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In this video, we guide you through a comprehensive Generative AI roadmap for beginners, breaking down the essential steps to kickstart your journey. From learning Python and basic machine learning concepts to diving into deep learning and building generative models like GANs and VAEs, this step-by-step guide covers everything you need. Whether you're just starting out or looking to build a solid foundation in AI, this roadmap will give you the skills and confidence to explore the exciting world of Generative AI. Don't miss out on this must-watch for aspiring AI enthusiasts!

✅ How to learn gen AI for beginners?
To learn Generative AI as a beginner, start by mastering Python and basic machine learning concepts. Then, explore deep learning frameworks like TensorFlow or PyTorch. Study neural networks and dive into generative models like GANs and VAEs. Practice with hands-on projects to build real-world experience.

✅ Does generative AI require coding?
Yes, generative AI typically requires coding, especially in languages like Python. You’ll need to understand coding to work with frameworks such as TensorFlow or PyTorch, build models, and manipulate data. However, some tools and platforms now offer low-code or no-code solutions for those with limited programming skills.

✅ Is AI highly paid?
Yes, AI professionals are highly paid due to the increasing demand for specialized skills in machine learning, data science, and AI development. Roles like AI engineers, data scientists, and machine learning specialists command high salaries, reflecting the value of AI expertise in industries like tech, healthcare, finance, and more.

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➡️ About Post Graduate Program In AI And Machine Learning

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

✅ Key Features

- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
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- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered

- ChatGPT
- Generative AI
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- Generative Modeling
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
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- Computer Vision
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This video, Top 30 Machine Learning Interview Questions 2025, brings you the most frequently asked questions and detailed answers to ace your next job interview. Whether you're a fresher or an experienced professional, these machine learning interview questions are designed to help you prepare effectively for roles like Machine Learning Engineer, Data Scientist, or AI Specialist.

Discover insights into key ML concepts, algorithms, and problem-solving techniques that hiring managers value. Learn about important machine learning interview questions and their answers. With this ML interview questions and answers for experienced and freshers guide, become confident in answering questions about various machine learning concepts. Look into the critical questions around concepts such as supervised and unsupervised learning, feature selection, model evaluation, and advanced ML techniques. Don't miss this video, because this is going to enhance your understanding of machine learning and going to help you crack your dream job. Watch now and get ready to shine in your ML interviews!

📖Below are the pointers covered in this 'ML Interview Questions and Answers' video:

🥇 00:00:00 - Introduction to Machine Learning Interview Questions

👨‍💻 ML Interview Questions for Freshers (Basic Level Machine Learning Engineer Interview Questions):
Q1. What is Machine Learning, and why is it important?
Q2. Differentiate between supervised, unsupervised, and reinforcement learning.
Q3. What is a model in machine learning, and how is it used?
Q4. Explain overfitting and underfitting with examples.
Q5. What is a confusion matrix, and how is it used in evaluating models?
Q6. Define cross-validation. Why is it important in model evaluation?
Q7. What is the role of precision and recall in evaluating a model?
Q8. What is the F1 score, and how is it calculated?
Q9. What is the purpose of regularization in machine learning?
Q10. Explain the bias-variance trade-off.

👨‍💻 Intermediate Level Machine Learning Interview Questions:
Q11. What is feature engineering, and why is it crucial in machine learning?
Q12. Example of when a False positive is more crucial than a false negative and vice versa
Q13. What does naivety stand for in naive Bayes?
Q14. Give an example where the median is a better measure than the mean.
Q15. What are the key differences between bagging and boosting in ensemble methods?
Q16. How does a decision tree work in machine learning?
Q17. What is the principal component analysis (PCA), and when should it be used?
Q18. How does a support vector machine (SVM) classify data?
Q19. What is a dropout in neural networks, and how does it prevent overfitting?
Q20. Differentiate between batch gradient descent and stochastic gradient descent.

