Name: Hands on Deep Learning Projects - Stock price Prognostics Course
Price: 12 GBP
Availability: InStock

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			<h4>Overview</h4>		</div>
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							<p><span>By enroling in Foundations of Artificial Intelligence, you can kickstart your vibrant career and strengthen your profound knowledge. You can learn everything you need to know about the topic.</span></p><p><span>The Foundations of Artificial Intelligence course includes all of the most recent information to keep you abreast of the employment market and prepare you for your future. The curriculum for this excellent Foundations of Artificial Intelligence course includes modules at all skill levels, from beginner to expert. You will have the productivity necessary to succeed in your organisation once you have completed our Foundations of Artificial Intelligence Program.</span></p><p><span>So enrol in our Foundations of Artificial Intelligence course right away if you're keen to envision yourself in a rewarding career.</span></p>						</div>
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			<h4>Description</h4>		</div>
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							<p><span>Enroling in this Foundations of Artificial Intelligence course can improve your Foundations of Artificial Intelligence perspective, regardless of your skill levels in the Foundations of Artificial Intelligence topics you want to master. If you're already a Foundations of Artificial Intelligence expert, this peek under the hood will provide you with suggestions for accelerating your learning, including advanced Foundations of Artificial Intelligence insights that will help you make the most of your time. This Foundations of Artificial Intelligence course will act as a guide for you if you've ever wished to excel at Foundations of Artificial Intelligence.</span></p>						</div>
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			<h4>Why Choose Us?</h4>		</div>
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										<span>This course is accredited by the CPD Quality Standards.</span>
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										<span>Lifetime access to the whole collection of the learning materials.</span>
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										<span>Online test with immediate results.</span>
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										<span>Enroling in the course has no additional cost.</span>
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										<span>You can study and complete the course at your own pace.</span>
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										<span>Study for the course using any internet-connected device, such as a computer, tablet, or mobile device.</span>
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			<h4>Certificate of Achievement</h4>		</div>
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							<p>Upon successful completion, you will qualify for the UK and internationally-recognised CPD certificate and you can choose to make your achievement formal by obtaining your PDF Certificate at a cost of £4.99 and Hardcopy Certificate for £9.99.</p>						</div>
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			<h4>Who Is This Course For?</h4>		</div>
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							<p><span>This Foundations of Artificial Intelligence course is a great place to start if you're looking to start a new career in Foundations of Artificial Intelligence field. This training is for anyone interested in gaining in-demand Foundations of Artificial Intelligence proficiency to help launch a career or their business aptitude. </span></p>						</div>
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			<h4>Requirements</h4>		</div>
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							<p><span>The Foundations of Artificial Intelligence course requires no prior degree or experience. All you require is English proficiency, numeracy literacy and a gadget with stable internet connection. Learn and train for a prosperous career in the thriving and fast-growing industry of Foundations of Artificial Intelligence, without any fuss.</span></p>						</div>
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			<h4>Career Path</h4>		</div>
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							<p><span>This Foundations of Artificial Intelligence training will assist you develop your Foundations of Artificial Intelligence ability, establish a personal brand, and present a portfolio of relevant talents. It will help you articulate a  Foundations of Artificial Intelligence professional story and personalise your path to a new career. Furthermore, developing this Foundations of Artificial Intelligence skillset can lead to numerous opportunities for high-paying jobs in a variety of fields.</span></p>						</div>
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			<h4>Order Your Certificate</h4>		</div>
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							<div><div><div><div id="1693981461.590199"><div><div><div><div><div><div><div><div><div><div><div>To order CPD Quality Standard Certificate, we kindly invite you to visit the following link:</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>						</div>
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	<span>Course Curriculum</span>
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					<td colspan="4">Module 01: Introduction To Artificial Intelligence</td>
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					<td>Introduction to Artificial Intelligence</td>
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					<td><span><i></i> 00:21:00</span></td>
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					<td colspan="4">Module 02: Mathematics For AI</td>
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					<td>Mathematics for AI</td>
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					<td><span><i></i> 00:17:00</span></td>
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					<td colspan="4">Module 3: Knowledge Representation In AI - Part 1</td>
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					<td>Knowledge Representation in AI - Part 1</td>
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					<td><span><i></i> 00:18:00</span></td>
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					<td colspan="4">Module 4: Knowledge Representation In AI - Part 2</td>
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					<td>Knowledge Representation in AI - Part 2</td>
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					<td><span><i></i> 00:16:00</span></td>
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					<td colspan="4">Module 5: Machine Learning - Part 1</td>
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					<td><span><i></i> 00:16:00</span></td>
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					<td><span><i></i> 00:15:00</span></td>
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					<td><span><i></i> 00:14:00</span></td>
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					<td colspan="4">Module 10: Robotics</td>
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					<td><span><i></i> 00:18:00</span></td>
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					<td colspan="4">Module 11: Building AI Applications</td>
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					<td>Building AI Applications</td>
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					<td><span><i></i> 00:24:00</span></td>
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					<td colspan="4">Order Your Certificate</td>
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NextGen Learning

