Best Mathematics Courses for Machine Learning

Best Mathematics Courses for Machine Learning

Best Mathematics Courses for Machine Learning

Knowledge of Mathematics is very important in order to understand how Machine Learning works. In mathematics, the most important topics regarding Machine Learning are:

  • Linear Algebra

  • Calculus

  • Matrix Algebra

  • Probability and Statistics

In order to understand the concepts of Machine Learning algorithms, concrete mathematical knowledge is necessary. That's why anyone who wants to start their Machine Learning or Data Science journey should first gain full control on mathematical topics listed above. Below is a non-exhaustive list of some of the best online mathematics courses currently available for Machine Learning.

1. Mathematics for Machine Learning Specialization

Rating- 4.4/5

Provider- Imperial College London

Time to Complete- 4 Months (4 hours/week)

This is one of the best specialization programs that covers all mathematical topics required for basic understanding Machine Learning. The aim of this specialization program is to fill the gap and build an intuitive understanding of mathematics.


2. Mathematics for Data Science Specialization

Rating- 4.4/5

Provider- National Research University Higher School of Economics

Time to Complete- 6 months (4 hours/week)

This is another mathematics specialization program, that covers all required math topics for Machine Learning and Data Science. In this specialization, you will learn Discrete Mathematics, Calculus, Linear Algebra, and Probability. This specialization covers a wide range of mathematical tools.


3. Data Science Math Skills

Rating- 4.5/5

Provider- Duke University

Time to Complete- 13 hours

This course is offered by Duke University. In this course, you will master the vocabulary, notation, concepts, and algebra rules required for Data Science and Machine Learning.


4. Introduction to Calculus

Rating- 4.8/5

Provider%u2013 The University of Sydney

Time to Complete- 51 Hours

This full course is dedicated to Calculus. In this course, you will get a complete understanding of Calculus. This course will teach you key ideas and historical motivation for calculus, while at the same time striking a balance between theory and application.


5. Probabilistic Graphical Models Specialization

Rating- 4.6/5

Provider- Stanford University

Time to Complete- 4 Months ( 11 hours/week)

This Specialization will master you in fundamentals of probabilistic graphical models. Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains.


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