Advanced Topics in Machine Intelligence


Content, progress and pedagogy of the module

Learning objectives


gain knowledge of advanced topics dealing with methods and application of machine intelligence, e.g.:

  • advanced techniques in data mining
  • advanced methods for reasoning and decision making under uncertainty
  • agent-based design of intelligent systems
  • intelligent web-based systems


  • achieve skills to identify and use advanced techniques from machine intelligence for constructing intelligent systems


  • be able to understand advanced methods for the design of intelligent systems and to analyze their applicability and efficacy in solving specific tasks.

Type of instruction

The teaching is organized according to the general teaching methods for the education, cf. chapter 3

Extent and expected workload

It is expected that the student uses 30 hours per ECTS, which for this activity means 150 hours



Name of examAdvanced Topics in Machine Intelligence
Type of exam
Written or oral exam
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Additional information

Contact: The Study board for Computer Science at or 9940 8854

Facts about the module

Danish titleAvancerede emner inden for maskinintelligens
Module codeDSNDATFK203
Module typeCourse
Duration1 semester
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Study BoardStudy Board of Computer Science
DepartmentDepartment of Computer Science
FacultyTechnical Faculty of IT and Design