Name: Machine Learning Course with Python
Price: 10.99 GBP
Availability: InStock

<p>Beyond vision and strategy, today's leaders must be able to think critically and make wise decisions in the fast-paced, intricate business environment. We hope to provide you with the skills and knowledge required to become a more capable leader through our "Critical Thinking Skills in Leadership" course. Embark on a thorough trip that improves your ability to solve problems, sharpens your judgment, and modifies your leadership style.</p><p><strong>Key Features:</strong></p><ul><li>CPD Certified</li><li>Free Certificate from Reed</li><li>CIQ Approved</li><li>Developed by Specialist</li><li>Lifetime Access</li></ul><p>Via this course, students will acquire critical thinking abilities that are necessary for leadership positions. They will examine the elements and advantages of critical thinking while developing their ability to effectively assess information. They will improve their ability to solve problems and learn how to approach problems from many viewpoints through logical and non-linear thinking tasks.</p><p>Students will graduate with a thorough understanding of critical thinking and how it applies to leadership. They'll possess the skills necessary to critically evaluate events, decide wisely, and confidently adjust to shifting conditions. With the help of this curriculum, students will be able to incorporate different ways of thinking into their leadership approach, which will help them solve complicated issues quickly and provide their teams with innovative, clear leadership.</p><p><strong>Course Curriculum:</strong></p><ul><li><strong>Module 01:</strong> Components of Critical Thinking</li><li><strong>Module 02:</strong> Critical Thinking (II)</li><li><strong>Module 03:</strong> Critical Thinkers (I)</li><li><strong>Module 04:</strong> Benefits of Critical Thinking</li><li><strong>Module 05: </strong>Evaluate the Information</li><li><strong>Module 06:</strong> Logical Thinking</li><li><strong>Module 07: </strong>Non-Linear Thinking</li><li><strong>Module 08: </strong>Problem Solving</li><li><strong>Module 09: </strong>Changing Your Perspective</li><li><strong>Module 10:</strong> Putting It All Together</li></ul><p><strong>Learning Outcomes</strong></p><ul><li>Identify components critical for effective leadership through critical thinking skills.</li><li>Apply logical and non-linear thinking techniques in leadership decision-making processes.</li><li>Evaluate information critically for relevance and accuracy in leadership contexts.</li><li>Solve complex problems using critical thinking strategies for effective leadership.</li><li>Demonstrate ability to change perspectives for enhanced leadership decision-making.</li><li>Integrate critical thinking skills into holistic leadership approaches effectively.</li></ul><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><li>
                                        <h3>
                                            
                                                Critical Thinking Skills in Leadership <span>32:35</span>
                                                <span></span>
                                            
                                        </h3>
                                        <ul id="section1">
                                                <li>
                                                    <span>1: Module 01: Components of Critical Thinking</span>

                                                    <span>04:30</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>2: Module 02: Critical Thinking (II)</span>

                                                    <span>02:58</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>3: Module 03: Critical Thinkers (I)</span>

                                                    <span>02:42</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>4: Module 04: Benefits of Critical Thinking</span>

                                                    <span>03:10</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>5: Module 05: Evaluate the Information</span>

                                                    <span>03:08</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>6: Module 06: Logical Thinking</span>

                                                    <span>03:54</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>7: Module 07: Non-Linear Thinking</span>

                                                    <span>02:17</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>8: Module 08: Problem Solving</span>

                                                    <span>03:39</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>9: Module 09: Changing Your Perspective</span>

                                                    <span>02:30</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>10: Module 10: Putting It All Together</span>

                                                    <span>02:47</span>

                                                        
                                                                                                                                                                                                            </li>
                                                <li>
                                                    <span>11: CPD Certificate - Free</span>

                                                    <span>01:00</span>

                                                                                                                                                                
                                                                                                    </li>
                                        </ul>
                                    </li><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <ul><li>Aspiring leaders seeking to enhance decision-making skills.</li><li>Professionals in managerial roles aiming for strategic leadership improvement.</li><li>Individuals interested in developing critical thinking abilities for leadership.</li><li>Team leaders looking to refine problem-solving approaches in leadership.</li><li>Students pursuing leadership roles in various industries.</li></ul>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Management Consultant</li><li>Project Manager</li><li>Policy Analyst</li><li>Business Development Manager</li><li>Operations Director</li><li>Human Resources Manager</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Digital certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Reed Courses Certificate of Completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><p>Will be downloadable when all lectures have been completed.</p></div>

                        </div>

Online Training Academy

Critical Thinking Skills in Leadership

General Admission

<strong>This course starts with the basics of data science and gradually moves towards explaining the concepts of machine learning and various data science algorithms.</strong>
        <p>Machine learning is the key to development in many areas, such as IT, security, marketing, automation, and even medicine. Without machine learning, it is impossible to build intelligent applications and devices, such as Alexa, Siri, and Google Assistant. This course will help to get familiar with data science and machine learning.

The course starts with an introduction to data science, explaining different terms associated with it. You will also become familiar with machine learning and data science modeling and explore the key differences between model parameters and hyperparameters. Next, you will become familiar with the concepts of machine learning models, such as linear regression, decision trees, random forests, neural networks, and clustering techniques. Towards the end, you will learn how to evaluate machine learning models and learn the best practices to succeed in your data scientist role.

By the end of this course, you will have a solid understanding of data science and machine learning fundamentals.</p>
        <h2>What You Will Learn</h2><p>Become familiar with data science and machine learning terms<br>Distinguish between model parameters and hyperparameters<br>Distinguish between supervised and unsupervised learning<br>Discover how decision trees, bagging, and random forest works<br>Understand the importance of the k-nearest neighbors (KNN) algorithm in machine learning<br>Learn about neural networks and clustering techniques<br>Evaluate the performance of machine learning models</p>
        <h2>Audience</h2><p>This course is designed for students and beginners who want to understand the concepts, statistics, and math behind machine learning algorithms and for those who are curious to solve real-world problems using machine learning and data science. Everything is taught from scratch; hence, there are no prerequisites to get started with this course.</p>
        <h2>Approach</h2><p>With the help of simple explanation, avoiding confusing mathematical notation and jargon, this course covers the fundamentals of data science, machine learning, and data mining from scratch.</p>
        <h2>Key Features</h2><p>Learn the fundamentals of data science, machine learning, and data mining * Learn interesting techniques to evaluate a machine learning model * Discover the best practices to solve real-world problems using machine learning</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. Welcome and Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Welcome</p><p style='margin: 0'>This video welcomes you to the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Introduction to Data Science</p><p style='margin: 0'>This video provides an introduction to data science.</p></td></tr></tbody></table><br><h4>2. Preliminary Requirements to Understand Data Science and Machine Learning</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Understanding Data Science Terms</p><p style='margin: 0'>This video provides an overview of the terms used in data science.</p></td></tr><tr><td style='padding: 15px;'><p>2. Understanding Machine Learning</p><p style='margin: 0'>This video presents an overview of machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>3. Types of Learning</p><p style='margin: 0'>This video explains the different types of learning.</p></td></tr><tr><td style='padding: 15px;'><p>4. Understanding Data Science Modeling</p><p style='margin: 0'>This video focuses on data science modeling.</p></td></tr><tr><td style='padding: 15px;'><p>5. Model parameters versus Hyperparameters</p><p style='margin: 0'>This video explains the difference between model parameters and hyperparameters.</p></td></tr></tbody></table><br><h4>3. Machine Learning Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. How Linear Regression Works</p><p style='margin: 0'>This video demonstrates how linear regression works.</p></td></tr><tr><td style='padding: 15px;'><p>2. How Decision Trees Work</p><p style='margin: 0'>This video demonstrates how decision trees work.</p></td></tr><tr><td style='padding: 15px;'><p>3. How Bagging and Random Forest Work</p><p style='margin: 0'>This video demonstrates the working of bagging and random forest.</p></td></tr><tr><td style='padding: 15px;'><p>4. How Support Vector Machine Works</p><p style='margin: 0'>This video demonstrates the working of support vector machines.</p></td></tr><tr><td style='padding: 15px;'><p>5. Neural Networks- Part 1</p><p style='margin: 0'>This video is the first part of a two-part video that explains neural networks.</p></td></tr><tr><td style='padding: 15px;'><p>6. Neural Networks- Part 2</p><p style='margin: 0'>This is the second part of the two-part video that explains neural networks.</p></td></tr><tr><td style='padding: 15px;'><p>7. How Logistic Regression Works</p><p style='margin: 0'>This video demonstrates the working of logistic regression.</p></td></tr><tr><td style='padding: 15px;'><p>8. How k-nearest neighbour (KNN) Works</p><p style='margin: 0'>This video focuses on KNN and explains how it works.</p></td></tr><tr><td style='padding: 15px;'><p>9. Clustering Techniques</p><p style='margin: 0'>This video explains the different clustering techniques.</p></td></tr></tbody></table><br><h4>4. Model Performance</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Evaluating Models Performance</p><p style='margin: 0'>This video demonstrates how to evaluate the performance of the models.</p></td></tr></tbody></table><br><h4>5. Best Practices for a Data Scientist</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Best Practices for a Data Scientist</p><p style='margin: 0'>This video explains the best practices used by data scientists.</p></td></tr></tbody></table>

Packt

Data Science

Algorithms

This course starts with the basics of data science and gradually moves towards explaining the concepts of machine learning and various data science algorithms.

