picture of your career growth in future. By the end of the <strong> SQL (Structured Query Language),</strong> you can equip yourself with the essentials to keep you afloat into the competition.</p> <p>Along with this <strong>SQL (Structured Query Language) </strong>course<strong>,</strong> you will get 10 other premium courses. Also, you will get an original Hardcopy and PDF certificate for the title course and a student ID card absolutely free.</p> <p><strong>This Bundle Consists of the following Premium courses: </strong></p> <ul> <li><strong>Course 01: </strong>SQL Server for Beginners</li><li><strong>Course 02: </strong>Microsoft SQL Server Development for Everyone</li><li><strong>Course 03: </strong>Python for Data Analysis</li><li><strong>Course 04: </strong>Coding with HTML, CSS, &amp; JavaScript</li><li><strong>Course 05: </strong>Modern Web Designing - Level 2</li><li><strong>Course 06: </strong>Diploma in PHP Web Development</li><li><strong>Course 07: </strong>Front End Web Development Diploma</li><li><strong>Course 08: </strong>Secure Programming of Web Applications</li><li><strong>Course 09: </strong>Linux for Absolute Beginners!</li><li><strong>Course 10: </strong>Ethical Hacking</li><li><strong>Course 11: </strong>Creativity and Problem Solving Skills</li></ul> <p>So, enrol now to advance your career!</p> <p><strong>Benefits you'll get choosing Apex Learning for this SQL (Structured Query Language):</strong></p> <ul> <li>One payment, but lifetime access to 11 CPD courses</li><li>Certificate, student ID for the title course included in a one-time fee</li><li>Full tutor support available from Monday to Friday</li><li>Free up your time - don't waste time and money travelling for classes</li><li>Accessible, informative modules taught by expert instructors</li><li>Learn at your ease - anytime, from anywhere</li><li>Study the course from your computer, tablet or mobile device</li><li>CPD accredited course - improve the chance of gaining professional skills</li></ul> <p><strong>How will I get my Certificate?</strong></p> <p>After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p> <ul> <li><strong>PDF Certificate: Free (Previously it was £6*11 = £66)</strong></li><li><strong>Hard Copy Certificate: Free (For The Title Course: Previously it was £10)</strong></li></ul><p><strong>Curriculum of the Bundle</strong></p> <p><strong>Course 01: SQL Server for Beginners</strong></p> <ul> <li>Introduction</li><li>Setup</li><li>Basic queries</li><li>Security</li><li>MSSQL and different drivers</li><li>Files</li><li>General</li></ul> <p><strong>Course 02: Microsoft SQL Server Development for Everyone</strong></p> <ul> <li>Introduction</li><li>Manipulating Tables and Data</li><li>Relationships Foreign Keys</li><li>Group By and Aggregate Functions</li><li>Advanced Server Objects and Concepts</li></ul> <p><strong>Course 03: Python for Data Analysis</strong></p> <ul> <li>Welcome, Course Introduction &amp; overview, and Environment set-up</li><li>Python Essentials</li><li>Python for Data Analysis using NumPy</li><li>Python for Data Analysis using Pandas</li><li>Python for Data Visualization using matplotlib</li><li>Python for Data Visualization using Seaborn</li><li>Python for Data Visualization using pandas</li><li>Python for interactive &amp; geographical plotting using Plotly and Cufflinks</li><li>Capstone Project - Python for Data Analysis &amp; Visualization</li><li>Python for Machine Learning (ML) - scikit-learn - Linear Regression Model</li><li>Python for Machine Learning - scikit-learn - Logistic Regression Model</li><li>Python for Machine Learning - scikit-learn - K Nearest Neighbors</li><li>Python for Machine Learning - scikit-learn - Decision Tree and Random Forests</li><li>Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs)</li><li>Python for Machine Learning - scikit-learn - K Means Clustering</li><li>Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA)</li><li>Recommender Systems with Python - (Additional Topic)</li><li>Python for Natural Language Processing (NLP) - NLTK - (Additional Topic)</li></ul> <p><strong>Course 04: Coding with HTML, CSS, &amp; Javascript</strong></p> <ul> <li>Welcome</li><li>HTML 5</li><li>CSS 3</li><li>Bootstrap</li><li>Project 1 - Design a Landing Page</li><li>Project 2 - Business Website</li><li>SProject 3 - Portfolio</li></ul> <p><strong>Course 05: Modern Web Designing - Level 2</strong></p> <p><strong>Module: 01</strong></p> <ul> <li>1.1 Intro</li><li>1.2 Install the Tools and Get Started</li></ul> <p><strong>Module: 02</strong></p> <ul> <li>2.1 Intro to HTML</li><li>2.2 What is HTML</li><li>2.3 Start a New HTML File &amp; Use Tags</li><li>2.4 Header Tags</li><li>2.5 Edit Text</li><li>2.6 Links</li><li>2.7 