Official course description, subject to change:
Preliminary info last published 24/05-22

Advanced Machine Learning

Course info
Language:
English
ECTS points:
15.0
Course code:
KSADMAL1KU
Participants max:
50
Offered to guest students:
yes
Offered to exchange students:
yes
Offered as a single subject:
yes
Price for EU/EEA citizens (Single Subject):
21250 DKK
Programme
Level:
MSc. Master
Programme:
MSc in Computer Science
Staff
Course semester
Semester
Efterår 2023
Start
28 August 2023
End
29 December 2023
Exam
Exam type
ordinær
Internal/External
ekstern censur
Grade Scale
7-trinsskala
Exam Language
GB
Abstract

This course introduces Machine Learning methods and how they are used in active research. Methods will be described in a way to enable you to select the suitable tool for given application, and adapt accordingly.

Description
We build upon knowledge from the course "Linear Algebra and Probability", and assume that you have prior knowledge in programming. It is highly recommended to have taken the course "Introduction to Machine Learning".  
The course enables students to understand and implement advanced machine learning algorithms, and modify the learnt methods to analyze the outcome of various applications on different datasets. This includes the ability to select appropriate tools and reflect on the results.  
The first 10 weeks of the course consist of lectures and exercises twice a week, the remaining 4 weeks are reserved for the mandatory group project, which will be part of the oral exam.

Formal prerequisites

Linear Algebra and Probability

Intended learning outcomes

After the course, the student should be able to:

  • Define and describe basic machine learning terms and methods.
  • Develop and implement machine learning methods on your own in an appropriate programming language.
  • Characterize, relate, and analyze central machine learning concepts and algorithms.
  • Combine and modify machine learning methods to analyze practical datasets and reflect on the results.
Ordinary exam
Exam type:
D: Submission of written work with following oral, External (7-point scale)
Exam variation:
D2G: Submission for groups with following oral exam supplemented by the submission. Shared responsibility for the report.