Mathematics of Machine Learning 2026

This will be the main website for the Mathematics of Machine Learning course in the spring of 2026, as part of the bachelor of mathematics at the University of Amsterdam.

See last year’s course website for an impression of the course contents.

Instructor:	Tim van Erven	(tim@ No spam, please timvanerven. No really, no spam nl)
Teaching Assistants:

General Information

Machine learning is one of the fastest growing areas of science, with far-reaching applications. This course gives an overview of the main techniques and algorithms. The lectures introduce the definitions and main characteristics of machine learning algorithms from a coherent mathematical perspective. In the workgroups, students will both solve mathematical exercises to deepen their understanding, and apply algorithms from the course to a selection of data sets using Python Jupyter notebooks.

We will use Canvas for announcements, grades and submitting homework.

Prior Knowledge

• Probability theory
• Linear algebra, gradients, convexity
• Ability to write mathematical proofs
• Programming in Python with Jupyter notebooks
• Writing in LaTeX

Although mainly targeting mathematics students, the course is accessible to other science students (AI, CS, physics, …) with an interest in mathematical foundations of machine learning.