Name: Data Engineering - CPD Certified
Price: 100 GBP
Availability: InStock

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<h2>About this training course</h2>
<p>Gas-lift is one of the predominant forms of artificial lift used for lifting liquids from conventional, unconventional, onshore and offshore assets. Gas-lift and its various forms (intermittent lift, gas-assisted plunger lift) allows life of well lift-possibilities when selected and applied properly. This 5-day training course is designed to give participants a thorough understanding of gas-lift technology and related application concepts.</p>
<p>This training course covers main components such as application envelope, relative strengths and weaknesses of gas-lift and its different forms like intermittent lift, gas-assisted plunger lift. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion.</p>
<p><strong>Unique Features:</strong></p>
<ul>
<li>Hands-on usage of <strong>SNAP Software</strong> to solve gas-lift exercises</li>
<li>Discussion on <strong>digital oil field</strong></li>
<li><strong>Machine learning</strong> <strong>applications</strong> in gas-lift optimization</li>
</ul>
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Training Objectives 

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<p>After the completion of this training course, participants will be able to:</p>
<ul>
<li>Understand the fundamental theories and procedures related to Gas-Lift operations</li>
<li>Easily recognize the different components of the gas-lift system and their basic structural and operational features</li>
<li>Be able to design a gas-lift installation</li>
<li>Comprehend how digital oilfield tools help address ESP challenges</li>
<li>Examine recent advances in real-time approaches to the production monitoring and lift management</li>
</ul>
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Target Audience 

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<p>This training course is suitable and will greatly benefit the following specific groups:</p>
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<li>Production, reservoir, completion, drilling and facilities engineers, analysts, and operators</li>
<li>Anyone interested in learning about implications of gas-lift systems for their fields and reservoirs</li>
</ul>
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Course Level 

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<li>Intermediate</li>
<li>Advanced</li>
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Training Methods 

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<p><span>The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization.</span></p>
<p><em><span>Course Duration: 5 days in total (35 hours).</span></em></p>
<p><strong><span>Training Schedule</span></strong></p>
<p><span>0830 - Registration </span><span>0900 - Start of training </span><span>1030 - Morning Break </span><span>1045 - Training recommences </span><span>1230 - Lunch Break </span><span>1330 - Training recommences </span><span>1515 - Evening break </span><span>1530 - Training recommences </span><span>1700 - End of Training</span></p>
<p><span>The maximum number of participants allowed for this training course is 20.</span></p>
<p>This course is also available through our Virtual Instructor Led Training (VILT) format.</p>
<p><strong>Prerequisites:</strong></p>
<ul>
<li>Understanding of petroleum production concepts.</li>
<li>Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software.</li>
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Trainer

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<p>Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA.</p>
<p><strong>Highlighted Work Experience: </strong></p>
<ul>
<li>At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe.</li>
<li>Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements.</li>
<li>Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics.</li>
<li>Developed a workshop on digital oilfield approaches for production engineers.</li>
</ul>
<p><strong>Patents:</strong></p>
<ul>
<li>Principal inventor: 'Smarter Slug Flow Conditioning and Control'</li>
<li>Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells'</li>
<li>Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution'</li>
</ul>
<p><strong>Worldwide Experience in Training / Seminar / Workshop Deliveries:</strong></p>
<ul>
<li>Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&amp;T, Louisiana State, U of Southern California, and U of Houston.</li>
<li>He has conducted seminars, bespoke trainings / workshops globally for practicing professionals:
<ul>
<li><u>Companies:</u> Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others.</li>
<li><u>Countries:</u> USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela.</li>
<li>Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic.</li>
</ul>
</li>
</ul>
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POST TRAINING COACHING SUPPORT (OPTIONAL)

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<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information post training support and fees applicable</p>
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Accreditions And Affliations

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EnergyEdge - Training for a Sustainable Energy Future

Renewable Energy

Oil & Gas

Gas Lift Design & Optimization using NODAL Analysis

Team of 10, pp

Normal Fee, pp

<p>Do you want to prepare for your dream job but strive hard to find the right courses? Then, stop worrying, for our strategically modified<strong> Computer Programming and Data Analysis and Management</strong> bundle will keep you up to date with the relevant knowledge and most recent matters of this emerging field. So, invest your money and effort in our <strong>33</strong> course mega bundle that will exceed your expectations within your budget.</p> <p>The<strong> Computer Programming and Data Analysis and Management</strong> related fields are thriving across the UK, and recruiters are hiring the most knowledgeable and proficient candidates. It's a demanding field with magnitudes of lucrative choices. If you need more guidance to specialise in this area and need help knowing where to start, then <strong>StudyHub </strong>proposes a preparatory bundle. This comprehensive <strong> Computer Programming and Data Analysis and Management</strong> bundle will help you build a solid foundation to become a proficient worker in the sector.</p> <p><strong>This Computer Programming and Data Analysis and Management Bundle consists of the following</strong><strong> 30 </strong><strong>CPD Accredited Premium courses - </strong></p> <ul> <li>Course 01: C++ Development: The Complete Coding Guide</li><li>Course 02: Basic C# Coding</li><li>Course 03: Computer Vision: C++ and OpenCV with GPU support</li><li>Course 04: Python Basic Programming for Absolute Beginners</li><li>Course 05: Python Programming for Everybody</li><li>Course 06: Intermediate Python Coding</li><li>Course 07: Quick Data Science Approach from Scratch</li><li>Course 08: Root Cause Analysis</li><li>Course 09: Google Data Studio: Data Analytics</li><li>Course 10: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li>Course 11: Business Intelligence and Data Mining Masterclass</li><li>Course 12: Level 2 Microsoft Office Essentials</li><li>Course 13: SQL NoSQL Big Data and Hadoop</li><li>Course 14: Introduction to Data Analysis</li><li>Course 15: Data Science and Visualisation with Machine Learning</li><li>Course 16: Data Analytics with Tableau</li><li>Course 17: R Programming for Data Science</li><li>Course 18: Complete Google Analytics Course</li><li>Course 19: JavaScript Promises</li><li>Course 20: JavaScript Foundations for Everyone</li><li>Course 21: Javascript for Data Structures</li><li>Course 22: jQuery Masterclass Course: JavaScript and AJAX Coding Bible</li><li>Course 23: Microsoft SQL Server Development for Everyone</li><li>Course 24: SQL Programming Masterclass</li><li>Course 25: Level-3 Machine Learning Course with Python</li><li>Course 26: Learn to Use Python for Spatial Analysis in ArcGIS</li><li>Course 27: Microsoft Azure Machine Learning</li><li>Course 28: Javascript Programming for Beginners</li><li>Course 29: Basic Asynchronous JavaScript</li><li>Course 30: JavaScript Functions</li></ul> <p><strong>3 </strong><strong>Extraordinary Career Oriented courses that will assist you in reimagining your thriving techniques-</strong></p> <ul> <li>Course 01: Career Development Plan Fundamentals</li><li>Course 02: CV Writing and Job Searching</li><li>Course 03: Interview Skills: Ace the Interview</li></ul> <p><strong>Learning Outcome</strong></p> <p><strong>This tailor-made </strong><strong>Computer Programming and Data Analysis and Management</strong><strong> bundle will allow you to-</strong></p> <ul> <li>Uncover your skills and aptitudes to break new ground in the related fields</li><li>Deep dive into the fundamental knowledge</li><li>Acquire some hard and soft skills in this area</li><li>Gain some transferable skills to elevate your performance</li><li>Maintain good report with your clients and staff</li><li>Gain necessary office skills and be tech savvy utilising relevant software</li><li>Keep records of your work and make a report</li><li>Know the regulations around this area</li><li>Reinforce your career with specific knowledge of this field</li><li>Know your legal and ethical responsibility as a professional in the related field</li></ul> <p>This Computer Programming and Data Analysis and Management Bundle resources were created with the help of industry experts, and all subject-related information is kept updated on a regular basis to avoid learners from falling behind on the latest developments.</p> <p><strong>Certification</strong></p> <p>After studying the complete training you will be able to take the assessment. After successfully passing the assessment you will be able to claim all courses pdf certificates and <strong>1 hardcopy certificate for the Title Course completely free</strong>. Other Hard Copy certificates need to be ordered at an additional cost of •8.</p> <h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                             <p>Ambitious learners who want to strengthen their CV for their desired job should take advantage of the Computer Programming and Data Analysis and Management bundle! This bundle is also ideal for professionals looking for career advancement.</p> 
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                             <p>To participate in this 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 Programming and Data Analysis and Management</li></ul> 
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                             <p>Upon completing this essential Bundle, you will discover a new world of endless possibilities. These courses will help you to get a cut above the rest and allow you to be more efficient in the relevant fields.</p> 
                        </div>

