Machine Learning and Introduction to AI

This course teaches the basics of machine learning, including theory and practical aspects, and an introduction to artificial intelligence (AI).

Exam and project. The exam (3h) takes place in week 1.10 and the final assignment is due in week 1.9. The project can be made in groups (pairs).

In order to pass, students must obtain a grade greater or equal to 5.0 for both the exam and final assignment, and at least a 5.8 for the final grade after rounding. There is a resit opportunity and also a possibility to repair for the final project. Resit is only necessary for parts with a failing grade (passing grades are kept for the resit). The resit grade replaces the original grade only if the resit grade is greater than the original grade.

Weighting for the final grade:

Project 30%

Exam 70%

Disclaimer: information may change depending on unforeseen circumstances or measures (see: TER Art 29, sub 4)