Foundations of Artificial Intelligence Course

General Admission

<p>Python is a powerful and versatile programming language that's widely used in the world of data science and machine learning. In this Python for Beginners course, you will learn the fundamentals of Python programming, including data types, data structures, control flow, and more. By the end of the course, you will have a solid foundation in Python that will enable you to tackle more complex projects in the future.</p><p><strong>Learning outcomes:</strong></p><ul><li>Understand the basic concepts of programming using Python</li><li>Know how to install and set up a Python development environment</li><li>Learn about data types and operators in Python</li><li>Understand the various data structures available in Python</li><li>Learn how to use control flow constructs in Python to make decisions and repeat actions</li><li>Gain the ability to write simple Python programs from scratch</li></ul><p>Python for Beginners Part 1 is a comprehensive course designed for anyone who wants to learn the basics of Python programming. The course is structured into five modules, each focusing on a specific area of Python programming. You will start by learning about the basics of programming and setting up a Python development environment. From there, you will move on to topics such as data types, data structures, and control flow.</p><p>Throughout the course, you will have access to interactive exercises and quizzes that will help you reinforce your learning. By the end of the course, you will have a solid understanding of Python programming and the ability to write your own simple programs.</p><p>If you're new to programming or just starting out with Python, this course is the perfect place to begin. With clear, concise explanations and plenty of examples, you'll be up and running with Python in no time.</p><p><strong>Certification</strong></p><p>Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations.</p><h2>
        
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                                        10 CPD hours / points
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                                            Accredited by CPD Quality Standards
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        <div>Who is this course for?</div>
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                            <ul><li>Individuals who are new to programming</li><li>Professionals who want to learn Python for data science or machine learning</li><li>Students who want to gain a fundamental understanding of Python programming</li><li>Anyone who wants to add a valuable skill to their resume</li></ul>
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        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Python Developer: £30,000 - £75,000 per year</li><li>Data Analyst: £24,000 - £46,000 per year</li><li>Machine Learning Engineer: £35,000 - £85,000 per year</li><li>Software Engineer: £24,000 - £70,000 per year</li><li>Full Stack Developer: £28,000 - £70,000 per year</li><li>Artificial Intelligence Developer: £35,000 - £85,000 per year</li></ul>
                        </div>

Learn Python Programming from Scratch

<strong>Learn to make interactive apps using Swift 4.2 and Xcode 10 and have your own applications in the App Store in just 10 days</strong>
        <p>Looking to get started with creating fun and interactive apps? This course will equip you with the skills you need to create an app and submit it to the App Store in just 10 days. 

While other courses offer 40+ hours of video content, this quick and engaging course keeps it simple and manageable for beginners. On June 4 2018, Apple announced iOS 12, and the course is based on this latest version.  

Following a step-by-step approach, you will use Swift 4 and Xcode 10 to create exciting iOS 12 apps. 

Your ten-day schedule will look like this: 

&bull; Day 1 - Exploring the basics, such as writing your first line of Swift and getting started with Xcode 

&bull; Day 2 - Delving further into Swift and creating a Tip Calculator  

&bull; Day 3 - Learning about Table Views while creating an app to remember jokes - the Joke Bank app 

&bull; Day 4 - Understanding advanced Swift functions, classes, and methods and applying these skills to the Joke Bank App 

&bull; Day 5 - Creating a functional To-Do List app 

&bull; Day 6 - Adding Core Data to your To-Do app to save your items 

&bull; Day 7 - Adding images to an app and allowing users to take a photo 

&bull; Day 8 - Making a Bitcoin Price Tracker that connects with an API to display real-time Bitcoin prices 

&bull; Day 9 - Using the new Core ML 2 to learn the basics of machine learning 

&bull; Day 10 - Submitting your app to the App Store and learning how to make money with iOS 

This course can be downloaded easily so you can even use it offline.  