Studyhub UK

Microsoft Certification

Computing Skills

Computing & Software Development Tools

Computer Programming

Computer Skills

Professional Skills Course (PSC)

Computer Programming and Data Analysis and Management

General Admission

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<section>
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<h2><strong>About this Course</strong></h2>
<p>This 5 full-day course presents the most modern statistical and mathematical forecasting frameworks used by practitioners to tackle the load forecasting problem across short time and long time scales. The course presents practical applications to solving forecasting challenges, supported by real life examples from large control areas. It presents the weather impacts on the load forecasts and the methodologies employed to quantify the weather effect and building a repository of weather normal data.</p>
<p>A good load forecast methodology must improve its forecasting accuracy and support a consistent load forecasting process. The load forecasting widely used in the power industry has evolved significantly with the advancement and adoption of Artificial Intelligence techniques such as Machine Learning.</p>
<p>With the increased penetration of inverter-based resources, the operation of electric grids grew in complexity, leading to load forecasts that are updated more frequently than once a day. Furthermore, several jurisdictions adopted a smaller granularity than the hourly load forecasts in the effort to reduce the forecasting uncertainties.</p>
<p>On the generation side, fuel forecasting professionals must meet energy requirements while making allowance for the uncertainty on both the demand and the supply side.</p>
<p>This training course will also feature a guest speaker, who is a Ph.D candidate to provide insights into the most modern aspects of Artificial Intelligence in the context of load forecasting.</p>
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<div id="accordion">
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Training Objectives 

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<p><span>This course offers a comprehensive approach to all aspects of load forecasting:</span></p>
<ul>
<li><span>Gain a perspective of load forecasting from both operators in the generating plant and system operators.</span></li>
<li><span>Understand and review the advanced load forecasting concepts and forecasting methodologies</span></li>
<li><span>Learn the application of Artificial Neural Networks and Probabilistic Forecasting methods to manage forecasting uncertainties in short time frames</span></li>
<li><span>Appreciate market segmentation and econometric framework for long term forecasts</span></li>
<li><span>Find out the most recent practical application of load forecasting as examples from large power companies</span></li>
<li><span>Get access to recent industry reports and developments</span></li>
</ul>
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Target Audience 

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<ul>
<li><span>Energy load forecasting professionals from power plant and system operators</span></li>
<li><span>Energy planners and energy outlook forecasters and plant operators</span></li>
<li><span>Fuel procurement professionals</span></li>
<li><span>Planners and schedulers of thermal generating units</span></li>
</ul>
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Course Level 

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<li>Intermediate</li>
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Trainer

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<p><span>Your expert course instructor is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5.</span></p>
<p><span>With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana.</span></p>
<p><span>Our Key expert delivered over 60 specialized seminars to executives and engineers from Canada, Europe, South and North America, Middle East, South East Asia and Japan. Few examples are:</span></p>
<ul>
<li><span>Modern Power System in Digital Utilities - The Energy Commission, Malaysia and utilities in the Middle East, GCCIA, June 2020</span></li>
<li><span>Assessment of OETC Control Centre, Oman, December 2019</span></li>
<li><span>Demand Side management, Load Forecasting in a Smart Grid, Oman, 2019</span></li>
<li><span>Renewable Resources in a Smart Grid (Malaysia, Thailand, Indonesia, GCCIA, Saudi Arabia)</span></li>
<li><span>The Modern Power System: Impact of the Power Electronics on the Power System</span></li>
<li><span>The Digital Utility, AI and Blockchain</span></li>
<li><span>Smart Grid and Reliability of Distribution Systems, Cyme, Montreal, Canada</span></li>
<li><span>Economic Dispatch in the context of an Energy Market (TNB, Sarawak Energy, Malaysia)</span></li>
<li><span>Energy Markets, Risk Assessment and Financial Management, PES, IEEE: Chicago, San Francisco, New York, Portugal, South Africa, Japan. Provided training at CEO and CRO level.</span></li>
<li><span>Enterprise Risk methodology, EDP, Portugal</span></li>
<li><span>Energy Markets: Saudi Electricity Company, Tenaga National Berhad, Malaysia</span></li>
<li><span>Reliability Centre Maintenance (South East Asia, Saudi Electricity Company, KSA)</span></li>
<li><span>EUSN, ENERGY &amp; UTILITIES SECTOR NETWORK, Government of Canada, 2016</span></li>
<li><span>Connected+, IOT, Toronto, Canada September 2016 and 2015</span></li>
<li><span>Smart Grid, Smart Home HomeConnect, Toronto, Canada November 2014</span></li>
<li><span>Wind Power: a Cautionary Tale, Ontario Centre for Public Policy, 2010</span></li>
</ul>
</div>
</div>
</div>
<div>
<div>