Mastering Data Science and Machine Learning Fundamentals

<div>
									<section>
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					<div>
			<div>
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				<div>
			<h3><b>Advance Mathematics</b></h3>		</div>
				</div>
				<div>
				<div>
							<p><span>Are you ready to take your love for math to the next level? Our Advance Mathematics course is like a supportive mentor, here to guide you through the fascinating world beyond the basics. It's about empowering you to think critically, solve problems creatively, and see the world in a new light.</span></p><p><span>Our Advance Mathematics course will help you develop a strong mathematical logic foundation, enabling you to dissect sentences, identify statements, and classify them into various types with precision. Plus, you will comprehensively understand trigonometric functions and their applications. You'll confidently solve triangles, explore polar coordinates, and navigate through the rules and theorems of sine, cosine, and tangent. Moreover, in this Advance Mathematics course, you will acquire the skills needed to tackle real-world problems through linear programming, allowing you to optimize solutions using mathematical models.</span></p><p><span>You will also gain insights into the dynamic relationships between pairs of straight lines, understanding degrees and types to solve complex geometric problems. Furthermore, you will understand the concept of multiplication &amp; addition using matrix, inverse of matrix, uniqueness of inverse, etc.</span></p><p><span>Don't let fear hold you back from unlocking your full mathematical potential. Enroll in our Advance Mathematics course!</span></p>						</div>
				</div>
					</div>
		</div>
							</div>
		</section>
				<section>
						<div>
					<div>
			<div>
								<div>
				<div>
			<h3><b>Why Choose Teachers Training</b></h3>		</div>
				</div>
				<div>
				<div>
			<p>Some of our website features are:</p>		</div>
				</div>
				<div>
				<div>
					<ul>
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											<span>
													</span>
										<span>This is a dedicated website for teaching</span>
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										<span>24/7 tutor support</span>
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										<span>Interactive Content</span>
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										<span>Affordable price</span>
									</li>
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										<span>Courses accredited by the UK's top awarding bodies</span>
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											<span>
													</span>
										<span>100% online </span>
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										<span>Flexible deadline</span>
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		</section>
				<section>
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			<h3><b> Entry Requirements
</b></h3>		</div>
				</div>
				<div>
				<div>
			<p>No formal entry requirements. You need to have:</p>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Passion for learning</span>
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										<span>A good understanding of the English language</span>
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										<span>Be motivated and hard-working</span>
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										<span>Over the age of 16.</span>
									</li>
						</ul>
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		</div>
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		</section>
				<section>
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			<h3><b>Certification</b></h3>		</div>
				</div>
				<div>
				<div>
							<p><b>CPD Certification from The Teachers Training</b></p><p>Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish.</p><ul><li>You can get your digital certificate (PDF) for £4.99 only</li><li>Hard copy certificates are also available, and you can get one for only £10.99</li><li>You can get both PDF and Hard copy certificates for just £12.99!</li></ul><p>The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs.</p>						</div>
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							</div><table width="100%">				<tbody><tr>
					<td colspan="4">Unit 01: Introduction</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
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								<tr>
					<td colspan="4">Unit 02: Mathematical Logic</td>
				</tr>
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					<td><i></i></td>
					<td>Introduction to Mathematical Logic, What is Sentence, Statements and their Types</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Introduction to Logical Connectivity, Tautology, Contradiction, Contingency, Pattern</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Quantitative and Quantified Statement and types and example</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Dual: Replacing of Connections and Symbols</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Negations of Compound Statement, Converse, Inverse, &amp; Contrapositive</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Algebra of Statements and Law</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Real Life application of Logic to Switching Electric Circuit</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 03: Matrices</td>
				</tr>
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					<td><i></i></td>
					<td>Introduction to Matrices, Multiplication and Addition using Matrix</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Inverse of Matrix Uniqueness of Inverse, Elementary Transformation</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
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					<td><i></i></td>
					<td>Method of REDUCTION AND INVERSION with real life example how we can implement</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
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					<td colspan="4">Unit 04: Trigonometric Functions</td>
				</tr>
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					<td><i></i></td>
					<td>Introduction to Trigonometric Function</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>General Solutions and Theorem</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Solution of Triangle: Polar Co-ordinates</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Rules and Theorems of Sin Cosine and Tan</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
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					<td colspan="4">Unit 05: Pair of Straight Line</td>
				</tr>
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					<td><i></i></td>
					<td>Introduction &amp; Combined Equations</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Degrees and Types</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
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					<td><i></i></td>
					<td>Some Theorem</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
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					<td colspan="4">Unit 06: Lines &amp; Planes</td>
				</tr>
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					<td><i></i></td>
					<td>Introduction - vector Cartesian theorem</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Cartesian Equation &amp; 2 Point Theorem</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Theorems &amp; Problem Solving</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Distance of Point Line</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Skew Lines</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Distance of skew lines</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Distance between parallel lines</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Equation of Plane and Cartesian Form</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 07: Linear Programming</td>
				</tr>
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					<td><i></i></td>
					<td>Linear Programming Introduction</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to LPP (Linear Programming Problem)</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>LPP Problem Solving</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
				</tbody></table>

The Teachers Training

GCSE Maths

Higher Maths

Maths Teacher

Maths

Algebra

Further Maths

Advance Mathematics

<p>The 'Mathematics' course provides a comprehensive study of various mathematical concepts, including mathematical logic, matrices, trigonometric functions, pair of straight lines, lines &amp; planes, and linear programming. It aims to enhance students' mathematical knowledge and problem-solving skills.</p>
<h3><strong>Learning Outcomes:</strong></h3>
<ol>
<li>Understand the fundamentals of mathematical logic and its application in problem-solving.</li>
<li>Comprehend matrix operations and solve mathematical problems involving matrices.</li>
<li>Analyze trigonometric functions and their properties in various mathematical contexts.</li>
<li>Solve problems related to pair of straight lines and their equations.</li>
<li>Explore lines and planes in three-dimensional space and their geometric properties.</li>
<li>Apply linear programming techniques to optimize solutions in real-world scenarios.</li>
<li>Acquire a strong foundation in mathematics and develop critical thinking abilities.</li>
<li>Demonstrate proficiency in mathematical concepts through problem-solving exercises.</li>
<li>Utilize mathematical tools and techniques in practical applications and academic settings.</li>
<li>Successfully complete the Mathematics course with a comprehensive understanding of key mathematical principles.</li>
</ol>
<h3><b>Why buy this Mathematics?</b></h3>
<ol>
<li><span>Unlimited access to the course for forever</span></li>
<li><b>Digital Certificate, Transcript, student ID</b><span> all included in the price</span></li>
<li><span>Absolutely no hidden fees</span></li>
<li><span>Directly receive </span><b>CPD </b><span>accredited qualifications after course completion</span></li>
<li><span>Receive one to one assistance on every weekday from professionals</span></li>
<li><span>Immediately receive the PDF certificate after passing</span></li>
<li><span>Receive the original copies of your certificate and transcript on the next working day</span></li>
<li><span>Easily learn the skills and knowledge from the comfort of your home</span></li>
</ol>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials of the </span><b>Mathematics</b><span> there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60.</span></p>
<h3><b>Who is this course for?</b></h3>
<p><span>This </span><b>Mathematics</b><span> course is ideal for</span></p>
<ul>
<li><span>Students</span></li>
<li><span>Recent graduates</span></li>
<li><span>Job Seekers</span></li>
<li><span>Anyone interested in this topic</span></li>
<li><span>People already working in the relevant fields and want to polish their knowledge and skill.</span></li>
</ul>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>Mathematics</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning.This </span><b>Mathematics</b><span> was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.</span></p>
<h3><b>Career path</b></h3>
<p><span>As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This </span><b>Mathematics </b><span>is a great way for you to gain multiple skills from the comfort of your home.</span></p><div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4">Unit 01: Introduction</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 02: Mathematical Logic</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Mathematical Logic, What is Sentence, Statements and their Types</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Logical Connectivity, Tautology, Contradiction, Contingency, Pattern</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Quantitative and Quantified Statement and types and example</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Dual: Replacing of Connections and Symbols</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Negations of Compound Statement, Converse, Inverse, &amp; Contrapositive</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Algebra of Statements and Law</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Real Life application of Logic to Switching Electric Circuit</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 03: Matrices</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Matrices, Multiplication and Addition using Matrix</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Inverse of Matrix Uniqueness of Inverse, Elementary Transformation</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Method of REDUCTION AND INVERSION with real life example how we can implement</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 04: Trigonometric Functions</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Trigonometric Function</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>General Solutions and Theorem</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution of Triangle: Polar Co-ordinates</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Rules and Theorems of Sin Cosine and Tan</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 05: Pair of Straight Line</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction &amp; Combined Equations</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Degrees and Types</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Some Theorem</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 06: Lines &amp; Planes</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction - vector Cartesian theorem</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Cartesian Equation &amp; 2 Point Theorem</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Theorems &amp; Problem Solving</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Distance of Point Line</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Skew Lines</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Distance of skew lines</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Distance between parallel lines</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Equation of Plane and Cartesian Form</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 07: Linear Programming</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Linear Programming Introduction</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to LPP (Linear Programming Problem)</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>LPP Problem Solving</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Assignment</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assignment - Mathematics</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Studyhub UK

Numeracy

Mathematics

<div>
							<div>
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			<div>
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						<div>
				<div>
			<h2><b>Course Overview</b></h2>		</div>
				</div>
				<div>
				<div>
					<div><p><span>Build your confidence in maths and gain the skills you need to pass your maths exam with flying colours, in this complete <strong>Mathematics Masterclass. </strong></span></p><p><span>This mathematics course is ideal for those who already have a basic understanding of everyday maths and want to learn more complex skills. Through this training, you will explore key topics such as trigonometry, linear programming, and algebra, learning how to apply them in a practical way.</span></p><p><span>By the end of this course, you will have excellent problem-solving, logical and linear thinking skills, with the confidence to master any complex mathematical problem. You will also have an excellent grasp of matrix multiplication and addition.</span></p></div>
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					<div><p>This best selling <strong>Mathematics Masterclass </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Mathematics Masterclass </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The <strong>Mathematics Masterclass </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>Mathematics Masterclass </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> Mathematics Masterclass</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>Mathematics Masterclass </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>Mathematics Masterclass </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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							<div>
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			<div>
							<div>
						<div>
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				<section>
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		</section>
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Course Cloud

Mathematics Masterclass

<div>
        <div>
            <h2>
                Recognised Accreditation
            </h2>
            <p>This course is accredited by continuing professional development (CPD). CPD UK is globally
                recognised by employers, professional organisations, and academic institutions, thus a
                certificate from CPD Certification Service creates value towards your professional goal
                and achievement.</p>

                

                <p>The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries.</p>
                
    </div>
    <div>
        <div>
            <div>
                
                <h3>What is CPD?</h3>
                <p>Employers, professional organisations, and academic institutions all recognise CPD,
                    therefore a credential from CPD Certification Service adds value to your professional
                    goals and achievements.</p>
                <h4>Benefits of CPD</h4>
                <ul>
                    <li>Improve your employment prospects </li>
                    <li>Boost your job satisfaction </li>
                    <li>Promotes career advancement </li>
                    <li>Enhances your CV </li>
                    <li>Provides you with a competitive edge in the job market </li>
                    <li>Demonstrate your dedication </li>
                    <li>Showcases your professional capabilities</li>
                </ul>
            </div>
        </div>
        <div>
            <div>
                
                <h3>What is IPHM? </h3>
                <p>The IPHM is an Accreditation Board that provides Training Providers with international
                    and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation
                    is a guarantee of quality and skill. </p>
                <h4>Benefits of IPHM </h4>
                <ul>
                    <li>It will help you establish a positive reputation in your chosen field </li>
                    <li>You can join a network and community of successful therapists that are dedicated to
                    providing excellent care to their client </li>
                    <li>You can flaunt this accreditation in your CV </li>
                    <li>It is a worldwide recognised accreditation </li>
                </ul>
            </div>
        </div>
        <div>
            <div>
                