Images</li><li>2.8 Lists</li><li>2.9 Challenge</li><li>2.10 HTML Outro</li></ul> <p><strong>Module: 03</strong></p> <ul> <li>3.1 CSS Intro</li><li>3.2 Add CSS Styles</li><li>3.3 Classes and IDs</li><li>3.4 Borders</li><li>3.5 Sizing</li><li>3.6 Padding and Margin</li><li>3.7 Text Styles</li><li>3.8 DIVs</li><li>3.9 Postioning</li><li>3.10 Hover</li><li>3.11 Easily Center Elements</li><li>3.12 Fonts</li><li>3.13 Challenge</li><li>3.14 CSS Outro</li></ul> <p><strong>Module: 04</strong></p> <ul> <li>4.1 Intro to Bootstrap</li><li>4.2 Install Bootstrap</li><li>4.3 Indenting and Containers</li><li>4.4 The Grid System</li><li>4.5 Images</li><li>4.6 Buttons</li><li>4.7 Challenge</li><li>4.8 Bootstrap Outro</li></ul> <p><strong>Module: 05</strong></p> <ul> <li>5.1 Landing Page Intro</li><li>5.2 Sketch Your Landing Page</li><li>5.3 The Top Section</li><li>5.4 Polish the Top Section</li><li>5.5 Adding Images</li><li>5.6 The Main Points Section</li><li>5.7 Collecting Emails With an Opt-In Form</li><li>5.8 Challenge</li><li>5.9 Landing Page Outro</li></ul> <p><strong>Module: 06</strong></p> <ul> <li>6.1 Business Site Intro</li><li>6.2 Sketch Up</li><li>6.3 Using Fancy Font Logo</li><li>6.4 Carousel Basics</li><li>6.5 Carousel Extras</li><li>6.6 Text on Images</li><li>6.7 Phone Number Icon</li><li>6.8 Google Maps</li><li>6.9 Font Awesome</li><li>6.10 Challenge</li><li>6.11 Business Site Outro</li></ul> <p><strong>Module: 07</strong></p> <ul> <li>7.1 Intro</li><li>7.2 Portfolio Sketch</li><li>7.3 Jumbotron</li><li>7.4 Nav Bar</li><li>7.5 Panels</li><li>7.6 Challenge</li><li>7.7 Portfolio Outre</li></ul> <p><strong>Module: 08</strong></p> <ul> <li>8.1 Hosting</li><li>8.2 Bluehost</li><li>8.3 Uploading</li><li>8.4 Tips</li><li>8.5 Hosting Outro</li></ul> <p><strong>Course 06: Diploma in PHP Web Development </strong></p> <ul> <li>Unit 01: Introduction</li><li>Unit 02: Environment Configuration</li><li>Unit 03: PHP Basics and Syntax</li><li>Unit 04: PHP Forms and MySQL and User Authentication</li></ul> <p><strong>Course 07: Front End Web Development Diploma</strong></p> <ul> <li>Welcome to the course!</li><li>Web Development Basics - HTML</li><li>Advanced HTML Concepts</li><li>Introduction to Cascading Style Sheets (CSS)</li><li>Advanced CSS</li><li>JavaScript for Begeinners</li><li>More JavaScript Concepts</li><li>Getting Started with jQuery</li><li>More jQuery</li><li>Bootstrap Basics</li><li>Project #2 - Pipboy from Fallout 4</li><li>Project #3 - Google Chrome Extension</li><li>BONUS - Coding Another Google Chrome Extension</li></ul> <p><strong>Course 08: Secure Programming of Web Applications</strong></p> <ul> <li>Section 01: Introduction</li><li>Section 02: Well-known Vulnerabilities and Secure Programming</li><li>Section 03: Conclusion and Summary</li></ul> <p><strong>Course 09: Linux for Absolute Beginners!</strong></p> <ul> <li>Introduction to Linux</li><li>Linux Installation</li><li>Linux Command Line Interface (CLI) Essentials</li><li>Advanced CLI Usage</li><li>Linux Development Tools</li><li>Web Development Project</li><li>Web Server Setup, Host Cofiguration and App Deployment</li><li>Linux User Management</li><li>Linux Network Administration</li></ul> <p><strong>Course 10: Ethical Hacking</strong></p> <ul> <li>Introduction to Ethical Hacking</li><li>Reconnaissance - Surveying the Attack Surface</li><li>Scanning and Enumeration - Getting Down to Business</li><li>Network Presence</li><li>Attacking</li><li>Web Hacking</li><li>Social Engineering - Hacking Humans</li></ul> <p><strong>Course 11: Creativity and Problem Solving Skills</strong></p> <ul> <li>Getting Started</li><li>The Problem Solving Method</li><li>Information Gathering</li><li>Problem Definition</li><li>Preparing for Brainstorming</li><li>Generating Solutions (I)</li><li>Generating Solutions (II)</li><li>Analyzing Solutions</li><li>Selecting a Solution</li><li>Planning Your Next Steps</li><li>Recording Lessons Learned</li></ul><h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                             <p>Anyone from any background can enrol in this <strong>SQL (Structured Query Language) </strong>bundle<strong>. </strong>Persons with similar professions can also refresh or strengthen their skills by enrolling in this course. Students can take this course to gather professional knowledge besides their study or for the future.</p> 
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                             <p>Our <strong>SQL (Structured Query Language) </strong>is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</p> <p>There is no time limit for completing this course, it can be studied in your own time at your own pace.</p> 
                        </div><h2>
        