POST TRAINING COACHING SUPPORT (OPTIONAL)

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<div>
<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information post training support and fees applicable</p>
</div>
</div>
</div>
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Accreditions And Affliations

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</div>
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</section>

Advanced Load Forecasting & Methodology

<p><strong>Unleash Your Coding Potential with the Ultimate Software Engineering Bundle!</strong></p><p>According to a recent study by Tech Nation, the UK's tech industry is booming, with an estimated <strong>4.8 million</strong> tech workers contributing over <strong>£185 billion</strong> to the economy. It also shows a growing demand for skilled software engineers, with a projected job growth of <strong>22% </strong>over the next decade and an average salary of <strong>£58,000</strong> per year.<strong><br /></strong></p><p>Are you ready to embark on an incredible journey through the world of programming and software engineering? Our <strong>Software Engineering, Python, C++ , Javascript, CSS, HTML Coding</strong> bundle is meticulously curated to equip you with the essential skills and knowledge to thrive in this dynamic field. We've assembled a collection of 20 skill-boosting courses in this Software Engineering bundle that will teach you the fundamentals of programming, web development, machine learning, and more. You'll also gain valuable insights into cybersecurity, SaaS development, and game development, empowering you to pursue a diverse range of career paths.</p><p>Don't miss out on this opportunity to enhance your coding prowess and ignite your software engineering journey. Enrol now and shape your future today!</p><p><strong>This Software Engineering, Python, C++ , Javascript, CSS, HTML Coding Bundle Contains </strong><strong>20</strong><strong> of Our Premium Courses for One Discounted Price:</strong></p><ul><li><strong> Course 01: </strong>Coding with Scratch<strong><br /></strong></li><li><strong> Course 02: </strong>C# Programming - Beginner to Advanced<strong><br /></strong></li><li><strong> Course 03: </strong>Machine Learning with Python Course<strong><br /></strong></li><li><strong> Course 04: </strong>Basics of WordPress: Create Unlimited Websites<strong><br /></strong></li><li><strong> Course 05: </strong>Modern PHP Web Development w/ MySQL, GitHub &amp; Heroku<strong><br /></strong></li><li><strong> Course 06: </strong>Node JS: API Development with Swagger<strong><br /></strong></li><li><strong> Course 07: </strong>Refactor Javascript <strong><br /></strong></li><li><strong> Course 08: </strong>Python Programming Bible | Networking, GUI, Email, XML, CGI<strong><br /></strong></li><li><strong> Course 09: </strong>Web Application Penetration Testing Course<strong><br /></strong></li><li><strong> Course 10: </strong>Penetration Testing with OWASP ZAP: Mastery course<strong><br /></strong></li><li><strong> Course 11: </strong>How To Startup Your Own SaaS (Software As a Service) Company (SaaS Evolution)<strong><br /></strong></li><li><strong> Course 12: </strong>Three.js &amp; WebGL 3D Programming Crash Course<strong><br /></strong></li><li><strong> Course 13: </strong>HTML Web Development Crash Course<strong><br /></strong></li><li><strong> Course 14:</strong> CSS Web Development Crash Course<strong><br /></strong></li><li><strong> Course 15:</strong> Flutter &amp; Dart Development for Building iOS and Android Apps<strong><br /></strong></li><li><strong> Course 16: </strong>Masterclass Bootstrap 5 Course - Responsive Web Design<strong><br /></strong></li><li><strong> Course 17: </strong>Game Development using Cocos2d-x v3 C++<strong><br /></strong></li><li><strong> Course 18: </strong>C++ Development: The Complete Coding Guide<strong><br /></strong></li><li><strong> Course 19:</strong> .NET Core API Development<strong><br /></strong></li><li><strong> Course 20: </strong>Stripe with C#</li></ul><p><strong>Learning Outcomes of Software Engineering Bundle:</strong></p><ul><li>Fluent coding in Python, C++, JavaScript, and more.</li><li>Web development mastery with HTML, CSS, and Bootstrap.</li><li>Expertise in machine learning, AI, and 3D programming.</li><li>Proficiency in WordPress, PHP, and Node.js.</li><li>Penetration testing skills for enhanced cybersecurity.</li><li>Creating iOS and Android apps using Flutter &amp; Dart.</li><li>Building a successful SaaS company from scratch.</li></ul><p><strong>Why Choose Our Software Engineering Bundle?</strong></p><ul><li>FREE Software Engineering certificate accredited</li><li>Get a free student ID card with Software Engineering Training</li><li>Get instant access to this Software Engineering course.</li><li>Learn Software Engineering from anywhere in the world</li><li>The Software Engineering is affordable and simple to understand</li><li>The Software Engineering is an entirely online, interactive lesson with voiceover audio</li><li>Lifetime access to the Software Engineering course materials</li><li>The Software Engineering comes with 24/7 tutor support</li></ul> <p>If you aim to enhance your Software Engineering skills, our comprehensive Software Engineering course is perfect for you. Designed for success, this Software Engineering course covers everything from basics to advanced topics in Software Engineering.</p><p>Dive into the magic of coding with courses like "Coding with Scratch" and "C# Programming - Beginner to Advanced". Harness the power of AI and data with "Machine Learning with Python Course", and effortlessly create stunning websites with "Modern PHP Web Development w/ MySQL, GitHub &amp; Heroku". Explore cutting-edge technologies such as "Node JS: API Development with Swagger" and "Three.js &amp; WebGL 3D Programming Crash Course. With these courses, you'll not only master programming languages but also gain the skills to secure web applications with "Web Application Penetration Testing Course" and "Penetration Testing with OWASP ZAP: Mastery Course".</p><p>Each lesson in this Software Engineering course is crafted for easy understanding, enabling you to become proficient in Software Engineering. Whether you are a beginner or looking to sharpen your existing skills, this Software Engineering is the ideal choice.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        200 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 Software Engineering Bundle is ideal for:</p><ul><li>Aspiring programmers seeking comprehensive language expertise.</li><li>Web developers aiming to build responsive and engaging sites.</li><li>Tech enthusiasts interested in AI, machine learning, and 3D programming.</li><li>Individuals looking to enter the world of app development.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

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

                        <div id="career_path">
                            <p>This Software Engineering bundle will allow you to kickstart or take your career to the next stage in the related sector such as:</p><ul><li>Junior Software Engineer: £25,000 - £35,000</li><li>Web Developer: £30,000 - £40,000</li><li>Machine Learning Engineer: £40,000 - £55,000</li><li>App Developer: £35,000 - £45,000</li><li>Penetration Tester: £30,000 - £45,000</li><li>SaaS Entrepreneur: Potential for substantial earnings.</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4> Digital certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4> Hard copy certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>

