Courses Taught by Mark Schmidt

I've also assembled the material from all the completed courses below into one resource called 100 Lectures on Machine Learning.


This year, a substantial amount of 440/540 material was re-made to make it more undergrad and modern-ML friendly.


This year, we added a listing of CPSC 540 under the name CPSC 440 to make it easier for undergrads to enroll in the course.


This year, we made the probability prerequisites for 340 more strict, allowing us to cover some topics in more detail. In 540, the first part of the course (covering machine learning optimization algorithms) was be removed from the class. This made 540 act more as a sequel to 340, and reduced the gap in difficulty between the two courses. I later covered machine learning optimization algorithms in an official summer course, CPSC 5XX.


Since many students are taking 340 for graduate credit, this year graduate students in 340 will enroll under a different course number (532M) and require an extra project component.



This year, a multivariate calculus prerequisite was added to 340. For 340, this means that some topics were covered in more detail while some new topics were be covered that were previously only covered in 540. For 540, this means we skipped some topics that were previously covered and there was some new more-advanced material added.


This year, a lot of redundancy between 340 and 540 was removed so that together they can form a full-year course with a broader coverage of the field. CPSC 340 has a greater focus on data mining and applications, while CPSC 540 has a greater focus on theory and advanced methods.


A graduate-level introductory course in machine learning, mostly focusing on the typical topics you would see in a machine learning course.

Mark Schmidt > Courses