👨‍💻 Advanced Level Machine Learning Interview Questions for Experienced:
Q21. You notice that your model is overfitting on the training data. What steps would you take to address this issue?
Q22. How would you evaluate a model's performance using a Receiver Operating Characteristic (ROC) curve?
Q23. Describe a situation where regularization (L1 or L2) significantly improved your model's performance.
Q24. You are given a dataset with imbalanced classes. How would you handle this during model training?
Q25. Explain GAN.
Q26. Explain CNN.
Q27. Explain how recurrent neural networks (RNNs) are used for time-series data. Provide an example.
Q28. What strategy would you use to tune hyperparameters for a Random Forest or gradient-boosting model?
Q29. Describe a real-world scenario where reinforcement learning could be applied effectively.
Q30. How would you optimize the training of a deep neural network on a large-scale dataset with limited computational resources?

✅ How do I prepare for a machine learning interview?
Preparing for a machine learning interview involves mastering the fundamentals of ML concepts like supervised and unsupervised learning, algorithms, and model evaluation techniques. Work on real-world ML projects to showcase hands-on experience and build a strong portfolio.

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IoT architecture determines the efficiency and working of an IoT set-up. The concept behind the Internet of Things is as powerful as it is complex, and in order for the elements in the IoT puzzle to mesh together perfectly, they all have to be part of a well-thought-out structure. This is where IoT architecture enters into play. In this video, we'll understand the complete IoT structure.
Below topics are explained in this IoT architecture tutorial:
1. IoT Architecture - 0:00
2. IoT device architecture - 0:22
3. IoT reference architecture - 1:22
4. IoT standardization and design considerations - 4:04
5. IoT in smart farming - 8:40

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What is IoT?
IoT is the interconnection of computing devices embedded in everyday objects, enabling them to send and receive data via the Internet.

Introduction to IoT Training Course:
If you’re new to the Internet of Things (IoT) and want to leverage it across business functions, then this introductory course is for you. You’ll get a glimpse into the ever-growing field of IoT, a technology that allows the intelligent exchange of data among a network of internet-connected objects.

Course Overview:
The primary objective of this Introduction to IoT Training Course is to give you insights into the bright and exciting future of the Internet of Things (IoT). The course will familiarize you with IoT concepts, their origin, impact, methodologies and tools, and how IoT is integrated into business applications to improve business results.

Key Features:
- 2 hours of in-depth eLearning
- Lifetime access to self-paced learning
- Industry-relevant course completion certificate
- Comprehensive industry-relevant use cases and case studies

Eligibility:
This IoT course caters to CXO level and middle management professionals who want to enhance business value and ROI leveraging IoT. Simplilearn’s Introduction to IoT Training Course is ideal for anyone who wants to learn the fundamentals of IoT or pursue a career in this growing field.

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In this "Six Sigma Full Course Video", we'll teach you everything you need to know about Six Sigma and its underlying concepts in detail! Starting with Lean Six Sigma Explained with Six Sigma Green Belt Training including proper references. By the end of this video all your doubts related to lean six sigma would be cleared.

So without further ado, let’s jump in.
00:00:00 Six Sigma Explained
00:16:11 Introduction to six sigma
00:29:02 Six Sigma overview
01:07:09 Six Sigma Green belt - Define
02:38:01 Six Sigma Green belt - Measure
04:35:47 Six Sigma Green belt - Analyze
06:13:49 Six Sigma Green belt - Improve
06:44:25 Six Sigma vs Lean

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Learn to develop your organizational projects with the Lean Six Sigma Green Belt certification online program. Aligned to the IASSC exam, this online six sigma certification integrates lean and the DMAIC methodology with case studies to provide you the skills required for an organization's growth.

About Simplilearn SIx Sigma green belt course:
This Lean Six Sigma Green Belt course provides an overview of Six Sigma and the DMAIC methodology and is aligned to the leading Green Belt certifications at ASQ and IASSC. In this Lean Six Sigma Green Belt course, you will learn how to measure current performance to identify process issues and how to formulate solutions.