All code and supporting files for this course are available at - https://github.com/PacktPublishing/The-10-Day-iPhone-App-Bootcamp---New-iOS-12-and-Xcode</p>
        <h2>What You Will Learn</h2><p>Submit Your Own App to the App Store!<br>Become a Swift 4 Programmer<br>Industry Tips Such Asas How to Get a Job and Make Money from Your Apps<br>Create a Bitcoin Price Tracking App<br>Create a ToDo List App<br>Create a Joke Bank App<br>Create a Photo-Based Collector App<br>Create an App with Machine Learning</p>
        <h2>Audience</h2><p>This course is for people who want learn to build iPhone apps. Some programming experience is preferable.</p>
        <h2>Approach</h2><p>A comprehensive course packed with step-by-step instructions, working examples, and helpful advice. This course is divided into clear sections so you can learn at your own pace. <br><br>In each video, you'll delve straight into the topic. You'll only focus on the essentials and gain hands-on practice over a 10-day period, with 1-2 hours dedicated to learning each day.</p>
        <h2>Key Features</h2><p>Build real-world apps so that you can easily master the topics we are learning * Discover the essentials of Swift 4.2, Xcode 10 and iOS 12 with hands-on practice to build and publish your apps to the App store * Use Swift 4 and Xcode 10 to create iOS 12 apps in 10 days</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/the-10-day-iphone-app-bootcamp---new-ios-12-and-xcode</p>
        <h2>About the Author</h2><h3>Nick Walter</h3><p>Nick Walter is an experienced mobile and web developer and has worked with technologies such as iOS, Android, Django, and Python.

He learned to code about seven years ago. He had limited access to training resources back then. Whilst he learned to code, he also realized the need to change the way that people learn to code. That's when Nick took up teaching. His experience as an online student has definitely influenced his teaching style-he knows what it is like to be in their shoes.

He started his teaching career in 2014, with the Internet's first Swift course. He now teaches a range of technologies such as iOS, Android, Django, Kotlin, Python, HTML, and Blockchain.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><br><h4>2. DAY 1 - The Fundamentals</h4><p></p><br><h4>3. DAY 2 - More Swift</h4><p></p><br><h4>4. DAY 3 - Joke Bank App</h4><p></p><br><h4>5. DAY 4 - Advanced Swift</h4><p></p><br><h4>6. DAY 5 - ToDo List</h4><p></p><br><h4>7. DAY 6 - CoreData</h4><p></p><br><h4>8. DAY 7 - Images and the Camera</h4><p></p><br><h4>9. DAY 8 - Bitcoin Price Tracker</h4><p></p><br><h4>10. DAY 9 - Machine Learning</h4><p></p><br><h4>11. DAY 10 - App Store and Making Money</h4><p></p>

Packt

Swift

Mobile

Bootcamp

iOS Development

Xcode

Learn to make interactive apps using Swift 4.2 and Xcode 10 and have your own applications in the App Store in just 10 days

The 10 Day iPhone App Bootcamp - New iOS 12 and Xcode

<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> Software and Web Development</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> Software and Web Development</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>Software and Web Development</strong> bundle will help you build a solid foundation to become a proficient worker in the sector.</p> <p><strong>This Software and Web Development Bundle consists of the following</strong><strong> 30 </strong><strong>CPD Accredited Premium courses - </strong></p> <ul> <li>Course 1: C++ Development: The Complete Coding Guide</li><li>Course 2: Basic C# Coding</li><li>Course 3: Computer Vision: C++ and OpenCV with GPU support</li><li>Course 4: Python Basic Programming for Absolute Beginners</li><li>Course 5: Python Programming for Everybody</li><li>Course 6: Intermediate Python Coding</li><li>Course 7: Level-3 Machine Learning Course with Python</li><li>Course 8: Learn to Use Python for Spatial Analysis in ArcGIS</li><li>Course 9: Higher Order Functions in Python - Level 03</li><li>Course 10: Javascript Programming for Beginners</li><li>Course 11: Basic Asynchronous JavaScript</li><li>Course 12: JavaScript Functions</li><li>Course 13: JavaScript Promises</li><li>Course 14: JavaScript Foundations for Everyone</li><li>Course 15: JavaScript Masterclass: ES6 Modern Development</li><li>Course 16: jQuery Masterclass Course: JavaScript and AJAX Coding Bible</li><li>Course 17: Microsoft SQL Server Development for Everyone</li><li>Course 18: SQL Programming Masterclass</li><li>Course 19: SQL NoSQL Big Data and Hadoop</li><li>Course 20: Introduction to Data Analysis</li><li>Course 21: Data Science with Python</li><li>Course 22: Data Analytics with Tableau</li><li>Course 23: R Programming for Data Science</li><li>Course 24: Complete Google Analytics Course</li><li>Course 25: Quick Data Science Approach from Scratch</li><li>Course 26: Root Cause Analysis</li><li>Course 27: Google Data Studio: Data Analytics</li><li>Course 28: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li>Course 29: Business Intelligence and Data Mining Masterclass</li><li>Course 30: Need Another ONE COURSE</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 1:Career Development Plan Fundamentals</li><li>Course 2:CV Writing and Job Searching</li><li>Course 3:Interview Skills: Ace the Interview</li></ul> <p><strong>Learning Outcome</strong></p> <p><strong>This tailor-made </strong><strong>Software and Web Development</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 Software and Web Development 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 Software and Web Development 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 Software and Web Development</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