                        </div>

Academy for Health and Fitness

Software Engineer

Online Course Marketing

Online Course Creation

Software Engineering

Digital Skills

Software Development

Software Engineering, Python, C++ , Javascript, CSS, HTML Coding

<div>
                        
                        <div>
                            <p><span>Aligned with the AIGP certification program, AI Governance Professional</span><span>â¯</span><span>Training is for professionals tasked with implementing AI governance and risk management in their organizations. It provides baseline knowledge and strategies for responding to complex risks associated with the evolving AI landscape. This training meets the rapidly growing need for professionals who can develop, integrate and deploy trustworthy AI systems in line with emerging laws and policies.</span></p>
                        </div>
                    </div>
                    <div>
                        <h2>About This Course</h2>
                        <div>
                            <p>This training teaches critical artificial intelligence governance concepts that are also integral to the AIGP certification exam. While not purely a 'test prep' course, this training is appropriate for professionals who plan to certify, as well as for those who want to deepen their AI governance knowledge. Both the training and the exam are based on the same body of knowledge.</p>
<p> </p>
<p><strong>Module 1:</strong> Foundations of artificial intelligence Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context.</p>
<p><strong> Module 2:</strong> AI impacts on people and responsible AI principles Outlines the core risks and harms posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI.</p>
<p><strong>Module 3:</strong> AI development life cycle Describes the AI development life cycle and the broad context in which AI risks are managed.</p>
<p><strong>Module 4:</strong> Implementing responsible AI governance and risk management Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while acknowledging AI systems' potential societal benefits.</p>
<p><strong>Module 5:</strong> Implementing AI projects and systems Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment.</p>
<p><strong>Module 6:</strong> Current laws that apply to AI systems Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform.</p>
<p><strong>Module 7:</strong> Existing and emerging AI laws and standards Describes global AI-specific laws and the major frameworks and standards that exemplify how AI systems can be responsibly governed.</p>
<p><strong>Module 8:</strong> Ongoing AI issues and concerns Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues.</p>
                        </div>
                    </div>
                    <div>
                        <h2>Accreditation</h2>
                        <div>
                            <p>The associated exam is accredited by the IAPP under its <a href="https://iapp.org/news/a/iapp-certifications-granted-ansi-accreditation-under-international-iso-standard/">ANSI Accreditation</a></p>
                        </div>
                    </div>
                    <div>
                        <h2>Who Should Attend?</h2>
                        <div>
                            <p><span>Any professionals tasked with developing AI governance and risk management in their operations, and anyone pursuing IAPP Artificial Intelligence Governance Professional certification.</span></p>
                        </div>
                    </div>
                    <div>
                        <h2>Prerequisites</h2>
                        <div>
                            <p>A general understanding of AI, Corporate Governance, and Business value would be of benefit to participants.</p>
                        </div>
                    </div>
                    <div>
                        <h2>Assessment</h2>
                        <div>
                            <p>As with all IAPP exams, the AIGP is a 90 question, multiple choice exam to be completed within 150 minutes. Exams are hosted by Pearsonvue and can be taken either remotely, or via any one of hundreds of exam venues globally.</p>
<p>A passing score is achieved at 70%</p>
                        </div>
                    </div>
                    <div>
                        <h2>Our Guarantee</h2>
                        <div>
                            <ul>
<li>We are an approved IAPP training provider</li>
<li>Exam pass guarantee, or retrain until you do, for free</li>
</ul>
                        </div>
                    </div>
                    <div>
                        <h2>What's Included?</h2>
                        <div>
                            <ul>
<li>Participant Guide</li>
<li>Study Guide</li>
<li>Practice Exam</li>
<li>Exam voucher</li>
<li>Breakfast, lunch, coffees and snacks (Classroom courses only)</li>
</ul>
                        </div>
                    </div>
                    <div>
                        <h2>Certification Logo</h2>
                        <div>
                            <p><img src="https://www.the-training-centre.com/content/img/AIGP_Seal_color.png" /></p>
                        </div>
                    </div>

Training Centre

AI Governance Professional (AIGP)

<p><strong> 24-Hour Knowledge Knockdown! Prices Reduced Like Never Before </strong></p><p>Did you know the UK tech sector is booming, with a projected growth of <strong>2.7% in 2024?</strong> But with this growth comes the need for skilled professionals. Are you ready to be part of this exciting future? Python, a versatile and in-demand programming language, could be your key. But where do you start?</p><p>This Python Programming bundle empowers you, from beginner to advanced, to master Python programming. Learn essential syntax, build applications, explore data science and machine learning, and delve into deep learning and neural networks. Gain the skills and confidence to launch your tech career or upskill for lucrative opportunities.</p><p><strong>This</strong><strong> Diploma in Python Programming at QLS Level 5 Bundle Contains </strong><strong>11</strong><strong> of Our Premium Courses for One Discounted Price:</strong></p><ul><li><strong> Course 01: </strong>Diploma in Python for Beginners Part 1 at QLS Level 5</li><li><strong> Course 02: </strong>Computer Science With Python</li><li><strong> Course 03: </strong>Python Basic Programming for Absolute Beginners</li><li><strong> Course 04: </strong>Python 101: Essentials for Beginners</li><li><strong> Course 05: </strong>Python Masterclass: Advanced Diploma</li><li><strong> Course 06: </strong>Coding with Python 3</li><li><strong> Course 07: </strong>Python Programming Bible</li><li><strong> Course 08: </strong>Machine Learning with Python Course</li><li><strong> Course 09: </strong>Data Science &amp; Machine Learning with Python</li><li><strong> Course 10: </strong>Code with Python: Learn Classes, Methods and OOP</li><li><strong> Course 11: </strong>Deep Learning &amp; Neural Networks Python - Keras</li></ul><p>Take control of your career trajectory and join the growing community of Python developers-enrol today!</p><p><strong>Learning Outcomes of Python Programming</strong></p><ul><li>Understand the basics of Python and its environment setup.</li><li>Get a deep understanding of Python data types and operators.</li><li>Master Python's fundamental data structures including lists, dictionaries, and tuples.</li><li>Learn how to control the flow of Python programs through conditional statements and loops.</li><li>Develop a solid understanding of Python syntax and readability.</li><li>Acquire a comprehensive foundational knowledge of Python.</li><li>Establish a solid stepping stone for advanced Python topics and related fields.</li></ul><p><strong>Why Choose Our Bundle?</strong></p><ul><li>Get a <strong>free QLS endorsed Certificate</strong> upon completion of this Bundle</li><li>Get a free student ID card with this Bundle</li><li>Get instant access to this Bundle course.</li><li>Learn from anywhere in the world</li><li>This Bundle is affordable and simple to understand</li><li>This Bundle is an entirely online, interactive lesson with voiceover audio</li><li>Lifetime access to this Bundle of course materials</li><li>This Bundle Programming comes with 24/7 tutor support</li></ul> <p><strong>Start your learning journey straightaway!</strong></p><p>This Bundle curriculum has been designed by Python Programming experts with years of Python Programming experience behind them. The Bundle course is extremely dynamic and well-paced to help you understand the Bundle with ease. You'll discover how to master the Python Programming skill while exploring relevant and essential topics.</p><p><strong>Assessment Process</strong></p><p>You have to complete the assignment questions given at the end of the course and score a minimum of<strong> 60%</strong> to pass each exam. After passing the <strong>Diploma in Python for Beginners Part 1 at QLS Level 5</strong> exam, you will be able to request a certificate endorsed by the <strong>Quality Licence Scheme</strong> absolutely <strong>FREE of cost</strong>.</p> <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 bundle is suitable for everyone.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