Six Sigma Green Belt Training Key Features:
- 56 hours of high-quality blended learning
- 33 PDUs offered
- 4 simulation test papers, 4 real-life projects
- Aligned to ASQ and IASSC

Eligibility:
Lean Six Sigma professionals are in high demand due to their ability to use problem-solving techniques to reach business solutions and assuring quality control throughout the process. The Lean Six Sigma Green Belt certification is ideal for Quality system managers, Quality engineers, Quality supervisors, Quality analysts and managers, Quality auditors, and any individual wishing to improve quality and process within an organization.

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This video, titled "What is RPA?" gives a basic overview of RPA and its ideas. We learn about what RPA is, why it is being widely used across industries, how it works, the results of using RPA, and finally, its growth estimates over the last few years. So, let's jump right in.
0:00 - Start
0:50 - What is RPA?
1:51 - Working of RPA
2:46 - Advantages of RPA
3:29 - Applications of RPA
3:42 - Future of RPA
4:23 - Quiz


Don't forget to take the quiz at 04:24! Comment below what you think is the right answer, to be one of the 3 lucky winners who can win Amazon vouchers worth INR 500 or $10! (Depending on your location). What are you waiting for? Winners will be announced on May 27th, 2020.

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What is RPA?
Robotic Process Automation (RPA) is the use of software with Artificial Intelligence and Machine Learning capabilities to handle high-volume, repetitive tasks that previously required humans to perform. Some of these tasks include addressing queries, making calculations, maintenance of records, and performing transactions.

If you want to expand your expertise in advanced intelligent applications, then this Introduction to Robotic Process Automation (RPA) course will put you on the fast track. RPA is one of the hottest and fastest-growing technologies for improving real-time business operations and processes. This course will give you an overview of RPA concepts, the value-add it brings with relevant business use cases and tools understanding.

What are the benefits of this course?
Robotic Process Automation (RPA) is an advanced technology that automates huge quantities of redundant tasks by applying artificial intelligence (AI). RPA can be used for processing transactions, manipulating data, triggering responses and communicating with other digital systems. RPA has applications in a plethora of industries including insurance claims processing, invoice processing, customer feedback analysis, onboarding of employees, HR operations, and much more. More on the RPA market:
- The global market for RPA software and services is expected to grow to $1.2 billion by 2021 at a compound annual growth rate of 36 per cent.
- One wine producer increased its order accuracy from 98% to 99.7% while reducing costs There are 3000+ RPA job postings in India and the US.

What are the course objectives?
The primary objective of this Introduction to RPA training course is to give you a glimpse into the bright and exciting future of Robotic Process Automation and to give you an overview of the fundamental methodologies and tools that will help you employ RPA on the job. You’ll learn the key RPA tools and workflows used in intelligent automation, steps for implementing RPA in your enterprise and case studies that will provide innovative best practices.

Upon successful completion of our Introduction to Robotics Process Automation online training course, you will gain a fair understanding of RPA and related business applications. By the end of the course, you will be able to understand-
1. RPA and it's business applications
2. The impact that RPA creates with significant ROI
3. Various tools available in the market and their right fit
4. Organization and management of a real-life workflow automation project

Who should take this course?
Simplilearn’s Introduction to Robotic Process Automation course is best suited for:
1. CXOs
2. Team Leads
3. Business Analysts
4. Solution Architects

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This video on Top 10 Technologies to learn in 2022 brings to you the trending technologies in 2022 that you should watch out for. With time, new technologies are evolving, technologies that help address global challenges and those that will make life simpler in the coming years. Let's get started and have a look at the top technologies of the future!