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Computing & Software Development Tools

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Continuous Professional Development (CPD)

Software and Web Development - CPD Accredited

<p>Looking to take your graphic design skills to the next level? Look no further than our Graphic Design: UI/UX, After Effects &amp; Canva bundle! Featuring not one, not two, but THREE QLS-endorsed courses, this bundle is sure to elevate your graphic design game and set you on the path to success.</p><p>After completing these courses, you'll receive hardcopy certificates to showcase your newfound expertise. Imagine impressing your clients or future employers with physical proof of your skills right in your hands.</p><p>But wait, there's more! We also offer FIVE CPD-QS accredited courses, covering everything from advanced graphic design to photo manipulation and motion graphics. Whether you're looking to expand your knowledge or enhance your career prospects, our courses are designed to help you succeed.</p><p>So what are you waiting for? Sign up for our Graphic Design: UI/UX, After Effects &amp; Canva bundle today and unlock your full potential as a graphic designer. With courses covering everything from user experience design to creative advertising and beyond, there's something for everyone in this exciting and comprehensive bundle. Don't miss out on this opportunity to take your career to the next level!</p><p><strong>QLS Endorsed Courses:</strong></p><ul><li><strong>Course 01: </strong>Certificate in Graphic Design- Colour Theory at QLS Level 3</li><li><strong>Course 02:</strong> Advanced Diploma in User Experience UI/UX Design at QLS Level 7</li><li><strong>Course 03: </strong>Award in Machine Learning Model Using AWS SageMaker Canvas at QLS Level 2</li></ul><p><strong>CPD QS Accredited Courses:</strong></p><ul><li><strong>Course 04: </strong>Complete After Effects for Graphic Design</li><li><strong>Course 05:</strong> Advanced Graphic Design Diploma Course</li><li><strong>Course 06: </strong>Creative Advertising and Graphic Design for Everyone</li><li><strong>Course 07: </strong>Photo Manipulation: Graphic Design Training</li><li><strong>Course 08:</strong> Create Videos, Motion Graphics and Animation Using Canva</li></ul><p>Take your career to the next level with our bundle that includes not only technical courses but also<strong> five guided courses</strong> focused on personal development and<strong> career growth</strong>.</p><ul><li><strong>Course 09:</strong> Career Development Plan Fundamentals</li><li><strong>Course 10: </strong>Networking Skills for Personal Success</li><li><strong>Course 11:</strong> Boost Your Confidence and Self-Esteem</li><li><strong>Course 12: </strong>Practical Time Management Masterclass</li><li><strong>Course 13: </strong>Training For Anxiety &amp; Stress Management</li></ul><p><strong>Learning Outcomes:</strong></p><ul><li>Learn to use Adobe After Effects to create stunning motion graphics and visual effects</li><li>Develop a thorough understanding of user experience (UX) design and learn to use Adobe XD to create intuitive, user-friendly interfaces</li><li>Master the art of graphic design using Canva, a popular and user-friendly design platform</li><li>Gain CPD-QS accreditation in relevant courses to boost your resume and career prospects</li><li>Learn to create videos and animations using Canva</li><li>Become proficient in photo manipulation and advanced graphic design techniques</li><li>Understand the basics of creative advertising and how to apply it to your design work</li></ul><p><strong>Please Note: </strong>Imperial Academy is One Education approved resale partner for Quality Licence Scheme Endorsed courses.</p><p>The Complete After Effects for Graphic Design course is an in-depth guide to using Adobe After Effects for motion graphics and visual effects. The User Experience Design from A-Z: Adobe XD UI/UX Design course will teach you everything you need to know about UX design and how to create intuitive, user-friendly interfaces using Adobe XD. Finally, the Graphic Design Using Canva course will teach you how to create stunning designs using Canva, a user-friendly design platform.</p><p><strong>Certificate</strong></p><p>QLS-endorsed courses are designed to provide learners with the skills and knowledge they need to succeed in their chosen field.<br /><strong>The Quality Licence Scheme</strong> is a distinguished and respected accreditation in the UK, denoting exceptional quality and excellence. It carries significant weight among industry professionals and recruiters.<br />Upon completion, learners will receive Three <strong>QLS Endorsed</strong> hard copy certificates, making it easy for them to showcase their achievements. These certificates validate their course completion, the level of the course they have completed, and the QLS endorsement.</p><h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                            <ul><li>Graphic designers looking to expand their skillset</li><li>Marketing professionals looking to create engaging visual content</li><li>Students interested in pursuing a career in graphic design</li></ul>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Graphic Designer: £20,000 - £45,000 per year</li><li>UX Designer: £25,000 - £65,000 per year</li><li>Art Director: £30,000 - £70,000 per year</li><li>Motion Graphics Designer: £25,000 - £50,000 per year</li><li>Marketing Manager: £25,000 - £60,000 per year</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