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

                        <div id="career_path">
                            <p>This bundle will allow you to kickstart or take your career in the related sector to the next stage.</p><ul><li>Python Developer</li><li>Data Analyst</li><li>Machine Learning Engineer</li><li>Web Developer</li><li>Data Scientist</li><li>Software Engineer</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

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

                        </div>

Learning & Development

Managed Learning Programme (MLP)

Trainers Course

Diploma in Professional Studies (DPS)

ICDL (International Certification of Digital Literacy)

Level 5 Diploma in Python Programming - QLS Endorsed

<p><strong>Start Your Journey to Becoming a Data Analyst Expert Today, and Make Up to •75,000<br /></strong><br />The <strong>data analytics</strong> field is growing rapidly, and there is a high demand for qualified data analysts. With our Data Analyst Program, you can learn the skills you need to succeed in this exciting field. We will help you until you find a job, so you won't have to worry about a thing. Just gain knowledge and learn skills, getting you a job is our duty. Enrol today and take your career to the next level!</p><p>With our program, we go above and beyond traditional training. We understand that landing a job isn't just about having the right skills-<strong>it's about having the right support system by your side</strong>. That's why we are committed to being with you every step of the way, from your <strong>job search</strong> to your ultimate success<strong>.</strong><br /><br /></p><p><strong>Why Choose Us</strong></p><p>Here's what makes our Data Analyst Program stand out from the crowd:</p><ul><li><strong>Personalised Job Search Assistance:</strong> We're in this together! Our dedicated team will work tirelessly to support your entire job searching process. From crafting a standout resume to submitting it to top companies, we'll ensure you have a compelling application that gets noticed.</li></ul><ul><li><strong>Expertly Crafted CV:</strong> Your resume is your ticket to the interview room. Our professional resume writers will create a customised CV highlighting your unique skills and experiences. This will maximise your chances of standing out among the competition.</li></ul><ul><li><strong>Strategic Placement:</strong> We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals.</li></ul><ul><li><strong>One-On-One Consultation Sessions with Industry Experts:</strong> Gain invaluable insights and guidance from seasoned professionals who have thrived in the data analysis field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and finesse.</li></ul><ul><li><strong>Comprehensive Skill Development:</strong> Our program is designed to equip you with the most sought-after skills in data analysis. From mastering cutting-edge tools to honing your analytical prowess, we'll ensure you have the knowledge and expertise to excel in any data-driven environment.</li></ul><p><strong>Here are the 25 courses we will provide once you enrol in the program:</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>These courses will help you to develop your knowledge and skills to become a successful data analyst.</p> <p>The Program is completed in 5 easy steps:</p><p><strong>Step 1 - Enrol in the program and start learning from the courses we provide</strong></p><p>After you enrol in the Data Analyst Program, you will get lifetime access to 25 premium courses related to data analysis. These courses will teach you the knowledge and skills required to become a successful data analyst. Our customer service team will help you and keep in contact with you every step of the way.</p><p><strong>Step 2 - Complete your courses and get certifications</strong></p><p>After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks for the first course and 80% for the rest relevant courses. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.</p><p><strong>Step 3 - Get a consultation session from a professional data analyst</strong></p><p>Take your data analysis skills to new heights with a one-on-one consultation session led by a seasoned professional. Gain invaluable insights, expert tips, and tailored advice that will propel your career forward.</p><p><strong>Step 4 - Complete the CV and attend the interview</strong></p><p>Once you've successfully obtained the certifications, our team of professionals will build you a compelling CV and LinkedIn profile. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. Kickstart your IT career with a starting salary ranging from •25,000 to •40,000 annually. Step into the IT industry with the assurance of a promising future.</p><p><strong>Step 5 - We will not leave you until you get a job</strong></p><p>Our commitment to your success goes above and beyond. We won't stop until you land that dream job. With personalised support, expert guidance, and unwavering dedication, we'll be by your side until you secure the perfect opportunity. Your job search becomes our mission, ensuring you have the best chance at a successful career in data analysis.</p><p>Don't let your dream career as a data analyst remain out of reach. You just have to learn and gain knowledge and skills. Finding a job is our task! We will remove most of your worries and help you focus on only developing your skills. So join our Data Analyst Program today, and let us be your trusted partner on your journey to success.</p> <h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                            <p>This Data Analyst Program is ideal for:</p><ul><li>Aspiring data analysts eager to launch a successful career in the field.</li><li>Recent graduates seeking practical skills and industry insights to stand out in a competitive job market.</li><li>Professionals looking to transition into the dynamic world of data analysis and capitalise on emerging opportunities.</li><li>Individuals with a passion for numbers, problem-solving, and uncovering meaningful insights from complex datasets.</li><li>Job seekers seeking comprehensive support and guidance throughout the entire job searching and job finding process.</li></ul><p><strong>Please Note</strong>: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

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

                        <div id="career_path">
                            <p>Our Data Analyst Program equips you with the skills to excel in data analysis roles. You'll thrive as a data analyst, data scientist, business analyst, or market research analyst, unlocking opportunities in diverse industries such as finance, healthcare, e-commerce, and technology.</p><p>Act now, and let us guide you towards a brighter future. Enrol today!</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited e-Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Framed (Hardcopy) Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Enrolment Letter</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Student ID Card</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>The Quality Licence Scheme Endorsed Certificate of Achievement</h4>
        <p>
            Hard copy certificate -
            Included
        </p>

                        </div>

Business Analyst

Business Analytics & Intelligence

Data Engineering

Big Data Analytics

Data Science

Data Analyst

Certified Data Analyst Pathway  - Job Ready Program with Career & Money Back Guarantee

