What you'll learn
Understand the basic and advanced topics of calculus and how to use them in AI, such as derivatives, integrals, optimization, and multivariate calculus.
Understand the basic and advanced topics of probability and statistics and how to use them in AI, such as probability rules, random variables, etc.
Linear regression and logistic regression and how to use them in AI, such as fitting, evaluating, and optimizing regression models for numerical or categorical
Neural networks and deep learning and how to use them in AI, such as constructing, training, and optimizing neural networks
Requirements
A basic understanding of mathematics through Calculus is highly advisable before taking this course.
Description
Do you want to learn the math behind artificial intelligence (AI) and how to apply it to real-world problems and applications? Do you want to master the concepts, the formulas, the methods, and the examples of the math behind AI in a clear and simple way? Do you want to have access to a powerful and friendly tool that can help you with anything related to the math behind AI? If you answered yes to any of these questions, then this course is for you!Welcome to the course 'Understanding the Math Behind AI'. This course is designed to teach you the essential math concepts that are used in AI, such as calculus, probability, statistics, linear regression, logistic regression, neural networks, and deep learning. This course is suitable for anyone who wants to learn the math behind AI, whether you are a beginner, an intermediate, or an advanced learner. This course is also ideal for anyone who wants to pursue a career or a hobby in AI, such as data scientists, machine learning engineers, AI researchers, or AI enthusiasts. In this course, you will learn:What is AI and why is math important for AI?What are the basic and advanced topics of calculus and how to use them in AI?What are the basic and advanced topics of probability and statistics and how to use them in AI?What are linear regression and logistic regression and how to use them in AI?What are neural networks and deep learning and how to use them in AI?What are the challenges and the solutions of optimizing a neural network and how to apply them in AI?What are the applications and the examples of neural networks and deep learning and how to use them in AI?So, what are you waiting for? Enroll in this course today and start learning the math behind AI. You will be amazed by what you can learn and do with the math behind AI. See you in the course!
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Algebra
Lecture 3 Linear Algebra
Lecture 4 Calculus
Lecture 5 Probability & Statistics
Lecture 6 Linear & Logistic Regression
Lecture 7 Lecture 7
This course is designed for anyone who would like to intricately understand the mathematics behind AI models.



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