TDDE69 · 6 credits · Basic level (G2F) · Informationsteknologi, Datateknik, Datavetenskap
Machine Learning, Basic Course
Active · next start HT 2026
100%
passed the latest regular sitting
UPG1 · 13 Jan 2026 · 21 students
100%
passed the regular sittings, all sittings over the last 5 years
UPG1 · 43 students
This module only reports passing results, so the pass rate does not show how many did not pass.
Part of 1 programme
Hand-in or lab
UPG1 Laboratory and project assigments
- G
Main rounds
100% passed · 43 students
- 100%21
- 100%22
Later rounds
No sittings with at least 5 students.
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Other module
DAT1 Computer exam
- 5
- 4
- 3
- U
Main rounds
87% passed · 31 students
- 100%13
- 78%18
Later rounds
No sittings with at least 5 students.
- Get 4 or 5: 48% (31 students)
Show small sittings (3)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 0%1
- 100%2
- 100%4
About the course
Aim
The overall aim of the course is to provide an introduction to machine learning, with a focus on supervised learning. After completion of the course, the student should be able to:
- Use basic concepts and methods in machine learning to formulate, structure and solve practical problems.
- Construct linear and nonlinear models for classification and regression and fit these to training data.
- Evaluate a model's performance and account for model selection and model adjustment.
- Implement basic machine learning models and methods in a programming language.
Content
This is a basic course in machine learning with a focus on classification and regression: linear regression, regularization, classification via logistic regression, linear discriminant analysis, classification and regression trees, boosting, neural networks, deep learning; practical aspects such as cross-validation, model selection, trade-off between bias and variance, application of the methods to real data.
- Examiner
- Sebastian Mair
- Scheduled hours
- 0 h
- Main field of study
- Informationsteknologi, Datateknik, Datavetenskap