<p><strong>***24 Hour Limited Time Flash Sale***</strong><strong></strong></p><p><strong>Advanced Computer Science Admission Gifts </strong></p><p><strong> FREE PDF &amp; Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter</strong></p><p>Are you a professional feeling stuck in your career, struggling to keep up with the ever-changing demands of the industry? Or perhaps you're a beginner, unsure of where to start or how to break into your desired field. Whichever stage you're in, our exclusive Advanced Computer Science Bundle provides unique insights and tools that can help you achieve your goals.</p><p>Designed to cater to the needs of both seasoned professionals and aspiring newcomers, our Advanced Computer Science bundle is a comprehensive program that will equip you with the essential skills and knowledge you need to succeed. Whether you're looking to advance in your current role or embark on a new career journey, this bundle has everything you need to take your professional life to the next level.</p><p><strong>But that's not all. When you enrol in Advanced Computer Science Online Training, you'll receive 30 CPD-Accredited PDF Certificates, Hard Copy Certificates, and our exclusive student ID card, all absolutely free.</strong></p><p><strong>Courses Are Included In this Advanced Computer Science Career Bundle:</strong></p><ul><li><strong>Course 01: </strong>Computer Science With Python</li><li><strong>Course 02: </strong>Python Programming for Everybody</li><li><strong>Course 03: </strong>C++ Development: The Complete Coding Guide</li><li><strong>Course 04: </strong>Coding with HTML, CSS, &amp; Javascript</li><li><strong>Course 05: </strong>JavaScript Foundations for Everyone</li><li><strong>Course 06: </strong>SQL Programming Masterclass</li><li><strong>Course 07: </strong>SQL for Data Science, Data Analytics and Data Visualization</li><li><strong>Course 08: </strong>Ionic &amp; Angular JS: Mobile and Web Development</li><li><strong>Course 09: </strong>Secure Programming of Web Applications - Developers and TPMs</li><li><strong>Course 10: </strong>Web Application Penetration Testing</li><li><strong>Course 11: </strong>Diploma in CompTIA Network+ Training Level 7</li><li><strong>Course 12: </strong>CompTIA PenTest+ (Ethical Hacking)</li><li><strong>Course 13: </strong>Cloud Computing / CompTIA Cloud+ (CV0-002)</li><li><strong>Course 14: </strong>R Programming for Data Science</li><li><strong>Course 15: </strong>Quick Data Science Approach from Scratch</li><li><strong>Course 16: </strong>Ionic &amp; Angular JS: Mobile and Web Development</li><li><strong>Course 17: </strong>Machine Learning with Python Course</li><li><strong>Course 18: </strong>Spatial Data Visualization and Machine Learning in Python</li><li><strong>Course 19: </strong>Azure Machine Learning</li><li><strong>Course 20: </strong>Hands on Machine Learning Project - Auto Image Captioning for Social Media</li><li><strong>Course 21: </strong>JavaScript Project - Game Development with JS</li><li><strong>Course 22: </strong>Ultimate PHP &amp; MySQL Web Development &amp; OOP Coding</li><li><strong>Course 23: </strong>Masterclass Bootstrap 5 Course - Responsive Web Design</li><li><strong>Course 24: </strong>Diploma in User Experience UI/UX Design (Advanced)</li><li><strong>Course 25: </strong>Foundations of Artificial Intelligence</li><li><strong>Course 26: </strong>Project on Deep Learning - Artificial Neural Network</li><li><strong>Course 27: </strong>Encryption</li><li><strong>Course 28: </strong>Advanced Training on Windows 10</li><li><strong>Course 29: </strong>Advance Windows 10 Troubleshooting for IT HelpDesk</li><li><strong>Course 30: </strong>Linux</li></ul><p>With Advanced Computer Science, you'll embark on an immersive learning experience that combines interactive lessons with voice-over audio, ensuring that you can learn from anywhere in the world, at your own pace. And with 24/7 tutor support, you'll never feel alone in your journey, whether you're a seasoned professional or a beginner.</p><p>Don't let this opportunity pass you by. Enrol in Advanced Computer Science today and take the first step towards achieving your goals and dreams.</p><p><strong>Why buy this Advanced Computer Science?</strong></p><ul><li><strong>Free CPD Accredited Certificate</strong> upon completion of Advanced Computer Science</li><li>Get <strong>a free student ID card</strong> with Advanced Computer Science</li><li><strong>Lifetime access</strong> to the Advanced Computer Science course materials</li><li>Get instant access to this Advanced Computer Science course</li><li>Learn Advanced Computer Science from anywhere in the world</li><li>24/7 tutor support with the Advanced Computer Science course.</li></ul> <p><strong>Start your learning journey straightaway with our Advanced Computer Science Training!</strong></p><p>Advanced Computer Science premium bundle consists of 30 precisely chosen courses on a wide range of topics essential for anyone looking to excel in this field. Each segment of Advanced Computer Science is meticulously designed to maximise learning and engagement, blending interactive content and audio-visual modules for a truly immersive experience.</p><p><strong>Certification</strong></p><p>You have to complete the assignment given at the end of the Advanced Computer Science course. After passing the Advanced Computer Science exam You will be entitled to claim a PDF &amp; Hardcopy certificate accredited by CPD Quality standards completely free.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        300 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><strong>This Advanced Computer Science course is ideal for:</strong></p><ul><li>Students seeking mastery in Advanced Computer Science</li><li>Professionals seeking to enhance Advanced Computer Science skills</li><li>Individuals looking for a Advanced Computer Science-related career.</li><li>Anyone passionate about Advanced Computer Science</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This <strong>Advanced Computer Science</strong> doesn't require prior experience and is suitable for diverse learners.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This <strong>Advanced Computer Science</strong> bundle will allow you to kickstart or take your career in the related sector to the next stage.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Digital certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Hard copy certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>If you are an <strong>international student</strong>, then you have to pay an additional <strong>10 GBP</strong> for each certificate as an international delivery charge.</p></div>

                        </div>

Computer Science (CS)

