Course syllabus

Tillämpad maskininlärning
Applied Machine Learning

EDAN95, 7,5 credits, A (Second Cycle)

Valid for: 2018/19
Decided by: PLED C/D
Date of Decision: 2018-04-03

General Information

Elective for: BME4, C4-pv, D4-bg, D4-pv, E4-bg, F4, F4-pv, Pi4, Pi4-pv
Language of instruction: The course will be given in English


To give an introduction to several subdomains of machine learning and to give an orientation about fundamental methods and algorithms within these domains. To convey knowledge about breadth and depth of the domain.

Learning outcomes

Knowledge and understanding
For a passing grade the student must


Competences and skills
For a passing grade the student must



Judgement and approach
For a passing grade the student must







Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Written examination and assignments. The final grade of the course is based on the result of the written examination.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Code: 0118. Name: Written Examination.
Credits: 3. Grading scale: TH. Assessment: Written examination.
Code: 0218. Name: Assignments.
Credits: 4,5. Grading scale: UG. Assessment: To pass the course all the compulsory assignments must be approved. Details regarding the compulsory assignments will be found in the course program (syllabus) on the course web site. Contents: Assignments where some of the machine learning algorithms presented during lectures are implemented in order to give practical experience of difficulties related to, e.g., computational complexity, scalability and result interpretation.


Admission requirements:

The number of participants is limited to: 60
Selection: Credits remaining for the degree.

Reading list

Contact and other information

Course coordinator: Jacek Malec,
Course coordinator: Pierre Nugues,
Course coordinator: Elin Anna Topp,
Course homepage:
Further information: Detailed rules concerning the assignments will be found in the course web site.