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

                        </div>

Imperial Academy

3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | 10 CPD Courses | Lifetime Access | 24/7 Tutor Support

Graphic Design: UI/UX, After Effects & Canva

<p><strong></strong><strong> 14 in 1 "IT and Analytics Training Training" Bundle only at £ 79 </strong><strong></strong></p><p><strong>Get Hard Copy + PDF Certificates + Transcript + Student ID Card + e-Learning App as a Gift - Enrol Now</strong></p><p>Tired of browsing and searching for a <strong>IT and Analytics Training </strong> course you are looking for? Can't find the complete Training package that fulfils all your needs? Then don't worry as you have just found the solution. Take a minute and look through this 14-in-1 extensive IT and Analytics Training bundle that has everything you need to succeed in IT and Analytics Training and other relevant fields!</p><p>After surveying thousands of learners just like you and considering their valuable feedback, this all-in<strong>-</strong>one Training bundle has been designed by industry experts. We prioritised what learners were looking for in a complete IT and Analytics Training package and developed this in-demand Training course that will enhance your skills and prepare you for the competitive job market.</p><p>Furthermore, to help you showcase your expertise in this Training, we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These Training certificates will enhance your credibility and encourage possible employers to pick you over the rest.</p><p><strong>This Bundle Consists of the following Premium courses: </strong></p><ul><li><strong></strong><strong> Course 01:</strong> Introduction to Data Analysis</li><li><strong></strong><strong> Course 02: </strong>Quick Data Science Approach from Scratch</li><li><strong></strong><strong> Course 03: </strong>Excel Pivot Tables</li><li><strong></strong><strong> Course 04: </strong>Google Data Studio: Data Analytics</li><li><strong></strong><strong> Course 05: </strong>Excel Pivot Tables, Pivot Charts, Slicers, and Timelines</li><li><strong></strong><strong> Course 06: </strong>Business Intelligence and Data Mining Masterclass</li><li><strong></strong><strong> Course 07: </strong>Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li><strong></strong><strong> Course 08: </strong>RCA: Root Cause Analysis</li><li><strong></strong><strong> Course 09: </strong>Master JavaScript with Data Visualization</li><li><strong></strong><strong> Course 10: </strong>CompTIA CySA+ Cybersecurity Analyst (CS0-002)</li><li><strong></strong><strong> Course 11: </strong>Electronic Document Management System Step</li><li><strong></strong><strong> Course 12:</strong> IT For Recruiters</li></ul><p>Enrol now to advance your career, and use the premium study materials from Apex Learning.</p><p><strong>Benefits you'll get from choosing Apex Learning for this </strong><strong>training</strong><strong>:</strong></p><ul><li>Pay once and get lifetime access to 14 CPD courses</li><li>Free e-Learning App for engaging reading materials &amp; helpful assistance</li><li>Certificates, student ID included in a one-time fee</li><li>Free up your time - don't waste time and money travelling for classes</li><li>Accessible, informative modules designed by expert instructors</li><li>Learn anytime, from anywhere</li><li>Study from your computer, tablet or mobile device</li><li>CPD accredited course - improve the chance of gaining professional skills</li></ul><p><strong>How will I get my Certificate?</strong></p><p>After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement.</p><ul><li><strong>PDF Certificate: Free (For The Title Course)</strong></li><li><strong>Hard Copy Certificate: Free (For The Title Course)</strong></li></ul><p><strong>Curriculum</strong></p><p><strong>Course 01: Introduction to Data Analysis</strong></p><ul><li>Module 01: Introduction</li><li>Module 02: Agenda and Principles of Process Management</li><li>Module 03: The Voice of the Process</li><li>Module 04: Working as One Team for Improvement</li><li>Module 05: Exercise: The Voice of the Customer</li><li>Module 06: Tools for Data Analysis</li><li>Module 07: The Pareto Chart</li><li>Module 08: The Histogram</li><li>Module 09: The Run Chart</li><li>Module 10: Exercise: Presenting Performance Data</li><li>Module 11: Understanding Variation</li><li>Module 12: The Control Chart</li><li>Module 13: Control Chart Example</li><li>Module 14: Control Chart Special Cases</li><li>Module 15: Interpreting the Control Chart</li><li>Module 16: Control Chart Exercise</li><li>Module 17: Strategies to Deal with Variation</li><li>Module 18: Using Data to Drive Improvement</li><li>Module 19: A Structure for Performance Measurement</li><li>Module 20: Data Analysis Exercise</li><li>Module 21: Course Project</li><li>Module 22: Test your Understanding</li></ul><p><strong>--------Other Courses Are--------</strong></p><p><strong>Course 02: Quick Data Science Approach from Scratch</strong></p><p><strong>Course 03: Excel Pivot Tables</strong></p><p><strong>Course 04: Google Data Studio: Data Analytics</strong></p><p><strong>Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines</strong></p><p><strong>Course 06: Business Intelligence and Data Mining Masterclass</strong></p><p><strong>Course 07: Statistics &amp; Probability for Data Science &amp; Machine Learning</strong></p><p><strong>Course 08: RCA: Root Cause Analysis</strong></p><p><strong>Course 09: Master JavaScript with Data Visualization</strong></p><p><strong>Course 10: CompTIA CySA+ Cybersecurity Analyst (CS0-002)</strong></p><p><strong>Course 11: Electronic Document Management System Step</strong></p><p><strong>Course 12: </strong><strong>IT For Recruiters</strong></p><h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                            <p>Anyone from any background can enrol in this IT and Analytics Training bundle including-</p><ul><li>Students</li><li>Graduates</li><li>Job Seekers</li><li>Job Holders</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>Our Training is fully compatible with PCs, Macs, laptops, tablets and Smartphone devices. This Training course has been designed to be fully compatible with tablets and smartphones, so you can access your course on Wi-Fi, 3G or 4G.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