                <h3>What is Quality Licence Scheme?</h3>
                <p>This course is endorsed by the Quality Licence Scheme for its high-quality,
                    non-regulated provision and training programmes. The Quality Licence Scheme is a brand
                    of the Skills and Education Group, a leading national awarding organisation for
                    providing high-quality vocational qualifications across a wide range of industries.</p>
                <h4> Benefits of Quality License Scheme </h4>
                <ul>
                    <li>Certificate is valuable</li>
                    <li>Provides a competitive edge in your career</li>
                    <li>It will make your CV stand out</li>
                </ul>
            </div>
        </div>
    </div>
                    </div><div>
				
<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table>				<tbody><tr>
					<td colspan="4">Course Introduction</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Introduction					</td>

					
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Part 1: Forecasting</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Basics of Forecasting					</td>

					
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Creating Linear Model with Trendlines					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">1.1 Getting Data Ready For Regression Model</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Gathering Business Knowledge					</td>

					
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Data Exploration					</td>

					
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						The Data and the Data Dictionary					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Univariate analysis and EDD					</td>

					
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Discriptive Data Analytics in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Outlier Treatment					</td>

					
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Identifying and Treating Outliers in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Missing Value Imputation					</td>

					
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Identifying and Treating missing values in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Variable Transformation in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Dummy variable creation: Handling qualitative data					</td>

					
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Dummy Variable Creation in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Correlation Analysis					</td>

					
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Creating Correlation Matrix in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">1.2 Forecasting Using Regression Model</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						The Problem Statement					</td>

					
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Basic Equations and Ordinary Least Squares (OLS) method					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Assessing accuracy of predicted coefficients					</td>

					
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Assessing Model Accuracy: RSE and R squared					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Creating Simple Linear Regression model					</td>

					
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Multiple Linear Regression					</td>

					
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						The F - statistic					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Interpreting results of Categorical variables					</td>

					
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Creating Multiple Linear Regression model					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">1.3 Handling Special Events Like Holiday Sales</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Forecasting in presence of special events					</td>

					
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Running Linear Regression using Solver					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Including the impact of Special Events					</td>

					
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
								<tr>
					<td colspan="4">1.4 Identifying Seasonality &amp; Trend for Forecasting</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Models to identify Trend &amp; Seasonality					</td>

					
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Additive model to identify Trend &amp; Seasonality					</td>

					
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Multiplicative model to identify Trend &amp; Seasonality					</td>

					
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Market Basket Analysis</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Market Basket and Lift - Introduction					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Named Ranges - Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Indirect Function - Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						2-way lift calculation in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						2-way lift calculation - Dynamic					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						2-way lift data table creation					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						3-way lift calculation					</td>

					
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Store Layout optimization using Lift values					</td>

					
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">RFM (Recency, Frequency, Monetary) Analysis</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						RFM (recency, frequency, monetary) Analysis					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						RFM Analysis in Excel- Part 1					</td>

					
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						RFM Analysis in Excel- Part 2					</td>

					
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Part 2: Pricing</td>
				</tr>
								<tr>
					<td colspan="4">Part 2: Pricing</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Steps of setting a Pricing policy					</td>

					
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Different Pricing Objectives					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">2.1 Estimating Demand</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Estimating Demand					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Forms of Demand Curve					</td>

					
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Estimating Linear Demand Curve					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Estimating Power Demand curve with Elasticity					</td>

					
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Estimating Power Demand Curve with points					</td>

					
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Subjective Demand curve					</td>

					
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Estimating Subjective Demand Curve					</td>

					
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">2.3 Evaluating Pricing Strategies</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Price Bundling					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Types of Bundling					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						The Bundling Problem					</td>

					
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Solving Bundling problem Part 1					</td>

					
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Solving Bundling problem Part 2					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Non-Linear Pricing Strategies					</td>

					
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Excel: Solving Bundling problem (Price Reversal)					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">3.1 Lifetime Customer Value</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Lifetime Customer Value - Key concepts					</td>

					
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Lifetime Customer Value - Excel model					</td>

					
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4">3.2 Variations And Sensitivity Analysis</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Sensitivity Analysis in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Variations in finding customer value					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Appendix 1: Excel Crash Course</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Basics					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Worksheet Basics					</td>

					
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Entering values and Formulas					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Data Handling Basics - Cut, Copy and Paste					</td>

					
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Saving and Printing - Basics					</td>

					
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Basic Formula Operations					</td>

					
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Mathematical Formulas					</td>

					
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Textual Formulas					</td>

					
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Logical Formulas					</td>

					
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Date-Time Formulas					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Lookup Formulas ( V Lookup, Hlookup, Index-Match )					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Data Tools					</td>

					
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Formatting data and tables					</td>

					
					<td> </td>
					<td><span><i></i> 00:18:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Pivot Tables					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Advance Excel- Solver, Data tables					</td>

					
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4"> Assessment</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assessment - Retail Analytics In Microsoft Excel Diploma</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Obtain Your Certificate</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Order Your Certificate of Achievement					</td>

					
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Get Your Insurance Now</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Get Your Insurance Now					</td>

					
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Feedback</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>
						Feedback					</td>

					
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Study Plex

Retail Analytics In Microsoft Excel Diploma

<h2 style="color: rgb(15, 21, 26); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(15, 21, 26);">Overview</h2><div style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Are you interested in learning more about Agile in your role or organisation, or perhaps you need to know more to fit into a new role or have heard about the many benefits of working in an &#39;Agile&#39; way.<br fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;">The BCS Foundation Certificate in Agile is designed to equip learners with the core foundations that underpin the Agile mindset and Agile approaches to delivery. It teaches learners the knowledge that can be applied in a variety of situations and promotes effective working with any Agile team. It does not focus solely on one specific methodology.<br fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;">The course is relevant to anyone requiring an understanding of the use of Agile or looking to adopt it. This includes, but is not limited to, organisational leaders and managers, marketing executives and managers, and/or all professionals working in an Agile environment, including software sesters, developers, business analysts, UX designers, project management office (PMO), project support and project coordinators.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Upon achievement of the certificate, candidates will be able to demonstrate a practical understanding of:</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&bull; Why Agile?<br fr-original-style="" style="box-sizing: border-box;">&bull; The Agile Manifesto</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&bull; The Agile Mindset</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&bull; Roles in Agile Teams</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&bull; Common Agile Practices</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&bull; The Practical Application of Agile.<br fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;">With self -study, you get a whole package of support we call PASS ASSIST, including digital access to the recommended BCS book:<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Agile from First Principles</strong>eBook, 2 live video support calls with your course trainer, practice exam papers and a series of support videos to get the most out of your course, making a learning plan and how to prepare for the exam.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Why Choose Duco Digital Training?</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">With self-study, you get a whole package of support we call PASS ASSIST, including:<br fr-original-style="" style="box-sizing: border-box;">Free one year BCS Associate membership (normally costing &pound;90)<br fr-original-style="" style="box-sizing: border-box;">Free BCS Data Analyst eBook<br fr-original-style="" style="box-sizing: border-box;">Practice exam papers<br fr-original-style="" style="box-sizing: border-box;">Series of support videos to get the most out of your course, making a learning plan and how to prepare for the exam<br fr-original-style="" style="box-sizing: border-box;">5-star rating<br fr-original-style="" style="box-sizing: border-box;">95% pass rate.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">A live training option is available, please contact us.</p><section style="color: rgb(15, 21, 26); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(15, 21, 26);"><h2 fr-original-style="" style="box-sizing: border-box;">Description</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The &ldquo;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">BCS Foundation Data Protection</strong>&rdquo; is a professional certification that is a globally recognized professional qualification that will help develop your knowledge and understanding of:</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">1. WHY AGILE?</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Describe a linear development approach, such as Waterfall and V-model.</li><li fr-original-style="" style="box-sizing: border-box;">Explain why linear development approaches are not suitable in a Volatile, Uncertain,<br fr-original-style="" style="box-sizing: border-box;">Complex and Ambiguous (VUCA) environment.</li><li fr-original-style="" style="box-sizing: border-box;">Explain the origins of Agile.</li><li fr-original-style="" style="box-sizing: border-box;">Recognise the Agile Manifesto and its principles.</li><li fr-original-style="" style="box-sizing: border-box;">Explain how the Pillars of Scrum underpin Agile thinking.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">2. INDIVIDUALS AND THEIR INTERACTIONS OVER PROCESSES AND TOOLS</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Describe ways that the processes and tools can undermine Agile team performance.</li><li fr-original-style="" style="box-sizing: border-box;">Explain the connection between team motivation and self-organising autonomous<br fr-original-style="" style="box-sizing: border-box;">teams.</li><li fr-original-style="" style="box-sizing: border-box;">Describe how Agile teams interact.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">3. WORKING SOFTWARE OVER COMPREHENSIVE DOCUMENTATION</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Describe how working software means more than just code.</li><li fr-original-style="" style="box-sizing: border-box;">Explain how Agile can be applied to non-software products.</li><li fr-original-style="" style="box-sizing: border-box;">Explain how the Seven Wastes of Lean (Software Development) relates to comprehensive documentation.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">4. CUSTOMER COLLABORATION OVER CONTRACT NEGOTIATION</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Describe the Agile team&rsquo;s relationship with its customers.</li><li fr-original-style="" style="box-sizing: border-box;">Describe how Agile teams use time boxes and iterations to decide what work to commit to</li><li fr-original-style="" style="box-sizing: border-box;">Describe the Product Owner role and their responsibilities</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">5. RESPONDING TO CHANGE OVER FOLLOWING A PLAN</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Explain how regular feedback helps Agile teams respond to change.</li><li fr-original-style="" style="box-sizing: border-box;">Describe how Agile teams recognise when change is underway</li><li fr-original-style="" style="box-sizing: border-box;">Describe the different levels of planning that Agile teams use.</li><li fr-original-style="" style="box-sizing: border-box;">Explain the risks of detailed, upfront planning.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">6. THE AGILE MINDSET</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Explain Servant Leadership.</li><li fr-original-style="" style="box-sizing: border-box;">Explain how Agile teams are cross-functional and self-organising.</li><li fr-original-style="" style="box-sizing: border-box;">Explain how the Pillars of Scrum enable continuous improvement.</li><li fr-original-style="" style="box-sizing: border-box;">Describe how Agile teams demonstrate transparency.</li><li fr-original-style="" style="box-sizing: border-box;">Explain the importance of maximising the amount of work not done</li><li fr-original-style="" style="box-sizing: border-box;">Describe how Agile teams maintain sustainable pace.</li><li fr-original-style="" style="box-sizing: border-box;">Recall the critical factors in creating motivated teams.</li><li fr-original-style="" style="box-sizing: border-box;">Explain the importance of psychological safety for high performing teams.</li><li fr-original-style="" style="box-sizing: border-box;">Explain incremental and iterative delivery.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">7. ROLES IN AGILE TEAMS</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Describe the three Scrum roles.</li><li fr-original-style="" style="box-sizing: border-box;">Identify and describe commonly used non-Scrum Agile roles.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">8. COMMON AGILE PRACTICES</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Describe the practices of Team Leadership and Organisation in Agile.</li><li fr-original-style="" style="box-sizing: border-box;">Describe the use of requirements.</li><li fr-original-style="" style="box-sizing: border-box;">Describe the practise of estimation</li><li fr-original-style="" style="box-sizing: border-box;">Describe common software development practices.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">9. AGILE IN PRACTICE</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Describe the following Agile approaches.</li><li fr-original-style="" style="box-sizing: border-box;">Explain how the following practices can remove the need to adopt a scaling method.</li><li fr-original-style="" style="box-sizing: border-box;">Explain why the following metrics are indicators to healthy Agile teams.</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Exam Information of &ldquo;BCS Foundation Data Protection&rdquo; Course</strong>:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">It is a 40 multiple choice questions</li><li fr-original-style="" style="box-sizing: border-box;">Pass mark is 26/40 points or 65%</li><li fr-original-style="" style="box-sizing: border-box;">Duration of the exam is 60 minutes</li><li fr-original-style="" style="box-sizing: border-box;">The exam will be supervised virtually</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who is BCS?</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Recognised globally by corporations, academics and IT professionals, BCS is the British Computer Society, more commonly known as the Chartered Institute for IT.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">They have over 60,000 members in 150 countries, and a wider community of business leaders, educators, practitioners and policy-makers all committed to their mission of leading the IT industry through its ethical challenges, to support the people who work in the industry, and to make IT good for society.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">What our students say about us:</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">"The training provided will assist me to conduct AI research projects in a more professional and systematic way. The knowledge provided will be incredibly valuable for my future study in the field of computer vision."<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&nbsp;&mdash; Muhammad Lecturer and AI PhD Candidate</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&ldquo;Good training materials for remote learning, and the most impressive part was the speed at which they responded to questions.&rdquo;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&nbsp;&mdash; Tom Data Protection Practitioner</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">"This proved to be a very valuable course to me."&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&mdash; Janet Business Analyst</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong id="isPasted" fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Supporting new and the next-generation of analysts&nbsp;</strong></p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Soni is passionate about the value and importance of business analysis in bridging the gap between business and technology and is excited to champion and support new and next-generation analysts like you.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">She has over 20 years&rsquo; experience as a business analyst complimented with a MEng degree in Computer Science. In addition, she has experience of project management, enterprise architecture and agile project delivery. Her career as a senior business analyst has involved delivering large digital transformation programmes for both government and corporate organisations in a variety of sectors such as Defence, Banking, Cyber Security, Telecommunications, and IT. &nbsp;</p></section><section style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><h2 fr-original-style="" style="box-sizing: border-box;">Who is this course for?</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">For whom is the &ldquo;BCS Foundation Certificate in Agile&rdquo; course designed?</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Whether you&#39;re new to agile methodologies or a professional seeking to solidify your understanding of agile principles, the &ldquo;BCS Foundation Certificate in Agile&rdquo; course is designed to support your learning goals. It&#39;s intended for:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Aspiring Agile Practitioners: Individuals eager to enter the field of agile project management, ready to build a strong foundation in agile practices and frameworks.</li><li fr-original-style="" style="box-sizing: border-box;">Students with a Passion for Agile: University scholars aiming to enhance their theoretical understanding with practical, industry-relevant skills in agile methodologies, setting the stage for a successful career.</li><li fr-original-style="" style="box-sizing: border-box;">Career Transitioners: Professionals considering a shift into agile roles from various backgrounds, ready to acquire the fundamental knowledge needed to thrive in agile environments.</li><li fr-original-style="" style="box-sizing: border-box;">Process Improvement Enthusiasts: Practitioners dedicated to enhancing organizational efficiency and effectiveness by gaining a robust foundation in agile principles and practices.</li><li fr-original-style="" style="box-sizing: border-box;">Emerging Leaders and Managers: Entry-level managers and team leaders seeking to develop their agile knowledge, enabling them to support agile initiatives and lead teams in implementing agile processes effectively.</li></ul></section><section style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><h2 fr-original-style="" style="box-sizing: border-box;">Requirements</h2><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">An internet connection with a mobile/tablet or laptop is required to access the course</li><li fr-original-style="" style="box-sizing: border-box;">Access to laptop with camera is required for the exam and a pair of headphones is recommended for the exam.</li></ul></section><section style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><h2 fr-original-style="" style="box-sizing: border-box;">Career path</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The U.S. Bureau of Labor Statistics projected a 14% growth in management analyst positions, which includes business analysts, from 2020 to 2030.<br fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;">This growth rate is much faster than the average for all occupations and underscores the increasing need for professionals with business analysis skills.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Sectors using Agile:</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&bull; Health</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&bull; Robotics</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&bull; Engineering &amp; Manufacturing</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&bull; Finance</p></section></div>

