Tentalabbet

TDDE19 · 6 credits · Advanced level (A1F) · Datateknik, Datavetenskap

Advanced Project Course - AI and Machine Learning

Active · next start HT 2026

100%

passed the latest regular sitting

PRA1 · 22 Jan 2026 · 36 students

100%

passed the regular sittings, all sittings over the last 5 years

PRA1 · 168 students

This module only reports passing results, so the pass rate does not show how many did not pass.

Part of 4 programmes

Hand-in or lab

PRA1 Project

  • G

Main rounds

100% passed · 168 students

  • 100%36
  • 100%33
  • 100%18
  • 100%30
  • 100%51

Later rounds

100% passed · 18 students

  • 100%6
  • 100%7
  • 100%5
  • Pass a later round: 100% (18 students), compared with 100% (168 students) on the ordinary exam
Show small sittings (2)

Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.

  • 100%4
  • 100%4

About the course

Aim

The project should have significant technical level that requires in-depth subject knowledge in artificial intelligence and machine learning, should be carried out in a professional manner, and should develop and consolidate the participants' skills in the following areas:

  • Analyze and structure problems in the area of artificial intelligence and machine learning.
  • Apply knowledge and methods from a wide range of previous courses in the areas of artificial intelligence and machine learning.
  • Independently acquire new knowledge, as required by the project.
  • Integrate knowledge from many disciplines and apply them in the context of artificial intelligence and machine learning.
  • Formulate a requirement specification for the project based on a project directive and thereby assess the feasibility of the project in terms of technical solutions and available resources.
  • Present the project results for teh client as well as for other students, which can not be presumed to be specialists in the techniques used.
  • Actively contribute to a well functioning project group.
  • Demonstrate the ability to lead the project work with the support of a project model, and with limited access to supervisory resources.
  • Plan, implement and monitor a project in the area of artificial intelligence and machine learning.

The result of the project work should:

  • Attain high technical quality and be based on modern knowledge and practices in the relevant field of technology.
  • Be documented in relevant project documents and relevant technical documentation.
  • Be presented orally.
  • Meet the requirements stated in the specification.

Content

Description of the projects, with project directives, are available on the course website. The projects will be closely linked to either ongoing research within the field of computer science or to companies active in this field. Examples could be develop a robotic system to perform some specific type of tasks, develop a system that learns to detect and track objects from sensor data, develop a recommender system for a specific domain, develop a system that learns to predict the activity of an object based on prior observations. The nature of the projects may change from year to year.

Examiner
Mattias Tiger
Scheduled hours
64 h
Main field of study
Datateknik, Datavetenskap
Syllabus on Studieinfo ↗