Mathematics for Machine Learning: Multivariate Calculus
Imperial College London · View on Coursera ↗
Taught by Samuel J. Cooper, David Dye, A. Freddie Page
Data ScienceMath and LogicComputer Science
About the course
This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster. Next, we learn how to calculate vectors that point up hill on multidimensional surfaces and even put this into action
The dissent
The most-upvoted critical review (23 votes, 2.0★).
“The assessment at the end of a week was not really challenging and does not require a deep understanding of the concepts. Some of the quizzes were more challenging but in the assessments it was often only required to answer questions based on graphs or other images of functions. Most of the programming assignments only required the student to fill in some easier blanks.”
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Reviews read on 23 Oct 2026.Read them on Coursera ↗