Duco Digital Training

Agile

The course is relevant to anyone requiring an understanding of the use of Agile or looking to adopt it. This includes, but is not limited to, organisational leaders and managers, marketing executives and managers, and/or all professionals working in an Agile environment, including software sesters, developers, business analysts, UX designers, project management office (PMO), project support and project coordinators.

BCS Foundation Certificate in Agile

General admission

Computer Vision

Python

Programming

Deep Learning

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

Mastering Image Segmentation with PyTorch using Real-World Projects

<p>Discover the thrilling world of artificial intelligence with the '<strong>Machine Learning Course with Python</strong>'. Immerse yourself in a voyage from foundational concepts, unveiling the mysteries behind algorithms, to diving deep into the cores of preprocessing, regression, and classification. Crafted meticulously, this course introduces Python as the catalyst, opening doors to data-driven decision-making and predictive analysis, empowering your journey in the ever-evolving field of machine learning.</p>
<p><strong>Learning Outcomes</strong></p>
<ul>
<li>Grasp the foundational knowledge of various machine learning algorithms.</li>
<li>Attain proficiency in preprocessing data for optimal outcomes.</li>
<li>Master the nuances of regression analysis using Python.</li>
<li>Delve into the intricacies of classification techniques.</li>
<li>Enhance problem-solving abilities with practical Python-driven machine learning applications.</li>
</ul>
<h3><b>Why choose this Machine Learning Course with Python<span> course</span>?</b></h3>
<ul>
<li>Unlimited access to the course for a lifetime.</li>
<li>Opportunity to earn a certificate accredited by the <b>CPD Quality Standards</b><b> </b>after completing this course.</li>
<li>Structured lesson planning in line with industry standards.</li>
<li>Immerse yourself in innovative and captivating course materials and activities.</li>
<li>Assessments are designed to evaluate advanced cognitive abilities and skill proficiency.</li>
<li>Flexibility to complete the <b>Machine Learning Course with Python</b> Course at your own pace, on your own schedule.</li>
<li>Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience.</li>
</ul>
<h3><b>Who is this Machine Learning Course with Python<span> </span></b><b><span>course </span></b><b>for?</b></h3>
<ul>
<li>Aspiring data scientists eager to harness the power of machine learning.</li>
<li>Python enthusiasts aiming to delve into its applications in AI.</li>
<li>Professionals in the tech industry seeking a transition into data roles.</li>
<li>Academics and researchers wanting to employ machine learning in their work.</li>
<li>Business analysts aiming to leverage predictive analytics for better insights.</li>
</ul>
<h3><b>Career path</b></h3>
<ul>
<li><strong>Data Scientist</strong>: £40,000 - £70,000</li>
<li><strong>Machine Learning Engineer</strong>: £50,000 - £80,000</li>
<li><strong>AI Researcher</strong>: £45,000 - £75,000</li>
<li><strong>Data Analyst</strong>: £30,000 - £50,000</li>
<li><strong>Python Developer</strong>: £35,000 - £65,000</li>
<li><strong>Business Intelligence Developer</strong>: £40,000 - £60,000</li>
</ul>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>Machine Learning Course with Python</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning.This </span><b>Machine Learning Course with Python</b><span> was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.</span></p>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8.</span></p><div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4">Module 01: Introduction to Machine Learning Algorithms</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to types of ML algorithm</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 02: Preprocessing</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Importing a dataset in python</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Resolving Missing Values</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Managing Category Variables</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Training and Testing Datasets</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Normalizing Variables</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Normalizing Variables - Python Code</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Summary</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 03: Regression</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Simple Linear Regression - How it works?</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Simple Linear Regreesion - Python Implementation</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Multiple Linear Regression - How it works?</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Multiple Linear Regression - Python Implementation</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Decision Trees - How it works?</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Random Forest - How it works?</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Decision Trees and Random Forest - Python Implementation</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 04: Classification</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>kNN - How it works?</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>kNN - Python Implementation</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Decision Tree Classifier and Random Forest Classifier in Python</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SVM - How it works?</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>SVM - Python Implementation</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Assignment </td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assignment - Machine Learning Course with Python</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Learning & Development

Online Course Marketing

Managed Learning Programme (MLP)

Machine Learning (ML)

