Advanced Topics in Machine Intelligence

2018/2019

Content, progress and pedagogy of the module

Learning objectives

Knowledge

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

Skills

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

Competences

  • 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

Exam

Exams

Name of examAdvanced Topics in Machine Intelligence
Type of exam
Written or oral exam
ECTS5
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentAre stated in the Joint Programme Regulations

Additional information

Contact: The Study board for Computer Science at cs-sn@cs.aau.dk or 9940 8854

Facts about the module

Danish titleAvancerede emner inden for maskinintelligens
Module codeDSNDATFK203
Module typeCourse
Duration1 semester
SemesterSpring
ECTS5
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module

Organisation

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