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

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

                        </div>

Apex Learning

IT and Analytics Training

<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> Teach Yourself IT</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>30 </strong> course mega bundle that will exceed your expectations within your budget.</p> <p>The<strong> Teach Yourself IT</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>Teach Yourself IT</strong> bundle will help you build a solid foundation to become a proficient worker in the sector.</p> <p><strong>This Teach Yourself IT Bundle consists of the following</strong><strong> 25 </strong><strong>CPD Accredited Premium courses - </strong></p> <ul> <li>Course 1: Network Security and Risk Management</li><li>Course 2: CompTIA Network</li><li>Course 3: Information Management</li><li>Course 4: Web Application Penetration Testing Course</li><li>Course 5: CompTIA Cloud+ (CV0-002)</li><li>Course 6: Learn Ethical Hacking with Kali Linux</li><li>Course 7: Computer Operating System and Troubleshooting</li><li>Course 8: Building Your Own Computer Course</li><li>Course 9: It: Ethical Hacking, IT Security and IT Cyber Attacking</li><li>Course 10: SQL Database Administrator</li><li>Course 11: MS Word Essentials - The Complete Word Course - Level 3</li><li>Course 12: Data Protection (GDPR) Practitioner</li><li>Course 13: Website Hacking From Scratch</li><li>Course 14: Diploma in Front-End Web Development (HTML, CSS, &amp; Bootstrap)</li><li>Course 15: Data Science and Visualisation with Machine Learning</li><li>Course 16: SQL For Data Analytics &amp; Database Development</li><li>Course 17: PLC Programming Diploma</li><li>Course 18: Cisco ASA Firewall Training Course</li><li>Course 19: Create Your First Responsive Website</li><li>Course 20: C# (C-Sharp)</li><li>Course 21: Web Design (HTML, CSS, Bootstrap) Complete Course</li><li>Course 22: Python Course</li><li>Course 23: JavaScript</li><li>Course 24: Net MVC and Entity Framework Course</li><li>Course 25: Learn Spring &amp; Angular Material with a Full Web Application</li></ul> <p><strong>5 </strong><strong>Extraordinary Career Oriented courses that will assist you in reimagining your thriving techniques-</strong></p> <ul> <li>Course 1: Career Development Plan Fundamentals</li><li>Course 2: CV Writing and Job Searching</li><li>Course 3: Interview Skills: Ace the Interview</li><li>Course 4: Video Job Interview for Job Seekers</li><li>Course 5: Create a Professional LinkedIn Profile</li></ul> <p><strong>Learning Outcome</strong></p> <p><strong>This tailor-made </strong><strong>Teach Yourself IT</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 Teach Yourself IT 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 Teach Yourself IT training materials, you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for free. Original 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>
                                        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>Ambitious learners who want to strengthen their CV for their desired job should take advantage of the Teach Yourself IT 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 Teach Yourself IT</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>