Learning To Learn

Azure Machine Learning

Machine Learning Course with Python

<p>Did you know that businesses that use linear programming techniques experience an average increase in productivity of 10-15%? With statistics like these, it's no wonder that linear programming is becoming an increasingly important skill in the world of business.</p> <p>Our Level 3, 5 &amp; 7 Linear Programming course is designed to give learners a comprehensive understanding of linear programming, from the basics to advanced techniques. With this course, you will be equipped with the knowledge and skills to help businesses improve their productivity and profitability.</p> <p>What sets our course apart is that it is endorsed by the Quality Licence Scheme (QLS), an independent accrediting body that ensures the quality of our courses. Upon completion, learners will receive a<strong> Level 7 Endorsed certificate</strong> hardcopy free of charge, which is recognised by employers worldwide.</p> <p>But that's not all - we are also offering five career-guided courses for free with this QLS course, which will help you to boost your employability and take your career to the next level. These courses include Career Development Plan Fundamentals, Networking Skills for Personal Success, Boost Your Confidence and Self-Esteem, CV Writing and Job Searching, and Learn to Reduce and Manage Stress.</p> <p>With our course, you will receive top-quality education and valuable guidance, enabling you to gain the practical skills and knowledge you need to succeed in the competitive world of business. Enrol in our Level 3, 5 &amp; 7 Linear Programming course today and take the first step towards a successful career in business.</p> <p><strong>Learning Outcomes:</strong></p> <ul> <li>Understand the basic principles and concepts of linear programming, including the use of constraints and objective functions.</li><li>Learn to solve problems with mixed-type constraints, including those with multiple solutions.</li><li>Gain knowledge of the different types of constraints, including those of the '=', '&gt;=' and '&lt;=' types.</li><li>Develop the ability to simplify complex problems and identify degeneracy in linear programming.</li><li>Master the two-phase method and sensitivity analysis to evaluate solutions and identify the impact of changes in parameters.</li><li>Understand the concept of duality in linear programming and its applications.</li><li>Learn to use Solver tools and mobile apps for linear programming problems and find online solutions.</li></ul> <p><strong>Please Note: Imperial Academy is a One Education approved resale partner for Quality Licence Scheme Endorsed courses.</strong></p><p>Diploma in Level 3, 5 &amp; 7 Linear Programming at QLS at QLS's Description:</p> <p><strong>Level 3:</strong></p> <p>In this level, you will be introduced to the basics of linear programming, including the use of constraints and objective functions. You will learn how to solve problems with mixed-type constraints, including those with multiple solutions. We will also discuss the different types of constraints, including those of the '=', '&gt;=' and '&lt;=' types. You will have the opportunity to practice these concepts through various problem sets and examples.</p> <p><strong>Level 5:</strong></p> <p>In this level, you will learn how to simplify complex problems and identify degeneracy in linear programming. We will introduce you to the two-phase method and sensitivity analysis, which will help you evaluate solutions and identify the impact of changes in parameters. We will also discuss the concept of duality in linear programming and its applications. You will have the opportunity to practice these concepts through case studies and problem sets.</p> <p><strong>Level 7:</strong></p> <p>In this level, we will take a deeper dive into sensitivity analysis and duality in linear programming. You will learn how to use Solver tools and mobile apps to find online solutions for linear programming problems. We will present a production scheduling problem for formulation and an infeasible problem as case studies to help you apply these concepts in a practical context.</p> <p><strong>This bundle comprises the following courses:</strong><strong><br /></strong><strong>QLS Endorsed Course:</strong></p> <ul> <li><strong>Course 01:</strong> Advanced Diploma in Linear Programming at QLS Level 7</li></ul> <p><strong>CPD QS Accredited Courses:</strong></p> <ul> <li><strong>Course 01:</strong> Career Development Plan Fundamentals</li><li><strong>Course 02:</strong> Networking Skills for Personal Success</li><li><strong>Course 03:</strong> Boost Your Confidence and Self-Esteem</li><li><strong>Course 04:</strong> CV Writing and Job Searching</li><li><strong>Course 05:</strong> Learn to Reduce and Manage Stress</li></ul> <p><strong>Certificate</strong></p> <p>In pursuing this QLS-endorsed course, learners attain a profound understanding and amplify their professional prowess, enriching their curriculum vitae.</p> <p>The Quality Licence Scheme stands as a reputable and distinguished endorsement, emblematic of exceptional standards and excellence throughout the UK.</p> <p>Upon completion, learners will receive an Advanced Diploma in Linear Programming at QLS Level 7 Endorsed hard copy certificate, making it easy for them to showcase their achievements.</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>Business professionals who want to improve their decision-making skills.</li><li>Students who want to gain a competitive advantage in the job market.</li><li>Data analysts who want to improve their knowledge of linear programming.</li><li>Operations managers who want to optimise their business processes.</li><li>Anyone interested in improving their problem-solving skills.</li></ul> 
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                             <ul> <li>Operations Research Analyst - £30,000 to £60,000</li><li>Data Analyst - £25,000 to £50,000</li><li>Business Analyst - £25,000 to £45,000</li><li>Financial Analyst - £25,000 to £50,000</li><li>Logistics Manager - £30,000 to £60,000</li><li>Supply Chain Analyst - £25,000 to £50,000</li><li>Management Consultant - £40,000 to £80,000</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

Level 7 QLS Endorsed Course | Endorsed Certificate Included | Plus 5 Career Guided Courses | CPD Accredited

Level 3, 5 & 7 Linear Programming at QLS

<strong>Get started with using linear algebra in your data science projects</strong>
        <p>Vectorizing your code is an essential skill to make your calculations faster and take advantage of the capabilities of modern machine and deep learning packages. This course will get you up and running with linear algebra fundamentals for data science in Python. 

In this course, you will learn about scalars, vectors, and matrices and the geometrical meaning of these objects. You will also learn how you should use linear algebra in your Python code. In addition to this, you'll be able to perform operations such as addition, subtraction and dot product. As you cover further sections, you'll focus on the different syntactical errors you can encounter while vectorizing your code.  

By the end of this course, you will have gained the skills you need to use linear algebra confidently in your data science projects. 

All code and supporting files for this course are available at - https://github.com/PacktPublishing/Linear-Algebra-for-Data-Science-in-Python</p>
        <h2>What You Will Learn</h2><p>Focus on the addition and subtraction of Matrix <br>Understand errors when adding matrices <br>Learn why linear algebra is useful</p>
        <h2>Audience</h2><p>This course is designed for aspiring data scientists or anyone who wants to learn linear algebra in Python.</p>
        <h2>Approach</h2><p>This course takes you through linear algebra in a systematic manner. It is even packed with step-by-step instructions and working examples to enhance your learning experience.</p>
        <h2>Key Features</h2><p>Learn linear algebra for data science and understand the essential concepts  * Understand matrix, scalars, and vectors and learn how to use them</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/linear-algebra-for-data-science-in-python</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. Linear Algebra Fundamentals</h4><p></p>

Linear Algebra

Get started with using linear algebra in your data science projects

Linear Algebra for Data Science in Python

<div>
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            <h2>
                Recognised Accreditation
            </h2>
            <p>This course is accredited by continuing professional development (CPD). CPD UK is globally
                recognised by employers, professional organisations, and academic institutions, thus a
                certificate from CPD Certification Service creates value towards your professional goal
                and achievement.</p>

                

                <p>The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries.</p>
                
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                <h3>What is CPD?</h3>
                <p>Employers, professional organisations, and academic institutions all recognise CPD,
                    therefore a credential from CPD Certification Service adds value to your professional
                    goals and achievements.</p>
                <h4>Benefits of CPD</h4>
                <ul>
                    <li>Improve your employment prospects </li>
                    <li>Boost your job satisfaction </li>
                    <li>Promotes career advancement </li>
                    <li>Enhances your CV </li>
                    <li>Provides you with a competitive edge in the job market </li>
                    <li>Demonstrate your dedication </li>
                    <li>Showcases your professional capabilities</li>
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                <h3>What is IPHM? </h3>
                <p>The IPHM is an Accreditation Board that provides Training Providers with international
                    and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation
                    is a guarantee of quality and skill. </p>
                <h4>Benefits of IPHM </h4>
                <ul>
                    <li>It will help you establish a positive reputation in your chosen field </li>
                    <li>You can join a network and community of successful therapists that are dedicated to
                    providing excellent care to their client </li>
                    <li>You can flaunt this accreditation in your CV </li>
                    <li>It is a worldwide recognised accreditation </li>
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                <h3>What is Quality Licence Scheme?</h3>
                <p>This course is endorsed by the Quality Licence Scheme for its high-quality,
                    non-regulated provision and training programmes. The Quality Licence Scheme is a brand
                    of the Skills and Education Group, a leading national awarding organisation for
                    providing high-quality vocational qualifications across a wide range of industries.</p>
                <h4> Benefits of Quality License Scheme </h4>
                <ul>
                    <li>Certificate is valuable</li>
                    <li>Provides a competitive edge in your career</li>
                    <li>It will make your CV stand out</li>
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<h3>
	<span>Course Curriculum</span>
</h3>

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<table>				<tbody><tr>
					<td colspan="4">Getting Data Ready for Regression Model</td>
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						Transportation Problem in Excel using Goal Seek					</td>

					
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					<td><span><i></i> 00:12:00</span></td>
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						Gathering Business Knowledge					</td>

					
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					<td><span><i></i> 00:03:00</span></td>
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						Data Exploration					</td>

					
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					<td><span><i></i> 00:03:00</span></td>
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						The Data and the Data Dictionary					</td>

					
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					<td><span><i></i> 00:07:00</span></td>
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						Univariate analysis and EDD					</td>

					
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					<td><span><i></i> 00:03:00</span></td>
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						Discriptive Data Analytics in Excel					</td>

					
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					<td><span><i></i> 00:10:00</span></td>
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						Outlier Treatment					</td>

					
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					<td><span><i></i> 00:04:00</span></td>
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						Identifying and Treating Outliers in Excel					</td>

					
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					<td><span><i></i> 00:04:00</span></td>
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						Missing Value Imputation					</td>

					
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					<td><span><i></i> 00:03:00</span></td>
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						Identifying and Treating missing values in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
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						Variable Transformation in Excel					</td>

					
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					<td><span><i></i> 00:03:00</span></td>
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						Dummy variable creation: Handling qualitative data					</td>

					
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
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						Dummy Variable Creation in Excel					</td>

					
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					<td><span><i></i> 00:07:00</span></td>
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						Correlation Analysis					</td>

					
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					<td><span><i></i> 00:09:00</span></td>
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						Creating Correlation Matrix in Excel					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
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					<td colspan="4">Creating Regression Model</td>
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						The Problem Statement					</td>

					
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					<td><span><i></i> 00:01:00</span></td>
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						Basic Equations and Ordinary Least Squares (OLS) method					</td>

					
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					<td><span><i></i> 00:08:00</span></td>
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						Assessing accuracy of predicted coefficients					</td>

					
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					<td><span><i></i> 00:14:00</span></td>
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						Assessing Model Accuracy: RSE and R squared					</td>

					
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					<td><span><i></i> 00:07:00</span></td>
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						Creating Simple Linear Regression model					</td>

					
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					<td><span><i></i> 00:02:00</span></td>
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						Multiple Linear Regression					</td>

					
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
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						The F - statistic					</td>

					
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					<td><span><i></i> 00:08:00</span></td>
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						Interpreting results of Categorical variables					</td>

					
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					<td><span><i></i> 00:05:00</span></td>
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					<td>
						Creating Multiple Linear Regression model					</td>

					
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
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					<td colspan="4">What-if analysis</td>
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						Excel: Running Linear Regression using Solver					</td>

					
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
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					<td colspan="4">Assessment</td>
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					<td><i></i></td>
					<td>Assessment - Linear Regression Analysis In MS Excel</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
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								<tr>
					<td colspan="4">Certificate of Achievement</td>
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					<td><i></i></td>
					<td>
						Certificate of Achievement					</td>

					
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Get Your Insurance Now</td>
				</tr>
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					<td><i></i></td>
					<td>
						Get Your Insurance Now					</td>

					
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
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								<tr>
					<td colspan="4">Feedback</td>
				</tr>
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					<td><i></i></td>
					<td>
						Feedback					</td>

					
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Linear Regression Analysis in Microsoft Excel

<strong>This course covers the fundamental topics of statistical methodology, enabling you to understand the application and interpretation of linear and non-linear regression modeling.</strong>
        <p>Working with statistics and quantitative reports requires a good understanding of statistics fundamentals and techniques. However, learning and applying new statistical techniques can often be a daunting experience. This is where this course comes into play.
To make your experience with statistics a pleasant one, this course gives you comprehensive knowledge of basic principles of the statistical methodology, focusing on linear regression and non-linear regression.
The course starts with an introduction to easy statistics and gives you an overview of the course objectives. Next, you will explore the types of regression analysis that exist and find out how ordinary least squares (OLS) works. To gain a deeper understanding of linear regression and OLS, you will learn to interpret and analyze complicated regression output from OLS. You will also focus on Gauss-Markov assumptions and zero conditional mean. Moving ahead, you will cover non-linear regression, exploring how it works, what the different non-linear regression models are, and the major uses. Towards the end, you will learn to work around with regression modeling with the help of practical examples.
By the end of this video, you will be well-versed with linear and non-linear regression and the basic principles of the statistical methodology.

