Math 0-1: Calculus for Data Science & Machine Learning

Common scenario: You try to get into machine learning and data science, but there's SO MUCH MATH. Either you never studied this math, or you studied it so long ago you've forgotten it all. What do you do.

Well my friends, that is why I created this course. Calculus is one of the most important math prerequisites for machine learning. It's required to understand probability and statistics, which form the foundation of data science.

Backpropagation, the learning algorithm behind deep learning and neural networks, is really just calculus with a fancy name. If you want to do machine learning beyond just copying library code from blogs and tutorials, you must know calculus. Normally, calculus is split into 3 courses, which takes about 1.

5 years to complete. Luckily, I've refined these teachings into just the essentials, so that you can learn everything you need to know on the scale of hours instead of years. This course will cover Calculus 1 (limits, derivatives, and the most important derivative rules), Calculus 2 (integration), and Calculus 3 (vector calculus).