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00:46 ✅10. Robotics - Robotics is a significant industry that is gaining momentum with time. Some of the core robotics skills you need to possess are Python, Matlab, problem-solving, mathematics, and machine learning.
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01:44 ✅9. Augmented Reality and Virtual Reality - Augmented reality blends real-world elements with virtual ones, whereas Virtual reality creates an environment that is fully virtual.
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02:34 ✅8. Big Data and Analytics - Big Data and Analytics allow you to store, process, analyze, and make sense of vast amounts of data using cutting-edge technologies.
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03:32 ✅7. Quantum Computing - Quantum computing is now a tool that’s changing the face of several industries.
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04:20 ✅6. 5G networks - According to the GSM Association, by 2025, 5G networks are estimated to have more than 1.7 billion subscribers across the globe.
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05:11 ✅5. IoT - The Internet of things is fast becoming an integral part of our lives. The top-in-demand IoT skills are Machine learning & AI, Python & JavaScript, Big Data, and Node.js.
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06:09 ✅4. Cyber Security - The onset of the covid 19 pandemic has served as a trigger for a rise in the number of cyberattacks across the globe. Hence, the field of cyber security holds paramount importance in today’s times. To work in this field, skills like knowledge of operating systems, networking, virtualization, and programming are beneficial.
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07:03 ✅3. Blockchain - Blockchain developers need to know concepts like cryptography, data structures, and computer networking.
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07:50 ✅2. Cloud Services - For a successful career in cloud computing, you need to have knowledge of databases, programming, Linux, networking, and APIs.
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08:40 ✅1. Artificial Intelligence - AI is playing a great role in medicine, manufacturing, education, and Mobility.
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Power BI Full Course 2024 By Simplilearn is complete end to end Power BI Tutorial For Beginners that covers the most important concepts of the Power BI Course like, Data Modelling, Data Transformation, Data Visualization, and Data sharing etc. The goal of the full course is to help aspiring data analysts and business analysts to have a compfortable understanding of the power bi data visualisation tool. This power bi full course by Simplilearn covers the following topic:

0:00:00 What Is Power BI?
0:16:05 🔥Install Power Bi
0:37:23 How To Connect Data Sources In Power BI?
2:46:00 Power BI Tutorial For Beginners
3:07:54 How To Connect Data Sources In Power BI?
3:31:15 Data Modelling In Power BI
3:46:09 Data Transformation in Power BI
4:07:31 Top 10 Power BI Charts
4:10:06 How To Create KPI Visuals In Power BI
4:36:31 Creating Calculated Fields In Power BI
5:04:48 DAX In Power BI Tutorial
5:25:20 Sales Dashboard In Power BI
5:38:09 Cutomer Analytics Dashboard Using Power BI
5:49:51 Power Bi vs Tableau

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✅ About Post Graduate Program In Business Analysis
This Post Graduate Program in Business Analysis is for professionals looking to pursue a Business Analysis career, understand business analysis techniques, get hands-on experience, and for experienced analysts looking to learn the latest tools and frameworks used by Agile teams.

✅ Key Features
- Certificate from Simplilearn in collaboration with Purdue University
- Become eligible to be part of the Purdue University Alumni Association
- Master Classes delivered by Purdue faculty
- Earn 35 PDs/CDUs post completion of the CBAP® module
- Harvard Business Publishing case studies of Pearson, CarMax, EvCard, etc.
- Capstone from 3 domains and 14+ projects
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Get mentored and network with Business Analyst from Amazon, Microsoft and Google

✅Skills Required
- Business Analysis
- Elicitation and Collaboration
- BRD FRD and SRS Document Creation
- Requirements AnalysisPlanning and Monitoring
- Requirements Life Cycle Management
- Strategy AnalysisWireframing
- More...

