Key models in machine learning and their associated learning and inference techniques, such as:
The use of machine learning methods in selected fields of application, such as:
The type of instruction is organised in accordance with the general instruction methods of the programme, cf. § 17.
It is expected that the student uses 30 hours per ECTS, which for this activity means 150 hours
Name of exam | Machine Learning |
Type of exam | Written or oral exam |
ECTS | 5 |
Assessment | 7-point grading scale |
Type of grading | Internal examination |
Criteria of assessment | The criteria of assessment are stated in the Examination Policies and Procedures |
Contact: The Study board for Computer Science at cs-sn@cs.aau.dk or 9940 8854
Danish title | Maskinlæring |
Module code | DSNDATFK213 |
Module type | Course |
Duration | 1 semester |
Semester | Spring
|
ECTS | 5 |
Language of instruction | Danish and English |
Empty-place Scheme | Yes |
Location of the lecture | Campus Aalborg |
Responsible for the module |
Study Board | Study Board of Computer Science |
Department | Department of Computer Science |
Faculty | Technical Faculty of IT and Design |