Certificate in Teaching Program (CTP)

Certificate in Further Education & Training (Cert Ed)

IT Certifications

IT Skills

Teach Yourself IT - CPD Accredited

<p>Isn't it interesting that you searched for something on the internet and some relevant results appeared? Alternatively, you can enter your daily data into a health app that automatically recommends a diet and exercise routine for you. All of this would not have been possible without data science.</p><p>The modern world is entirely dependent on Machine Learning, Artificial Intelligence, Neural networks or data science in one phrase. Data science is a new field with no established leaders. It's too difficult to decide which one to learn, which leads to even more frustration because you can't make any progress. It is becoming more important, but the market for skilled data scientists is limited and competitive. What if you are one of those individuals?</p><p>If you have a background in maths or statistics, we have good news: you can become a data scientist with little training! Anyone can become a data scientist with the help of our Data Science courses. Whatever your background, this training will teach you how to analyse and interpret data to generate new insights that lead to better decisions and results. Our interactive materials set us apart and make us more effective for our students. So don't be late to take your place. Enrol now!</p><p><strong>Learning Outcomes</strong></p><ul><li>Understanding of the basic concepts and techniques in data science, such as data exploration, cleaning, and preprocessing</li><li>Knowledge of statistical analysis methods, including hypothesis testing, regression analysis</li><li>Learn probability theory and it's use in Data science</li><li>Knowledge of Advanced regression &amp; machine learning algorithms</li><li>Ability to communicate data science results effectively to a non-technical audience.</li></ul><p><strong>Key Highlights for Data Science Course:</strong></p><ul><li>Developed by industry experts</li><li>Instant e-certificate and hard copy dispatch by the next working day</li><li>Interactive course with audio voice-over</li><li>24/7 Learning Assistance</li><li>Lifetime access &amp; update without any limits</li><li>Unlimited Retake Exam and premium support for life</li><li>Easy Accessibility to the Course Materials- Anytime, Anywhere - From Any Smart Device (Laptop, Tablet, Smartphone Etc.)</li><li>100% Learning satisfaction guarantee</li><li>Covers to explore multiple job positions</li><li>One-stop solution for entrepreneurs and Jobseekers</li><li>Fastest growing sector</li><li>Boost your salary on program completion</li><li>Learn from diligent experts</li><li>Expert-verified response for quality education</li></ul><p><strong>So, You should not wait too long. Now is the time to enrol!</strong></p><p>Learn at your own pace from the comfort of your home, as the rich learning materials of this course are accessible from any place at any time. The curriculums are divided into tiny bite-sized modules by industry specialists. And you will get answers to all your queries from our experts.</p><p>So, enrol and excel in your career with Compliance Central.</p><p><strong>Curriculum Breakdown of the Course</strong></p><ul><li><strong>Section 01: </strong>Let's get started</li><li><strong>Section 02: </strong>Descriptive statistics</li><li><strong>Section 03: </strong>Distributions</li><li><strong>Section 04: </strong>Probability theory</li><li><strong>Section 05: </strong>Hypothesis testing</li><li><strong>Section 06: </strong>Regressions</li><li><strong>Section 07: </strong>Advanced regression &amp; machine learning algorithms</li><li><strong>Section 08: </strong>ANOVA (Analysis of Variance)</li><li><strong>Section 09: </strong>Wrap up</li></ul><h2>
        