        <div>Career path</div>
    </h2>

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

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the Hard Copy certificate for the title course (<strong>SQL Server for Beginners</strong>) absolutely Free! Other Hard Copy certificates are available for £10 each. </p> <p>Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

SQL - CPD Accredited

<p><strong>24 Hour Flash Deal **25-in-1 </strong><strong>Computer Vision: C++ and OpenCV with GPU support </strong><strong>Mega Bundle**</strong></p><p><strong> </strong><strong>Computer Vision: C++ and OpenCV with GPU support </strong><strong>Enrolment Gifts  **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter **</strong></p><p>Take the initial steps toward a successful long-term career by studying the <strong>Computer Vision: C++ and OpenCV with GPU support</strong> package online with <strong>Studyhub </strong>through our online learning platform. The Computer Vision: C++ and OpenCV with GPU support bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass.</p><p>This <strong>Computer Vision: C++ and OpenCV with GPU support </strong>course provides complete 360-degree training on Computer Vision: C++ and OpenCV with GPU support. You'll get not one, not two, not three, but <strong>twenty-five </strong>Computer Vision: C++ and OpenCV with GPU support courses included in this course. Plus Studyhub's signature <strong>Forever Access</strong> is given as always, meaning these Computer Vision: C++ and OpenCV with GPU support courses are yours for as long as you want them once you enrol in this course</p><p><strong>This Computer Vision: C++ and OpenCV with GPU support Bundle consists the following career oriented courses:</strong></p><ul><li>Course 01: Computer Vision: C++ and OpenCV with GPU support</li><li>Course 02: Python 3 Programming</li><li>Course 03: Machine Learning Course with Python</li><li>Course 04: Data Science &amp; Machine Learning with R</li><li>Course 05: Robotics - Sensors</li><li>Course 06: Digital Electric Circuits &amp; Intelligent Electrical Devices</li><li>Course 07: AutoCAD Programming using VB.NET with Windows Forms</li><li>Course 08: Learn MySQL from Scratch for Data Science and Analytics</li><li>Course 09: Data Structure</li><li>Course 10: Electronic Device and Circuits Protection Training</li><li>Course 11: Computer Science with Python Course</li><li>Course 12: IT Administration and Networking</li><li>Course 13: Foundations of IT Security: Protecting Digital Assets</li><li>Course 14: SQL Database Management</li><li>Course 15: Deep Learning Neural Network with R</li><li>Course 16: Computer Networks Security from Scratch to Advanced</li><li>Course 17: Electronic &amp; Electrical Devices Maintenance &amp; Troubleshooting</li><li>Course 18: Embedded Systems with 8051 Microcontroller</li><li>Course 19: MATLAB Simulink for Electrical Power Engineering</li><li>Course 20: Solidworks: Beginner to Advanced</li><li>Course 21: Info Graphics Web Design - Affinity Designer Training</li><li>Course 22: Diploma in Python Programming</li><li>Course 23: Penetration Testing with OWASP ZAP: Mastery course</li><li>Course 24: Unreal Engine 4</li><li>Course 25: Blender 3D Character Modeling &amp; Rendering</li></ul> <p>The <strong>Computer Vision: C++ and OpenCV with GPU support </strong>course has been prepared by focusing largely on Computer Vision: C++ and OpenCV with GPU support career readiness. It has been designed by our Computer Vision: C++ and OpenCV with GPU support 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.</p><p>The Computer Vision: C++ and OpenCV with GPU support Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Computer Vision: C++ and OpenCV with GPU support bundle course has been created with <strong>twenty-five </strong>premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field.</p><p>This Computer Vision: C++ and OpenCV with GPU support Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Computer Vision: C++ and OpenCV with GPU support Elementary modules, allowing our students to grasp each lesson quickly.</p><p>The Computer Vision: C++ and OpenCV with GPU support 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><p><strong>In this exclusive </strong><strong>Computer Vision: C++ and OpenCV with GPU support </strong><strong>bundle, you really hit the jackpot. Here's what you get:</strong></p><ul><li>Step by step Computer Vision: C++ and OpenCV with GPU support lessons</li><li>One to one assistance from Computer Vision: C++ and OpenCV with GPU supportprofessionals if you need it</li><li>Innovative exams to test your knowledge after the Computer Vision: C++ and OpenCV with GPU supportcourse</li><li>24/7 customer support should you encounter any hiccups</li><li>Top-class learning portal</li><li>Unlimited lifetime access to all twenty-five Computer Vision: C++ and OpenCV with GPU support 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 Computer Vision: C++ and OpenCV with GPU support certificate and transcript on the next working day</li><li>Easily learn the Computer Vision: C++ and OpenCV with GPU support skills and knowledge you want from the comfort of your home</li></ul> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        250 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>Computer Vision: C++ and OpenCV with GPU support </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 Computer Vision: C++ and OpenCV with GPU support</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To participate in this <strong>Computer Vision: C++ and OpenCV with GPU support </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 Computer Vision: C++ and OpenCV with GPU support</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>You will be able to kickstart your <strong>Computer Vision: C++ and OpenCV with GPU support </strong>career because this course includes various courses as a bonus. This Computer Vision: C++ and OpenCV with GPU support is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Computer Vision: C++ and OpenCV with GPU support 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>

