![]() Statistics with Python Specialization Level: Beginner Prerequisites: High school math Take the “Mathematics for Machine Learning Specialization” on Coursera. ![]() If your linear algebra is a bit rusty, I recommend taking the entire specialization which should take you about 12-15 weeks. Taking this course on its own will require around 3-6 weeks of about 1 hour of work a day and a solid understanding of linear algebra. The course consists of short video lectures, quizzes, and hands-on programming assignments. The main focus is on vector calculus and applications in machine learning such as regression and mathematical optimization. “Calculus” is the second course in the “mathematics for machine learning specialization” on Coursera. ![]() CalculusĬalculus for Machine Learning on Coursera Level: Beginner-Intermediate Prerequisites: High school math + basic understanding of linear algebra & matrices If you go at a comfortable pace and put in less than an hour a day, you’ll probably be able to finish this course in 3-5 weeks and the entire specialization in 12-15 weeks. It consists of several short video lectures, quizzes, and hands-on programming assignments. This is hands down one of the best courses I’ve come across for quickly getting up to speed with linear algebra. “Linear Algebra” is the first in a series of 3 courses that form the “mathematics for machine learning specialization” offered by Imperial College London on Coursera. ![]() Linear Algebra for Machine Learning on Coursera Level: Beginner Prerequisites: High school math ![]()
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