Advanced Computer Science

<p><strong>***24 Hour Limited Time Flash Sale***<br /><br /></strong><strong> Coding (C++, Python &amp; JavaScript) Admission Gifts <br /><br /></strong><strong> FREE PDF &amp; Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter</strong></p><p>Do you dream of building websites, creating games, or analysing data? In the UK, the digital sector is booming, with over <strong>2 million tech jobs</strong> and a projected growth of <strong>3%</strong> per year. If you're ready to join the wave, this <strong>Coding Bundle</strong> is your launchpad! Whether you're a complete beginner or have some experience, this comprehensive coding programme equips you with the in-demand skills to thrive in the digital world.</p><p>This <strong>Coding (C++, Python &amp; JavaScript)</strong> bundle offers a structured learning journey across three powerhouse languages: JavaScript, C++, and Python. Learn the fundamentals with beginner-friendly coding courses, then focus on advanced concepts like web application security, game development, data visualisation, and machine learning.</p><p><strong>But that's not all. When you enrol in Coding (C++, Python &amp; JavaScript) Online Training, you'll receive 25 CPD-Accredited PDF Certificates, Hard Copy Certificates, and our exclusive student ID card, all absolutely free.</strong></p><p><strong>Courses Are Included In this Coding (C++, Python &amp; JavaScript) Career Bundle:</strong></p><ul><li><strong>Course 01: </strong>Coding Essentials - Javascript, ASP. Net, C# - Bonus HTML</li><li><strong>Course 02: </strong>C++ Programming for Absolute Beginners</li><li><strong>Course 03: </strong>C++ Development: The Complete Coding Guide</li><li><strong>Course 04: </strong>Game Development using Cocos2d-x v3 C++</li><li><strong>Course 05: </strong>Tic-Tac-Toe Clone - The Complete Cocos2d-x C++ Game Course</li><li><strong>Course 06: </strong>Flappy Bird Clone: SFML C++ Game</li><li><strong>Course 07: </strong>Secure Programming of Web Applications</li><li><strong>Course 08: </strong>Python Basic Programming for Absolute Beginners</li><li><strong>Course 09: </strong>Python Programming Bible</li><li><strong>Course 10: </strong>Python Masterclass: Advanced Diploma</li><li><strong>Course 11: </strong>Machine Learning with Python Course</li><li><strong>Course 12: </strong>Python Programming from Scratch with My SQL Database</li><li><strong>Course 13: </strong>JavaScript Foundations for Everyone</li><li><strong>Course 14: </strong>JavaScript Advanced Training</li><li><strong>Course 15: </strong>Master JavaScript with Data Visualization</li><li><strong>Course 16: </strong>JavaScript Project Development - Creating Web Apps</li><li><strong>Course 17: </strong>Understanding Data Protection and Data Security</li><li><strong>Course 18: </strong>Computer Networks Security from Scratch to Advanced</li><li><strong>Course 19: </strong>Essential IT Skills Level 2</li><li><strong>Course 20: </strong>IT Support Technician</li><li><strong>Course 21: </strong>Functional Skills IT</li><li><strong>Course 22: </strong>Basics of Network Security</li><li><strong>Course 23: </strong>IT: Ethical Hacking &amp; IT Security</li><li><strong>Course 24: </strong>Learning Computers and Internet</li><li><strong>Course 25: </strong>Internet of Things</li></ul><p>With Coding (C++, Python &amp; JavaScript), you'll embark on an immersive learning experience that combines interactive lessons with voice-over audio, ensuring that you can learn from anywhere in the world, at your own pace. And with 24/7 tutor support, you'll never feel alone in your journey, whether you're a seasoned professional or a beginner.</p><p><strong>Learning Outcomes of this Bundle</strong></p><ul><li>Grasp core coding principles in JavaScript, Python, and C++.</li><li>Build functional web applications using ASP.Net and JavaScript.</li><li>Develop engaging games with Cocos2d-x and SFML.</li><li>Leverage Python for data analysis and machine learning.</li><li>Implement secure coding practices for web applications.</li><li>Confidently navigate the vast world of coding with expert guidance.</li></ul><p>Don't let coding skills hold you back from your dream career. <strong>Enrol in Coding (C++, Python &amp; JavaScript) today</strong> and take the first step towards achieving your goals and dreams.</p><p><strong>Why buy this Coding (C++, Python &amp; JavaScript)?</strong></p><ul><li><strong>Free CPD Accredited Certificate</strong> upon completion of this Bundle</li><li>Get <strong>a free student ID card</strong> with this Bundle</li><li><strong>Lifetime access</strong> to the course materials</li><li>Get instant access to this Bundle course</li><li>Learn from anywhere in the world</li><li>24/7 tutor support with this Bundle course.</li></ul> <p><strong>Start your learning journey straightaway with our Coding (C++, Python &amp; JavaScript) Training!</strong></p><p>Coding (C++, Python &amp; JavaScript) premium bundle consists of 25 precisely chosen courses on a wide range of topics essential for anyone looking to excel in this field. Each segment of Coding (C++, Python &amp; JavaScript) is meticulously designed to maximise learning and engagement, blending interactive content and audio-visual modules for a truly immersive experience.</p><p><strong>Certification of Coding (C++, Python &amp; JavaScript)<br /></strong></p><p>You have to complete the assignment given at the end of the Coding (C++, Python &amp; JavaScript) course. After passing the Coding (C++, Python &amp; JavaScript) exam You will be entitled to claim a PDF &amp; Hardcopy certificate accredited by CPD Quality standards completely free.</p> <h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                            <p>This Coding (C++, Python &amp; JavaScript) course is ideal for:</p><ul><li>Students seeking mastery in Coding (C++, Python &amp; JavaScript)</li><li>Professionals seeking to enhance Coding (C++, Python &amp; JavaScript) skills</li><li>Individuals looking for a Coding (C++, Python &amp; JavaScript)-related career.</li><li>Anyone passionate about Coding (C++, Python &amp; JavaScript)</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This Coding (C++, Python &amp; JavaScript) doesn't require prior experience and is suitable for diverse learners.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Coding (C++, Python &amp; JavaScript) bundle will allow you to kickstart or take your career in the related sector to the next stage.</p><ul><li>Web Developer</li><li>Data Analyst</li><li>Software Engineer</li><li>Game Developer</li><li>Machine Learning Engineer</li><li>Full-Stack Developer</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Digital Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Hard copy certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>If you are an <strong>international student</strong>, then you have to pay an additional <strong>10 GBP</strong> for each certificate as an international delivery charge.</p></div>

                        </div>

Coding For Kids

Coding (C++, Python & JavaScript)