All the resource files are added on GitHub at https://github.com/PacktPublishing/-Easy-Statistics-Linear-and-Non-Linear-Regression</p>
        <h2>What You Will Learn</h2><p>Understand the basic concept of statistical regression analysis<br>Become familiar with linear and non-linear regression terminologies<br>Distinguish between different types of regression methods<br>Analyze and integrate complicated regression output from ordinary least squares (OLS)<br>Find out the difference between logit and probit transformation<br>Model non-linear relationships in a linear regression</p>
        <h2>Audience</h2><p>If you're a student, an experienced professional, a manager, or a government worker who wants to learn linear and non-linear regression, regression modeling, and ordinary least squares, then this course is for you. This is a beginner-level course and does not require any prior knowledge of mathematics or statistics.</p>
        <h2>Approach</h2><p>With the help of eye-catching animated graphics and interesting examples, this course will teach you linear and non-linear regression and regression modeling to ensure that you become well-versed with the fundamentals of statistics and quantitative analysis.</p>
        <h2>Key Features</h2><p>Understand the statistical fundamentals of ordinary least squares (OLS) * Gain the confidence to comfortably interpret complicated regression output from OLS * Explore regression modeling and its application</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/-Easy-Statistics-Linear-and-Non-Linear-Regression</p>
        <h2>About the Author</h2><h3>Franz Buscha</h3><p>Franz Buscha is a professor of economics at the University of Westminster, which he joined after completing his Ph.D. in economics at Lancaster University. He has been involved in numerous funded research projects from research councils and government departments. He has also contributed to a wide range of projects, including policy evaluation and bespoke econometric advice to UK government departments. Franz has published in leading journals and contributed to numerous policy reports. His research has even been covered by various media outlets. He is an experienced online educator and has published several online courses, including LinkedIn Learning. Franz also has a monthly radio program called Policy Matters on Share Radio.</p>
        <h2>Course Outline</h2><h4>1. Linear Regression</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What is Easy Statistics: Linear Regression?</p><p style='margin: 0'>This video explains the concept of easy statistics with linear regression.</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Linear Regression?</p><p style='margin: 0'>This video explains the concept of linear regression.</p></td></tr><tr><td style='padding: 15px;'><p>3. Learning Outcomes</p><p style='margin: 0'>This video explains the various learning outcomes.</p></td></tr><tr><td style='padding: 15px;'><p>4. Whom is this Course for?</p><p style='margin: 0'>This video discusses the target audience for this course.</p></td></tr><tr><td style='padding: 15px;'><p>5. Prerequisites</p><p style='margin: 0'>This video explains the various prerequisites of the course.</p></td></tr><tr><td style='padding: 15px;'><p>6. Using Stata</p><p style='margin: 0'>This video shows how to use Stata for linear regression.</p></td></tr><tr><td style='padding: 15px;'><p>7. What is Regression Analysis?</p><p style='margin: 0'>This video explains the concept of regression analysis.</p></td></tr><tr><td style='padding: 15px;'><p>8. Get to Know About Linear Regression</p><p style='margin: 0'>This video explains the concept of linear regression in detail.</p></td></tr><tr><td style='padding: 15px;'><p>9. Why is Regression Analysis Useful?</p><p style='margin: 0'>This video explains the importance and uses of regression analysis.</p></td></tr><tr><td style='padding: 15px;'><p>10. What Types of Regression Analysis Exist?</p><p style='margin: 0'>This video explains the various types of regression analysis.</p></td></tr><tr><td style='padding: 15px;'><p>11. Explaining Regression</p><p style='margin: 0'>This video explains the concept of regression.</p></td></tr><tr><td style='padding: 15px;'><p>12. Lines of Best Fit</p><p style='margin: 0'>This video explains the lines of best fit concept.</p></td></tr><tr><td style='padding: 15px;'><p>13. Causality vs. Correlation</p><p style='margin: 0'>This video illustrates the difference between causality and correlation.</p></td></tr><tr><td style='padding: 15px;'><p>14. What is Ordinary Least Squares (OLS)?</p><p style='margin: 0'>This video explains the concept of OLS.</p></td></tr><tr><td style='padding: 15px;'><p>15. Ordinary Least Squares (OLS) Visual - Part 1</p><p style='margin: 0'>This video is the first part of the two-part video that explains OLS visually.</p></td></tr><tr><td style='padding: 15px;'><p>16. Ordinary Least Squares (OLS) Visual - Part 2</p><p style='margin: 0'>This video is the second part of the two-part video that explains OLS visually.</p></td></tr><tr><td style='padding: 15px;'><p>17. Sum of Squares</p><p style='margin: 0'>This video explains how to calculate the sum of squares using linear regression.</p></td></tr><tr><td style='padding: 15px;'><p>18. Best Linear Unbiased Estimator</p><p style='margin: 0'>This video explains the best linear unbiased estimator.</p></td></tr><tr><td style='padding: 15px;'><p>19. The Gauss-Markov Assumptions</p><p style='margin: 0'>This video discusses the Gauss-Markov assumptions.</p></td></tr><tr><td style='padding: 15px;'><p>20. Homoskedasticity</p><p style='margin: 0'>This video explains the concept of homoskedasticity.</p></td></tr><tr><td style='padding: 15px;'><p>21. No Perfect Collinearity</p><p style='margin: 0'>This video explains the concept of no perfect collinearity.</p></td></tr><tr><td style='padding: 15px;'><p>22. Linear in Parameters</p><p style='margin: 0'>This video focuses on linearity in parameters.</p></td></tr><tr><td style='padding: 15px;'><p>23. Zero Conditional Mean</p><p style='margin: 0'>This video explains what is zero conditional mean.</p></td></tr><tr><td style='padding: 15px;'><p>24. How to Test and Correct for Endogeneity?</p><p style='margin: 0'>This video explains how to test and correct for endogeneity.</p></td></tr><tr><td style='padding: 15px;'><p>25. The Gauss-Markov Assumptions - Recap</p><p style='margin: 0'>This video presents a recap of the Gauss-Markov assumptions.</p></td></tr><tr><td style='padding: 15px;'><p>26. Stata - Applied Examples</p><p style='margin: 0'>This video explains with an example how to use Stata.</p></td></tr><tr><td style='padding: 15px;'><p>27. Final Thoughts and Tips</p><p style='margin: 0'>This video provides some final thoughts and tips with respect to linear regression.</p></td></tr></tbody></table><br><h4>2. Non-Linear Regression</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What is Easy Statistics: Non-Linear Regression?</p><p style='margin: 0'>This video explains the concept of easy statistics with non-linear regression.</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Non-Linear Regression?</p><p style='margin: 0'>This video explains the concept of non-linear regression.</p></td></tr><tr><td style='padding: 15px;'><p>3. What are the Main Learning Outcomes?</p><p style='margin: 0'>This video presents the learning outcome of this course.</p></td></tr><tr><td style='padding: 15px;'><p>4. Whom is this Course for?</p><p style='margin: 0'>This video discusses the target audience for this course.</p></td></tr><tr><td style='padding: 15px;'><p>5. Prerequisites</p><p style='margin: 0'>This video discusses the various prerequisites for this course.</p></td></tr><tr><td style='padding: 15px;'><p>6. Using Stata</p><p style='margin: 0'>This video explains how to use Stata.</p></td></tr><tr><td style='padding: 15px;'><p>7. What is Non-Linear Regression Analysis?</p><p style='margin: 0'>This video explains the concept of non-linear regression analysis.</p></td></tr><tr><td style='padding: 15px;'><p>8. How does Non-Linear Regression Work?</p><p style='margin: 0'>This video explains the working of non-linear regression.</p></td></tr><tr><td style='padding: 15px;'><p>9. Why is Non-Linear Regression analysis Useful?</p><p style='margin: 0'>This video explains the importance and uses of non-linear regression analysis.</p></td></tr><tr><td style='padding: 15px;'><p>10. Types of Non-Linear Regression models</p><p style='margin: 0'>This video explains the various types of non-linear regression models.</p></td></tr><tr><td style='padding: 15px;'><p>11. Maximum Likelihood</p><p style='margin: 0'>This video explains the maximum likelihood estimation technique.</p></td></tr><tr><td style='padding: 15px;'><p>12. Linear Probability Model</p><p style='margin: 0'>This video explains the linear probability model.</p></td></tr><tr><td style='padding: 15px;'><p>13. The Logit and Probit Transformation</p><p style='margin: 0'>This video explains the logit and probit transformation model.</p></td></tr><tr><td style='padding: 15px;'><p>14. Latent Variables</p><p style='margin: 0'>This video focuses on latent variables.</p></td></tr><tr><td style='padding: 15px;'><p>15. What are Marginal Effects?</p><p style='margin: 0'>This video explains the concept of marginal effects.</p></td></tr><tr><td style='padding: 15px;'><p>16. Dummy Explanatory Variables</p><p style='margin: 0'>This video focuses on the dummy explanatory variables.</p></td></tr><tr><td style='padding: 15px;'><p>17. Multiple Non-Linear Regression</p><p style='margin: 0'>This video explains multiple non-linear regression.</p></td></tr><tr><td style='padding: 15px;'><p>18. Goodness-of-Fit</p><p style='margin: 0'>This video discusses the concept of goodness-of-fit.</p></td></tr><tr><td style='padding: 15px;'><p>19. A Note about Logit Coefficients</p><p style='margin: 0'>This video provides a note about logit coefficients.</p></td></tr><tr><td style='padding: 15px;'><p>20. Tips for Logit and Probit Regression</p><p style='margin: 0'>This video provides some tips for logit and probit regression.</p></td></tr><tr><td style='padding: 15px;'><p>21. Back to the Linear Probability Model</p><p style='margin: 0'>This video explains the linear probability model.</p></td></tr><tr><td style='padding: 15px;'><p>22. Stata - Applied Logit and Probit Examples</p><p style='margin: 0'>This video provides examples of applied logit and probit using Stata.</p></td></tr></tbody></table><br><h4>3. Regression Modelling</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video provides an introduction to regression modelling.</p></td></tr><tr><td style='padding: 15px;'><p>2. Regression Modelling - Don't Rush it</p><p style='margin: 0'>This video explains the concept of regression modelling in detail.</p></td></tr><tr><td style='padding: 15px;'><p>3. Non-Linear Shapes in Regression</p><p style='margin: 0'>This video explains the concept of non-linear shapes in regression.</p></td></tr><tr><td style='padding: 15px;'><p>4. Non-Linear Shapes in Regression - Practical Examples</p><p style='margin: 0'>This video explains the concept of non-linear shapes in regression with the help of examples.</p></td></tr><tr><td style='padding: 15px;'><p>5. How to use and Interpret Interaction Effects?</p><p style='margin: 0'>This video explains how to use and interpret interaction effects.</p></td></tr><tr><td style='padding: 15px;'><p>6. How to use and Interpret Interaction Effects? - Practical Examples</p><p style='margin: 0'>This video explains how to use and interpret interaction effects with the help of examples.</p></td></tr><tr><td style='padding: 15px;'><p>7. Using Time in Regression</p><p style='margin: 0'>This video explains how to use time in regression.</p></td></tr><tr><td style='padding: 15px;'><p>8. Using Time in Regression - Practical Examples</p><p style='margin: 0'>This video explains how to use time in regression with the help of examples.</p></td></tr><tr><td style='padding: 15px;'><p>9. Categorical Explanatory Variables in Regression</p><p style='margin: 0'>This video explains the categorical explanatory variables in regression.</p></td></tr><tr><td style='padding: 15px;'><p>10. Categorical Explanatory Variables in Regression - Practical Examples</p><p style='margin: 0'>This video explains the categorical explanatory variables in regression with the help of examples.</p></td></tr><tr><td style='padding: 15px;'><p>11. Dealing with Multicollinearity in Regression</p><p style='margin: 0'>This video explains how to deal with multicollinearity in regression.</p></td></tr><tr><td style='padding: 15px;'><p>12. Dealing with Multicollinearity in Regression - Practical Examples</p><p style='margin: 0'>This video explains how to deal with multicollinearity in regression with the help of examples.</p></td></tr><tr><td style='padding: 15px;'><p>13. Dealing with Missing Data in Regression</p><p style='margin: 0'>This video explains how to deal with missing data in regression.</p></td></tr><tr><td style='padding: 15px;'><p>14. Dealing with Missing Data in Regression - Practical Examples</p><p style='margin: 0'>This video explains how to deal with missing data in regression with the help of examples.</p></td></tr></tbody></table>