✅Tools Covered
- Excel
- JIRA
- Powerbi
- R
- MySQL

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This " Salesforce Tutorial For Beginners " will provide introduction to salesforce and Salesforce interface. So let's begin with salesforce training!
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This video on Salesforce training will help you understand the easy and best tool for CRM and Branding. You will learn how to customize the home page, create custom tabs. You will know how to upload a company logo to brand Salesforce, generate and convert leads, and build campaigns. You will understand how to create accounts, contacts, and email templates. You will get an idea to develop web-to-lead forms and lots more. Let's begin!

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Gain hands-on experience with this Salesforce certification training course while learning how to manage and develop apps for one of the most popular CRM platforms worldwide. Simplilearn’s Salesforce training enables you to pass two Salesforce certification exams and transform your career.

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This Convolutional neural network tutorial (CNN) will help you understand what is a convolutional neural network, how CNN recognizes images, what are layers in the convolutional neural network and at the end, you will see a use case implementation using CNN. A CNN is also known as a "ConvNet". Convolutional networks can also perform optical character recognition to digitize text and make natural-language processing possible on analog and hand-written documents. CNN can also be applied to sound when it is represented visually as a spectrogram. Now, let's deep dive into this video to understand what is CNN and how do they actually work.

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Below topics are explained in this CNN tutorial (Convolutional Neural Network Tutorial)
1. Introduction to CNN
2. What is a convolutional neural network?
3. How CNN recognizes images?
4. Layers in convolutional neural network
5. Use case implementation using CNN

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Simplilearn’s Deep Learning course will transform you into an expert in deep learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our deep learning course, you’ll master deep learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as deep learning scientist.

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Get a brief introduction to " Lean Six Sigma " in just 8 Minutes and clear your doubts on lean six sigma. Watch complete video to learn more!
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Don't forget to take the quiz at 07:08!

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Learn to develop your organizational projects with the Lean Six Sigma Green Belt certification online program. Aligned to the IASSC exam, this online six sigma certification integrates lean and the DMAIC methodology with case studies to provide you the skills required for an organization's growth.

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This Lean Six Sigma Green Belt course provides an overview of Six Sigma and the DMAIC methodology and is aligned to the leading Green Belt certifications at ASQ and IASSC. In this Lean Six Sigma Green Belt course, you will learn how to measure current performance to identify process issues and how to formulate solutions.

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Who Is A Business Analyst?
A business analyst understands the business problems and identifies the solutions that will maximize the organization's value to its stakeholders. A business analyst is an individual who works closely with the technology team to improve the quality of the services being delivered. They ensure the customer needs are correctly interpreted and translated into application. They possess programming, SQL, and business intelligence skills to deliver data-driven solutions.

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Jumpstart your career as a Business Analysis Professional with this comprehensive curriculum covering the concepts of business analysis tools and techniques, statistics fundamentals, interaction with databases using SQL, and data visualization using excel, Power BI, and Tableau.