        <div>CPD</div>
    </h2>

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

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

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

                        <div id="career_path">
                            <p>After completing this course, you can explore trendy and in-demand jobs related to Data Science, such as-</p><ul><li>Data Analyst: £25,000 to £45,000 per year</li><li>Data Scientist: £35,000 to £60,000 per year</li><li>Business Intelligence (BI) Analyst: £30,000 to £50,000 per year</li><li>Machine Learning Engineer: £40,000 to £70,000 per year</li><li>Data Engineer: £35,000 to £60,000 per year</li><li>Data Consultant: £45,000 to £75,000 per year</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

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

                        </div>

Compliance Central

Data Science Course Online

<p>The world of finance can be unpredictable and ever-changing. Gain a competitive edge with our Hands-on Deep Learning Projects - Stock Price Prognostics course. In this course, you'll learn how to build a deep learning model using RNN that can accurately predict stock prices. With a comprehensive curriculum that covers everything from data preprocessing to model building and evaluation, this course is perfect for those looking to upskill in the field of deep learning.</p><p>Our course modules are designed to provide you with a hands-on learning experience. You'll learn how to install tools and libraries, explore datasets, perform exploratory data analysis, and build and evaluate a deep learning model. You'll also learn how to scale features and make predictions on test data. By the end of this course, you'll have a deep understanding of how to develop cutting-edge technology that can revolutionise the world of finance.</p><p>This course is perfect for aspiring data scientists, machine learning engineers, and developers who want to gain real-world experience in deep learning development. With the skills and knowledge gained from this course, you'll be able to start a career in the exciting field of deep learning and contribute to the development of cutting-edge technology in the finance industry.</p><p><strong>Learning Outcomes:</strong></p><ul><li>Build a deep learning model using RNN that can accurately predict stock prices.</li><li>Preprocess data and perform exploratory data analysis.</li><li>Scale features and make predictions on test data.</li><li>Gain real-world experience in deep learning development.</li><li>Contribute to the development of cutting-edge technology in the finance industry.</li></ul><p>The Hands-on Deep Learning Projects - Stock Price Prognostics course is designed to provide you with the skills and knowledge needed to develop a deep learning model using RNN that can accurately predict stock prices. In this course, you'll learn how to preprocess data, perform exploratory data analysis, scale features, and make predictions on test data. The course is perfect for aspiring data scientists, machine learning engineers, and developers interested in deep learning development.</p><p>By the end of this course, you'll have a deep understanding of how to build a deep learning model that can revolutionise the world of finance. With hands-on experience in developing cutting-edge technology, you'll be well-equipped to start a career in deep learning and contribute to the development of cutting-edge technology in the finance industry.</p><p><strong>â±â± Hands on Deep Learning Projects - Stock price Prognostics</strong><strong> Course Curriculum </strong></p><ul><li><strong>Section 01: </strong>Introduction</li><li><strong>Section 02:</strong> Installation of Tools and Libraries</li><li><strong>Section 03: </strong>Dataset</li><li><strong>Section 04: </strong>EDA</li><li><strong>Section 05: </strong>Feature Scaling</li><li><strong>Section 06: </strong>Building RNN</li><li><strong>Section 07: </strong>Prediction on Test Data</li><li><strong>Section 08: </strong>Output</li></ul><p><strong>How is the course assessed?</strong></p><p>Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%.</p><p><strong>Exam &amp; Retakes:</strong><br />It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable.</p><p><strong>Certification</strong><br />Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery).</p><h2>
        
        <div>CPD</div>
    </h2>

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

                        <div id="who_is_this_course_for">
                            <ul><li>Aspiring data scientists.</li><li>Machine learning engineers.</li><li>Developers interested in deep learning development.</li><li>Anyone interested in the field of deep learning.</li><li>Professionals looking to upskill in the latest technology.</li></ul>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Scientist: £40,000 to £80,000 per year.</li><li>Machine Learning Engineer: £55,000 to £90,000 per year.</li><li>Artificial Intelligence Developer: £40,000 to £80,000 per year.</li><li>Quantitative Analyst: £30,000 to £80,000 per year.</li><li>Financial Data Analyst: £25,000 to £60,000 per year.</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            £9
        </p>
            <div> <p>You can apply for a CPD Accredited PDF Certificate at the cost of £9.</p> </div>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            £15
        </p>
            <div> <p>Hard copy can be sent to you via post at the expense of £15.</p> </div>

                        </div>

One Education

Hands on Deep Learning Projects - Stock price Prognostics Course

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

Nexus Human

Data Engineering

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

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

Data Science

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!

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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>
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        <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.

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        <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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