<p><strong>24 Hours Left! Don't Let Winter Sale Slip Away - Enrol Now!</strong></p><p><strong>With over 100,000 civil engineers in the UK, the demand for data-savvy professionals is high. According to a recent study, 72% of UK civil engineering firms are investing in data analytics to enhance decision-making processes, with data engineering experiencing a 40% year-on-year growth.</strong></p><p>This surge outpaces other tech sectors, highlighting the critical role of data engineers in big data and advanced analytics. This Data Engineering bundle empowers you to capitalise on this growing trend, equipping you with the proficiency to extract valuable insights from vast datasets, optimise project planning, and enhance overall efficiency.</p><p>Embark on a transformative journey with our Data Engineering Bundle, thoroughly crafted to bridge the skill gap in one of the UK's fastest-growing job markets. Our bundle offers a comprehensive exploration into the world of data, equipping you with the analytical prowess to harness, process, and visualise data effectively. From mastering SQL programming to delving into the complexities of machine learning with R, this bundle is your gateway to becoming a data engineering maestro.</p><p>In today's data-driven landscape, possessing a robust set of analytical skills is no longer a luxury but a necessity. With an emphasis on Data engineering, our courses are designed to foster a deep understanding of data analytics, visualisation, and mining, ensuring you can convert raw data into strategic insights that propel business decisions.</p><p>Seize the opportunity to be at the helm of innovation and become the architect of tomorrow's data landscape with our Data Engineering Bundle. Join us now!</p><p><strong>Courses are Included in This Data Engineering Bundle:</strong></p><ul><li><strong> Course 01: </strong>Introduction to Data Analysis</li><li><strong> Course 02: </strong>Data Science &amp; Machine Learning with R</li><li><strong> Course 03: </strong>Data Analytics with Tableau</li><li><strong> Course 04: </strong>SQL Programming Masterclass</li><li><strong> Course 05: </strong>Excel Pivot table for Data analytics</li><li><strong> Course 06: </strong>Data analytics with Excel</li><li><strong> Course 07: </strong>Python for Data Analysis</li><li><strong> Course 08: </strong>Basic Google Data Studio</li><li><strong> Course 09: </strong>Business Intelligence and Data Mining Masterclass</li><li><strong> Course 10: </strong>Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li><strong> Course 11: </strong>JavaScript Functions for Data Analyst</li><li><strong> Course 12: </strong>GDPR Data Protection Level 5</li><li><strong> Course 13: </strong>GDPR Training</li><li><strong> Course 14: </strong>Learn Programming with Python</li><li><strong> Course 15: </strong>Data Center Training Essentials: General Introduction</li><li><strong> Course 16: </strong>Quick Data Science Approach from Scratch</li><li><strong> Course 17: </strong>Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li><strong> Course 18: </strong>Master JavaScript with Data Visualization</li><li><strong> Course 19: </strong>Excel Data Tools and Data Management</li><li><strong> Course 20: </strong>Cloud Computing Essentials for Data Analysis</li></ul><p><strong>Learning Outcomes of Data Engineering Bundle:</strong></p><ul><li>Gain proficiency in SQL for complex database management and analytics tasks.</li><li>Master R for data science and machine learning applications in various industries.</li><li>Develop advanced Excel skills, including data analytics and pivot table expertise.</li><li>Acquire hands-on experience with Tableau for effective data visualisation.</li><li>Learn Python programming essentials for data analysis and engineering solutions.</li><li>Understand Google Data Studio to create dynamic reports and dashboards.</li></ul><p><strong>Why Choose Our Data Engineering Course?</strong></p><ul><li>FREE Data Engineering certificate accredited</li><li>Get a free student ID card with Data Engineering Training</li><li>Get instant access to this Data Engineering course.</li><li>Learn Data Engineering from anywhere in the world</li><li>The Data Engineering is affordable and simple to understand</li><li>The Data Engineering is an entirely online, interactive lesson with voiceover audio</li><li>Lifetime access to the Data Engineering course materials</li><li>The Data Engineering comes with 24/7 tutor support</li></ul> <p><strong>Start your learning journey straightaway with our Data Engineering Bundle!</strong></p><p>This Data Engineering bundle will equip you with the skills and knowledge to become a data-savvy civil engineer. You will learn how to collect, analyze, and interpret data to improve infrastructure projects and processes. This Data Engineering bundle includes courses on data analysis, data science, machine learning, SQL programming, Excel pivot tables, Excel data analytics, Python for data analysis, Google Data Studio, business intelligence, data mining, GDPR data protection, JavaScript functions for data analysts, and Python programming.</p><p><strong>Assessment Process of Data Engineering</strong></p><p>Once you have completed all the courses in the Data Engineering bundle, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        200 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 Engineering bundle is suitable for everyone. Also, our Data Engineering Bundle is perfect for:</p><ul><li>Aspiring data engineers</li><li>Business intelligence analysts</li><li>Data-driven marketers</li><li>IT professionals</li><li>Statistics enthusiasts</li><li>Career changers</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise in the Data Engineering Bundle.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Data Engineering bundle will allow you to kickstart or take your career to the next stage in the related sector such as:</p><ul><li><strong>Data Analyst</strong></li><li><strong>BI Developer</strong></li><li><strong>ML Engineer</strong></li><li><strong>Data Scientist</strong></li><li><strong>Database Administrator</strong></li><li><strong>Data Strategist</strong></li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Digital Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>If you are an <strong>international student</strong>, then you have to pay an additional <strong>10 GBP</strong> for each certificate as an international delivery charge.</p></div>

                        </div>

Data Engineering - 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

Packt

Python

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

Python Machine Learning Bootcamp

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

Machine Learning with Real World Projects

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			<h2><b>Course Overview</b></h2>		</div>
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					<div><p><span>Machine learning as a programming technique has shaped the future of technology. In this course, you will learn how to build intelligent handwriting recognition apps from scratch using Python and Core ML.</span></p><p><span>The </span><b>Machine Learning for Apps Level 4 </b><span>course will teach you how to take advantage of machine learning to code like a pro and build incredible apps that can make predictions. Designed by industry experts, it covers best practices for managing projects, core concepts for creating your own ML model, building a convolutional neural network, and much more.</span></p><p><span>On successful completion, you will be able to build an amazing handwriting recognition app and convolutional neural network from scratch, and have an in-depth understanding of the core ML basics. This course is ideal for those with a basic understanding of iOS development.</span></p></div>
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					<div><p>This best selling <strong>Machine Learning for Apps Level 4 </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Machine Learning for Apps Level 4 </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The <strong>Machine Learning for Apps Level 4 </strong>is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The <strong>Machine Learning for Apps Level 4 </strong>is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p><p>After successfully completing the<strong> Machine Learning for Apps Level 4</strong>, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the <strong>Machine Learning for Apps Level 4 </strong>will help you stand out from the crowd. You can also validate your certification on our website.</p><p>We know that you are busy and that time is precious, so we have designed the <strong>Machine Learning for Apps Level 4 </strong>to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p><p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Course Cloud

Machine Learning (ML)

Machine Learning for Apps Level 4

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

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

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

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

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

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

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

Python Machine Learning Crash Course for Beginners

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

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

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

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

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

Machine Learning 101 with Scikit-learn and StatsModels

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

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

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

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

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

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

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

Machine Learning for Absolute Beginners - Level 2

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

TensorFlow

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

The Complete Machine Learning Course with Python

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

Machine Learning - Use in Flutter

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

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

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

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

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

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

Deep Learning

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

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