Mathematics for AI & ML Developers : The Complete Course
Mathematics for AI & ML Developers : The Complete Course, available at $49.99, has an average rating of 4.45, with 43 lectures, 6 quizzes, based on 16 reviews, and has 321 subscribers.
You will learn about Learn the fundamental Mathematics required for machine learning development Learn core concepts of probability theory Learn all about calculus and its application in AI & ML Learn lineal algebra and neural networks This course is ideal for individuals who are Anyone who wants to learn the important mathematical concepts required for AI & ML will find this course very useful It is particularly useful for Anyone who wants to learn the important mathematical concepts required for AI & ML will find this course very useful.
Enroll now: Mathematics for AI & ML Developers : The Complete Course
Summary
Title: Mathematics for AI & ML Developers : The Complete Course
Price: $49.99
Average Rating: 4.45
Number of Lectures: 43
Number of Quizzes: 6
Number of Published Lectures: 43
Number of Published Quizzes: 6
Number of Curriculum Items: 49
Number of Published Curriculum Objects: 49
Original Price: $29.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn the fundamental Mathematics required for machine learning development
- Learn core concepts of probability theory
- Learn all about calculus and its application in AI & ML
- Learn lineal algebra and neural networks
Who Should Attend
- Anyone who wants to learn the important mathematical concepts required for AI & ML will find this course very useful
Target Audiences
- Anyone who wants to learn the important mathematical concepts required for AI & ML will find this course very useful
Mathematics for AI
If you want to develop AI solutions, you need to know the key formulas and computational theories and the mathematical algorithms used to analyze the data and statistics.
So, Want To Know How Maths Plays A Key Role In Developing AI Solutions?
This program is designed for the one who wants to become a complete AI specialist by gaining mastery over mathematical algorithms of AI. This course will help you learn the most important theories of probability, algebra, and calculus for data science and artificial intelligence.
This course will help you learn how probability stimulates probabilistic models using python. You’ll learn about probability mathematical frameworks which allow analyzing the chances of events in a logical manner. Also, this course gives you in-depth knowledge on how to deal with uncertainty in AI. This course provides you with knowledge of calculus that helps you understand the hidden pieces in the AI patterns.
Basically, you are going to get every single knowledge regarding mathematics in AI through this program.
Major Concepts That You’ll Learn
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Introduction to Mathematics for AI
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Probability theory
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Introduction to Calculus and Derivatives
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Calculus Continued and Integrals
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Introduction to Linear Algebra
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Linear Algebra Continued
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Neural Networks from Scratch
This course also covers essential topics like linear algebra and neural networks which help you develop reliable AI models.
Perks Of Availing This Program!
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Get Well-Structured Content
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Learn From Industry Experts
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Includes The Must-Learn AI Mathematical Concepts
So why are you waiting? make your move to become an AI specialist now.
See You In The Class!
Course Curriculum
Chapter 1: Introduction to Mathematics for AI
Lecture 1: Course Introduction
Chapter 2: Probability theory
Lecture 1: Section Overview
Lecture 2: Introduction to Probabilty theory
Lecture 3: Combinatorics
Lecture 4: Multiple events
Lecture 5: Section Summary
Chapter 3: Introduction to Calculus and Derivatives
Lecture 1: Section Overview
Lecture 2: The Essence of Calculus, Integrals and Derivatives
Lecture 3: Limits
Lecture 4: Derivative Formulas and Geometric Intuition
Lecture 5: Derivation Rules: Power Rule, Product Rule and Chain Rule
Lecture 6: Euler's Number and Continuous Growth
Lecture 7: Implicit differentiation
Lecture 8: Section Summary
Chapter 4: Calculus Continued and Integrals
Lecture 1: Section Overview
Lecture 2: Integral Intuition
Lecture 3: Integral Intuition Continued
Lecture 4: Indefinite Integrals
Lecture 5: Definite Integrals
Lecture 6: Integration in Python
Lecture 7: Calculus in Machine Learning
Lecture 8: Section Summary
Chapter 5: Introduction to Linear Algebra
Lecture 1: Section Overview
Lecture 2: Linear Algebra Intuition
Lecture 3: Linear Transformations
Lecture 4: Introduction to Matrices
Lecture 5: Matrices Continued
Lecture 6: Dot Product
Lecture 7: Matrix Patterns
Lecture 8: Section Summary
Chapter 6: Linear Algebra Continued
Lecture 1: Section Overview
Lecture 2: Determinant
Lecture 3: Cross Products
Lecture 4: Vector Calculus
Lecture 5: Change of Basis
Lecture 6: EigenVectors and EigenValues
Lecture 7: EigenVectors and EigenValues continued
Lecture 8: Section Summary
Chapter 7: Neural Networks from Scratch
Lecture 1: Section Overview
Lecture 2: Neural Networks
Lecture 3: Creating Model Classes
Lecture 4: Model Training
Lecture 5: Summary
Instructors
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Eduonix Learning Solutions
1+ Million Students Worldwide | 200+ Courses
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 0 votes
- 3 stars: 3 votes
- 4 stars: 5 votes
- 5 stars: 6 votes
Frequently Asked Questions
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