Stata

Statistics

This course covers the fundamental topics of statistical methodology, enabling you to understand the application and interpretation of linear and non-linear regression modeling.

Easy Statistics: Linear and Non-Linear Regression

<strong>This course covers the fundamental topics of statistical methodology, linear regression, and ordinary least squares that every statistician needs to know.</strong>
        <p>To work with statistics and quantitative reports, you need to have a good understanding of the fundamentals and techniques of statistics. However, learning and applying new statistical techniques can often be a daunting experience and this is where this video course comes in handy. This course is designed to guide you through the basic principles of statistical methodology in a step-by-step way.
You'll start with an introduction to the course along with an overview of the learning objectives. Next, you'll explore the types of regression analysis that exist, and find out how ordinary least squares (OLS) work. To get a deeper understanding of linear regression and OLS, you'll interpret and analyze complicated regression output from OLS. Finally, you'll discover essential tips and techniques that'll help you to confidently perform regression analysis.
By the end of this video, you'll be well-versed with linear regression techniques and the basic principles of statistical methodology.
The code and resources for this course is available at https://github.com/PacktPublishing/Easy-Statistics-Linear-Regression</p>
        <h2>What You Will Learn</h2><p>Understand the basic concept of statistical regression analysis<br>Become familiar with linear regression terminologies<br>Distinguish between different kinds of regression methods<br>Find out the difference between correlation and causation<br>Analyze and integrate complicated regression output from OLS<br>Explore tips and tricks relating to regression analysis</p>
        <h2>Audience</h2><p>If you are a student at any level, an experienced professional, a manager, or a government worker who wants to delve into statistical regression or work with quantitative reports and policy analysis, then this course is for you. As the course is for beginners, it doesn't require you to have any knowledge of mathematics or statistics.</p>
        <h2>Approach</h2><p>With the help of animated graphics and interesting examples, this course will teach you the fundamentals of statistical regression terminologies.</p>
        <h2>Key Features</h2><p>Explore the basic statistical fundamentals of ordinary least squares (OLS) * Understand linear regression and its application * Gain the confidence to interpret complicated regression output</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Easy-Statistics-Linear-Regression</p>
        <h2>About the Author</h2><h3>Franz Buscha</h3><p>Franz Buscha is a professor of economics at the University of Westminster, which he joined after completing his Ph.D. in economics at Lancaster University. He has been involved in numerous funded research projects from research councils and government departments. He has also contributed to a wide range of projects, including policy evaluation and bespoke econometric advice to UK government departments. Franz has published in leading journals and contributed to numerous policy reports. His research has even been covered by various media outlets. He is an experienced online educator and has published several online courses, including LinkedIn Learning. Franz also has a monthly radio program called Policy Matters on Share Radio.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><br><h4>2. What is Regression?</h4><p></p><br><h4>3. What is Ordinary Least Squares?</h4><p></p><br><h4>4. Ordinary Least Squares Regression in Practice</h4><p></p><br><h4>5. Tips and Final Thoughts </h4><p></p>

This course covers the fundamental topics of statistical methodology, linear regression, and ordinary least squares that every statistician needs to know.

Easy Statistics: Linear Regression

SkillWise

Advanced Linear Programming

<p><strong></strong><strong> Our Aim Is Your Satisfaction! Offer Ends Soon; Hurry Up!! </strong><strong></strong></p><p><strong>Are you looking to improve your current abilities or make a career move? Our unique</strong><strong> Statistical Concepts in R</strong><strong> course might help you get there! Expand your expertise with high-quality training - study the</strong><strong> Statistical Concepts in R </strong><strong>course and get an expertly designed, great-value training experience. Learn from industry professionals and quickly equip yourself with the specific knowledge and skills you need to excel in your chosen career through the</strong><strong> Statistical Concepts in R </strong><strong>online training course.</strong></p><p>The Statistical Concepts in R course is broken down into several in-depth modules to provide you with the most convenient and rich learning experience possible. Upon successful completion of the Statistical Concepts in R course, an instant e-certificate will be exhibited in your profile that you can order as proof of your skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.</p><p>This Statistical Concepts in R training can help you to accomplish your ambitions and prepare you for a meaningful career. So, join us today and gear up for excellence!</p><p><strong>Why Prefer Us? </strong></p><ul><li>Opportunity to earn a certificate accredited by <strong>CPDQS.</strong></li><li><strong>Get a free student ID </strong>card! (£10 postal charge will be applicable for international delivery)</li><li>Innovative and Engaging Content.</li><li>Free Assessments</li><li>24/7 Tutor Support.</li></ul> <p>Take a step toward a brighter future!</p><p><strong>*** Course Curriculum ***</strong></p><p><strong>Module 01: Introduction to the Course</strong></p><ul><li>Introduction</li></ul><p><strong>Module 02: Simple Linear Regression</strong></p><ul><li>Install R, RStudio and Basic Functionality</li><li>Basics of Linear Regression</li><li>Basics of Linear Regression continued</li></ul><p><strong>Module 03: Linear Regression Analysis</strong></p><ul><li>Linear Relationships</li><li>Line of Best Fit, SSE and MSE</li><li>Linear Regression Analysis Continued</li><li>Regression Results and Interpretation</li><li>Predicting Future Profits</li><li>Statistical Validity Tests</li><li>Statistical Validity Discussion</li></ul><p><strong>Module 04: Multiple Linear Regression</strong></p><ul><li>Multiple Linear Regression</li><li>Importing the data</li><li>Correlation Matrix and MLR</li><li>MLR Results and ANOVA</li><li>The Best Model?</li><li>Interaction Terms and Validity Testing</li><li>ANOVA and Predictions</li></ul><p><strong>Module 05: Non-linear Regression</strong></p><ul><li>Non-linear Regression (and Recap)</li><li>Logistic Regression Overview</li><li>Logistic Regression: Odds, Logs and Poisson</li><li>Logistic Regression: Fitting the Models in R</li></ul><p><strong>Assessment Process</strong></p><p>Your skills and knowledge will be tested with an <strong>automated multiple-choice assessment</strong>. You will then receive instant results to let you know if you have successfully passed the Statistical Concepts in R course.</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">
                            <p>Anyone interested in learning more about the topic is advised to take this Statistical Concepts in R course. This course is open to everybody.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

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

                        <div id="career_path">
                            <p>After completing this course, you are to start your career or begin the next phase of your career.</p>
                        </div>

 Our Aim Is Your Satisfaction! Offer Ends Soon; Hurry Up!! 
Are you looking to improve your current abilities or make a career move? Our unique Statistical Concepts in R course might help you get there! Expand your expertise with high-quality training - study the Statistical Concepts in R course and get an expertly designed, great-value training experience. Learn from industry professionals and quickly equip yourself with the specific knowledge and skills you need to excel in your chosen career through the Statistical Concepts in R online training course.
The Statistical Concepts in R course is broken down into several in-depth modules to provide you with the most convenient and rich learning experience possible. Upon successful completion of the Statistical Concepts in R course, an instant e-certificate will be exhibited in your profile that you can order as proof of your skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.
This Statistical Concepts in R training can help you to accomplish your ambitions and prepare you for a meaningful career. So, join us today and gear up for excellence!
Why Prefer Us? 
Opportunity to earn a certificate accredited by CPDQS.
Get a free student ID card! (£10 postal charge will be applicable for international delivery)
Innovative and Engaging Content.
Free Assessments
24/7 Tutor Support.
Take a step toward a brighter future!
*** Course Curriculum ***
Module 01: Introduction to the Course
Introduction
Module 02: Simple Linear Regression
Install R, RStudio and Basic Functionality
Basics of Linear Regression
Basics of Linear Regression continued
Module 03: Linear Regression Analysis
Linear Relationships
Line of Best Fit, SSE and MSE
Linear Regression Analysis Continued
Regression Results and Interpretation
Predicting Future Profits
Statistical Validity Tests
Statistical Validity Discussion
Module 04: Multiple Linear Regression
Multiple Linear Regression
Importing the data
Correlation Matrix and MLR
MLR Results and ANOVA
The Best Model?
Interaction Terms and Validity Testing
ANOVA and Predictions
Module 05: Non-linear Regression
Non-linear Regression (and Recap)
Logistic Regression Overview
Logistic Regression: Odds, Logs and Poisson
Logistic Regression: Fitting the Models in R
Assessment Process
Your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the Statistical Concepts in R course.
 CPD 
10 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Anyone interested in learning more about the topic is advised to take this Statistical Concepts in R course. This course is open to everybody.
 Requirements 
You will not need any prior background or expertise to enrol in this course.
 Career path 
After completing this course, you are to start your career or begin the next phase of your career.