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Imagine a world where AI isn't just science fiction but a powerful partner in your business success. This video on AI for Business dives into the exciting world of AI for business, showcasing its revolutionary impact across industries. Witness real-world examples of AI driving innovation in marketing, finance, and manufacturing data analysis on steroids. Imagine the massive benefits of AI for business, predict customer behavior, and make smarter decisions. Get a sneak peek into the future of manufacturing with smart factories (Industry 4.0) and the rise of human-AI collaboration (Industry 5.0). We'll dive into how AI is changing industries like marketing, finance, and supply chain. AI isn't magic, it's the future of business.
00:00:00 Introduction
00:02:11 AI for Business
00:07:38 What Is Artificial Intelligence?
00:14:19 Types Of Artificial Intelligence
00:24:33 AI vs Machine Learning vs Deep Learning
00:38:17 What is Deep Learning
00:49:30 What is LLM (Large Language Model)
01:06:00 What Is Generative AI?
01:21:18 What Is AI Ethics
01:29:55 What is Responsible AI
01:38:09 Artificial Intelligence with Python
03:17:04 Artificial Neural Network
03:48:53 Recurrent Neural Networks
04:17:44 Convolutional Neural Network
04:38:19 Introduction to TensorFlow
05:01:57 Prompt Engineering
05:21:21 Prompt Engineering For Code Generation
05:30:40 Building a Chatbot with Prompt Engineering
05:46:44 OpenAI o3-mini Model
05:53:55 What is Agentic AI?
06:04:59 Introduction to Midjourney
06:23:31 How to use Midjourney?
06:31:15 GitHub Copilot
06:48:34 What is Vibe Coding
06:57:44 Top 5 AI Frameworks in 2025
07:12:29 How AI Is Transforming Studio Ghibli-Style Animation?
07:17:56 AI in Web Development
07:43:07 AI in Healthcare
07:51:49 AI in Retail
07:57:57 AI in Automotive
08:07:52 AI for Marketing
08:20:28 AI in Finance
08:29:04 AI for HR
08:35:25 AI in Manufacturing
08:41:53 AI in Cybersecurity
08:51:41 AI for Startup
09:00:15 AI for Testing
09:05:40 AI for Ethical Hacking
09:10:34 AI on Microsoft Azure
09:23:00 AI and Industry 4.0
09:28:01 AI Engineer Learning Path
09:35:13 Top 15 AI Skills You Need to Know
09:43:33 Build AI Applicant Tracking System (ATS)
09:59:07 Artificial Intelligence Interview Questions & Answers
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Learn Calculus 1 in this full college course.

This course was created by Dr. Linda Green, a lecturer at the University of North Carolina at Chapel Hill. Check out her YouTube channel: https://www.youtube.com/channe....l/UCkyLJh6hQS1TlhUZx

This course combines two courses taught by Dr. Green. She teaches both Calculus 1 and a Calculus 1 Corequisite course, designed to be taken at the same time. In this video, the lectures from the Corquisite course, which review important Algebra and Trigonometry concepts, have been interspersed with the Calculus 1 lectures at the places suggested by Dr. Green.

⭐️ Prerequisites ⭐️
🎥 Algebra: https://www.youtube.com/watch?v=LwCRRUa8yTU
🎥 Precalculus: https://www.youtube.com/watch?v=eI4an8aSsgw

⭐️ Lecture Notes ⭐️
🔗 Calculus 1 Corequisite Notes: http://lindagreen.web.unc.edu/....files/2020/08/course
🔗 Calculus 1 Notes: http://lindagreen.web.unc.edu/....files/2019/12/course