Computer Vision: C++ and OpenCV with GPU support - CPD Certified

<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

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

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

Data Science

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

Python Machine Learning Bootcamp

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

Machine Learning with Real World Projects

<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2><b>Course Overview</b></h2>		</div>
				</div>
				<div>
				<div>
					<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>
				</div>
				</div>
				<div>
				<div>
					<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>
				</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div><div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
					</div>
				</div>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
					<div>
											
															
											</div>
				</div>
				</div>
						</div>
					</div>
		</div>
				<div>
			<div>
							<div>
						<div>
				<div>
					<div>
											
															
											</div>
				</div>
				</div>
						</div>
					</div>
		</div>
				<div>
			<div>
							<div>
						<div>
				<div>
					<div>
											
															
											</div>
				</div>
				</div>
						</div>
					</div>
		</div>
				<div>
			<div>
							<div>
						<div>
				<div>
					<div>
											
															
											</div>
				</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
						</div>
					</div>
		</div>
								</div>
					</div>

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

<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
					</div>
				</div>
				<div>
				<div>
					<div><p>The comprehensive Machine Learning - Use in Flutter has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Machine Learning - Use in Flutter today, and learn from the very best the industry has to offer!</p></div>
				</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div><div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
					<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>
				</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>

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.

649 Courses

Complete Data Science - CPD Certified

By Academy for Health and Fitness

Cloud Solutions Architect Diploma - CPD Certified

By Studyhub UK

Data Engineering Advanced Diploma - CPD Certified

By Studyhub UK

Mastering Image Segmentation with PyTorch using Real-World Projects

By Packt

Database Administrator

By Apex Learning

Anti-Money Laundering (AML) - Level 3

By PETM

Database Administrator Courses

By Apex Learning

Python Data Science - For Beginners

By Skill Up

SQL - CPD Accredited

By Apex Learning

Computer Vision: C++ and OpenCV with GPU support - CPD Certified

By Studyhub UK

Search By Location