Academy for Health and Fitness

Statistical Computing

Trainers Course

Statistical Concepts in R

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">In this workshop we address Bereavement.&nbsp;Grief is a complex emotion that stems from various losses, not just death. It encompasses feelings of loss from relationships, dreams, health, and more. Losing a partner or a family member can profoundly impact one&#39;s life and support system. Children face unique challenges in grieving, which require careful support. The grieving process is unpredictable and non-linear, involving stages like denial, anger, and acceptance. Hypnotherapy offers a therapeutic approach to address emotional processing, trauma, and acceptance, aiding individuals in navigating their grief journey. While grief is universal, seeking support and exploring therapeutic options like hypnotherapy can help individuals find healing and solace amidst their pain.</p>

In this workshop we address Bereavement. Grief is a complex emotion that stems from various losses, not just death. It encompasses feelings of loss from relationships, dreams, health, and more. Losing a partner or a family member can profoundly impact one's life and support system. Children face unique challenges in grieving, which require careful support. The grieving process is unpredictable and non-linear, involving stages like denial, anger, and acceptance. Hypnotherapy offers a therapeutic approach to address emotional processing, trauma, and acceptance, aiding individuals in navigating their grief journey. While grief is universal, seeking support and exploring therapeutic options like hypnotherapy can help individuals find healing and solace amidst their pain.

The Northern College Of Clinical Hypnotherapy

Grief Healing

Bereavement

Hypnotherapy offers a therapeutic approach to address emotional processing, trauma, and acceptance, aiding individuals in navigating their grief journey. While grief is universal, seeking support and exploring therapeutic options like hypnotherapy can help individuals find healing and solace amidst their pain.

Module 7 Part 2 Bereavement & working with loss 

Probability

Pandas

Start your data science journey with this carefully constructed comprehensive course and get hands-on experience with Python for data science. Gain in-depth knowledge about core Python and essential mathematical concepts in linear algebra, probability, and statistics. Complete data science training with 13+ hours of content.

Data Science 101: Methodology, Python, and Essential Math

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			<h2>Overview
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					<p><span>This comprehensive course on <strong>Algebra Fundamentals </strong></span>will deepen your understanding on this topic.</p><p><span><span>After successful completion of this course you can acquire the required skills in this sector. This <strong>Algebra Fundamentals</strong></span> comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.</span></p><p><span><span>So enrol in this course today to fast track your career ladder.</span></span></p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p><span>You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.</span></p>					</div>
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			<h2>Who is This course for?</h2>		</div>
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					<p><span>There is no experience or previous qualifications required for enrolment on this <strong>Algebra Fundamentals</strong></span>. It is available to all students, of all academic backgrounds.</p>					</div>
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				</div>
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			<h2>Requirements</h2>		</div>
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					<p><span>Our <strong>Algebra Fundamentals</strong></span><strong> </strong>is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</p><p><span><span>There is no time limit for completing this course, it can be studied in your own time at your own pace.</span></span></p>					</div>
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			<h2>Career Path</h2>		</div>
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					<p><span>Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to-</span></p><ul><li>Open doors of opportunities</li><li>Increase your adaptability</li><li>Keep you relevant</li><li>Boost confidence</li></ul><p>And much more!</p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>17 sections • 83 lectures • 11:02:00 total length</p></div><div><div><div><div><div><div><div><p>•Lecture 1 Introduction: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 2 What is Algebra: 00:02:00</p></div><div><div><p>•Lecture 3 Simple Equations: 00:05:00</p></div><div><div><p>•Lecture 4 What are Polynomials: 00:04:00</p></div><div><div><p>•Lecture 5 Terms in Polynomials: 00:03:00</p></div><div><div><p>•Lecture 6 Degree of Polynomials: 00:05:00</p></div><div><div><p>•Lecture 7 Writing statements to algebraic form: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 8 Integers and common mistakes in solving integers: 00:13:00</p></div><div><div><p>•Lecture 9 Arrangement of Terms: 00:07:00</p></div><div><div><p>•Lecture 10 Powers on integers: 00:04:00</p></div><div><div><p>•Lecture11 Simplification using BODMAS: 00:08:00</p></div><div><div><p>•Lecture 12 Distributive Properties in Polynomials: 00:04:00</p></div><div><div><p>•Lecture 13 Simplify Polynomials: 00:10:00</p></div><div><div><p>•Lecture 14 Additions of Polynomials: 00:06:00</p></div><div><div><p>•Lecture 15 Subtractions of Polynomials: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 16 The rules of Indices in algebra: 00:11:00</p></div><div><div><p>•Lecture 17 Fractional indices: 00:10:00</p></div><div><div><p>•Lecture 18 Understanding indices (practice questions): 00:07:00</p></div><div><div><p>•Lecture 19 Problems from IGCSE Last year papers: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 20 Multiplication of monomial to Polynomial: 00:09:00</p></div><div><div><p>•Lecture 21 Multiplication of Polynomial by Polynomial: 00:06:00</p></div><div><div><p>•Lecture 22 Division of algebraic expression by a monomial: 00:08:00</p></div><div><div><p>•Lecture 23 Division of algebraic expression by another polynomial: 00:09:00</p></div><div><div><p>•Lecture 24 Division of a polynomial by another polynomial with remainder: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 25 Rules of brackets: 00:04:00</p></div><div><div><p>•Lecture 26 Simplification by removing brackets: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 27 Simplification of algebraic fractions: 00:07:00</p></div><div><div><p>•Lecture 28 Rules to solve linear equations in one variable: 00:03:00</p></div><div><div><p>•Lecture 29 Solving linear equations in one variable: 00:07:00</p></div><div><div><p>•Lecture 30 Solving complex linear equations in one variable: 00:10:00</p></div><div><div><p>•Lecture 31 Word problems on linear equations in one variable: 00:13:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 32 What are Identities?: 00:05:00</p></div><div><div><p>•Lecture 33 Identity ( a + b ) Â²: 00:13:00</p></div><div><div><p>•Lecture 35 Identity aÂ² - bÂ² = (a-b) (a +b ) new: 00:07:00</p></div><div><div><p>•Lecture 36 -- Standard Identities ( a + b + c ) Â² = a Â² + b Â² + c Â² + 2 a b + 2 a c +2 b c old: 00:07:00</p></div><div><div><p>•Lecture 37 Identity (x + a) (x + b) Identity Derivation &amp; Application new: 00:08:00</p></div><div><div><p>•Lecture 38 Pascal's Triangle _ Identity ( a + b ) Â³ new: 00:07:00</p></div><div><div><p>•Lecture 39 Identities( a - b ) Â³, ( a Â³ + b Â³) and (a Â³ - b Â³) new: 00:13:00</p></div><div><div><p>•Lecture 40 - Standard Identities a Â³ + b Â³ + c Â³ - 3 a b c: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 41 -Changing the subject of formula: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 42 - Linear Inequalities: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 43 - Factorization by taking out common factor: 00:10:00</p></div><div><div><p>•Lecture 44 - Factorization by grouping the terms: 00:09:00</p></div><div><div><p>•Lecture 45 - factorize using identity a Â² - b Â²: 00:07:00</p></div><div><div><p>•Lecture 46 - factorize using identity (a + b )Â² and (a - b )Â² (2): 00:08:00</p></div><div><div><p>•Lecture 47 - factorize using identity ( a + b + c ) Â²: 00:05:00</p></div><div><div><p>•Lecture 48 - factorization by middle term split: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 49 -Simplification of algebraic fractions: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 50 All that you need to know about co ordinate axis: 00:04:00</p></div><div><div><p>•Lecture 51 Some important facts needed to draw line graph: 00:03:00</p></div><div><div><p>•Lecture 52 - How to draw a line graph on coordinate plane: 00:03:00</p></div><div><div><p>•Lecture 53 Drawing line graphs: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 54 Simultaneous Linear Equations in two variables- intro: 00:03:00</p></div><div><div><p>•Lecture 55 Graphical method of solving linear equations: 00:06:00</p></div><div><div><p>•Lecture 56 Graphical method - more problems: 00:10:00</p></div><div><div><p>•Lecture 57 Method of Elimination by substitution: 00:09:00</p></div><div><div><p>•Lecture 58 Method of Elimination by Equating coefficients: 00:11:00</p></div><div><div><p>•Lecture 59 Method of Elimination by cross multiplication: 00:07:00</p></div><div><div><p>•Lecture 60 Equations reducible to simultaneous linear equations: 00:12:00</p></div><div><div><p>•Lecture 61 Word Problems on Linear equations: 00:18:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 62 Polynomials and Zeros of polynomials: 00:10:00</p></div><div><div><p>•Lecture 63 Remainder Theorem: 00:04:00</p></div><div><div><p>•Lecture 64 Factor Theorem: 00:08:00</p></div><div><div><p>•Lecture 65 Practice problems on Remainder and Factor Theorem: 00:09:00</p></div><div><div><p>•Lecture 66 Factorization using factor Theorem: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture 67 Zeros of polynomials Î±, Î² &amp; Î³: 00:10:00</p></div><div><div><p>•Lecture 68 Relation between zeros and coefficients of a polynomials: 00:13:00</p></div><div><div><p>•Lecture 69 Finding polynomials if zeros are known: 00:06:00</p></div><div><div><p>•Lecture 70 Practice problems on zeros of polynomials: 00:10:00</p></div><div><div><p>•Lecture 71Problems solving with Î± and Î² (part 1): 00:11:00</p></div><div><div><p>•Lecture 72 Problems solving with Î± and Î² (part 2): 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Lecture73 what are Quadratic equations: 00:03:00</p></div><div><div><p>•Lecture 74 Solutions by factorization method: 00:12:00</p></div><div><div><p>•Lecture 75 Solutions by completing square formula: 00:06:00</p></div><div><div><p>•Lecture 76 Deriving Quadratic formula: 00:05:00</p></div><div><div><p>•Lecture 77 Practice problems by Quadratic formula: 00:07:00</p></div><div><div><p>•Lecture 78 Solving complex quadratic equations by Quadratic Formula: 00:11:00</p></div><div><div><p>•Lecture 79 Solutions of reducible to Quadratic Formula: 00:09:00</p></div><div><div><p>•Lecture 80 Skilled problems on Quadratic Equations: 00:07:00</p></div><div><div><p>•Lecture 81 Exponential problems reducible to Quadratic Equations: 00:06:00</p></div><div><div><p>•Lecture 82 Nature of Roots of Quadratic Equations: 00:09:00</p></div><div><div><p>•Lecture 83 Word problems on quadratic Equations Part 1: 00:13:00</p></div><div><div><p>•Lecture 84 Word problems on quadratic Equations Part 2: 00:11:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

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