⭐️ Course Contents ⭐️
(0:00:00) [Corequisite] Rational Expressions
(0:09:40) [Corequisite] Difference Quotient
(0:18:20) Graphs and Limits
(0:25:51) When Limits Fail to Exist
(0:31:28) Limit Laws
(0:37:07) The Squeeze Theorem
(0:42:55) Limits using Algebraic Tricks
(0:56:04) When the Limit of the Denominator is 0
(1:08:40) [Corequisite] Lines: Graphs and Equations
(1:17:09) [Corequisite] Rational Functions and Graphs
(1:30:35) Limits at Infinity and Graphs
(1:37:31) Limits at Infinity and Algebraic Tricks
(1:45:34) Continuity at a Point
(1:53:21) Continuity on Intervals
(1:59:43) Intermediate Value Theorem
(2:03:37) [Corequisite] Right Angle Trigonometry
(2:11:13) [Corequisite] Sine and Cosine of Special Angles
(2:19:16) [Corequisite] Unit Circle Definition of Sine and Cosine
(2:24:46) [Corequisite] Properties of Trig Functions
(2:35:25) [Corequisite] Graphs of Sine and Cosine
(2:41:57) [Corequisite] Graphs of Sinusoidal Functions
(2:52:10) [Corequisite] Graphs of Tan, Sec, Cot, Csc
(3:01:03) [Corequisite] Solving Basic Trig Equations
(3:08:14) Derivatives and Tangent Lines
(3:22:55) Computing Derivatives from the Definition
(3:34:02) Interpreting Derivatives
(3:42:33) Derivatives as Functions and Graphs of Derivatives
(3:56:25) Proof that Differentiable Functions are Continuous
(4:01:09) Power Rule and Other Rules for Derivatives
(4:07:42) [Corequisite] Trig Identities
(4:15:14) [Corequisite] Pythagorean Identities
(4:20:35) [Corequisite] Angle Sum and Difference Formulas
(4:28:31) [Corequisite] Double Angle Formulas
(4:36:01) Higher Order Derivatives and Notation
(4:39:22) Derivative of e^x
(4:46:52) Proof of the Power Rule and Other Derivative Rules
(4:56:31) Product Rule and Quotient Rule
(5:02:09) Proof of Product Rule and Quotient Rule
(5:10:40) Special Trigonometric Limits
(5:17:31) [Corequisite] Composition of Functions
(5:29:54) [Corequisite] Solving Rational Equations
(5:40:02) Derivatives of Trig Functions
(5:46:23) Proof of Trigonometric Limits and Derivatives
(5:54:38) Rectilinear Motion
(6:11:41) Marginal Cost
(6:16:51) [Corequisite] Logarithms: Introduction
(6:25:32) [Corequisite] Log Functions and Their Graphs
(6:36:17) [Corequisite] Combining Logs and Exponents
(6:40:55) [Corequisite] Log Rules
(6:49:27) The Chain Rule
(6:58:44) More Chain Rule Examples and Justification
(7:07:43) Justification of the Chain Rule
(7:10:00) Implicit Differentiation
(7:20:28) Derivatives of Exponential Functions
(7:25:38) Derivatives of Log Functions
(7:29:38) Logarithmic Differentiation
(7:37:08) [Corequisite] Inverse Functions
(7:51:22) Inverse Trig Functions
(8:00:56) Derivatives of Inverse Trigonometric Functions
(8:12:11) Related Rates - Distances
(8:17:55) Related Rates - Volume and Flow
(8:22:21) Related Rates - Angle and Rotation
(8:28:20) [Corequisite] Solving Right Triangles
(8:34:54) Maximums and Minimums
(8:46:18) First Derivative Test and Second Derivative Test
(8:51:37) Extreme Value Examples
(9:01:33) Mean Value Theorem
(9:09:09) Proof of Mean Value Theorem
(0:14:59) [Corequisite] Solving Right Triangles
(9:25:20) Derivatives and the Shape of the Graph
(9:33:31) Linear Approximation
(9:48:28) The Differential
(9:59:11) L'Hospital's Rule
(10:06:27) L'Hospital's Rule on Other Indeterminate Forms
(10:16:13) Newtons Method
(10:27:45) Antiderivatives
(10:33:24) Finding Antiderivatives Using Initial Conditions
(10:41:59) Any Two Antiderivatives Differ by a Constant
(10:45:19) Summation Notation
(10:49:12) Approximating Area
(11:04:22) The Fundamental Theorem of Calculus, Part 1
(11:15:02) The Fundamental Theorem of Calculus, Part 2
(11:22:17) Proof of the Fundamental Theorem of Calculus
(11:29:18) The Substitution Method
(11:38:07) Why U-Substitution Works
(11:40:23) Average Value of a Function
(11:47:57) Proof of the Mean Value Theorem for Integrals

Sing's Best Songs - "Let me hear you sing!" Groove with all your favorite songs featuring Rosita (Reese Witherspoon), Meena (Tori Kelly), Gunter (Nick Kroll), Ash (Scarlett Johansson), Johnny (Taron Egerton), and more! What's your favorite song from the Sing movies?
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CREDITS:
TM & © Universal (2021)
Cast: Reese Witherspoon, Nick Kroll, Taron Egerton, Scarlett Johansson, Tori Kelly

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00:00-Top 5 Free Online Courses with Certification
01:37-Introduction to Data Science
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