Artificial Intelligence


Content, progress and pedagogy of the module

The module is based on Linear algebra, calculus and probability theory, and knowledge about programming in one or more of the modern computer languages.

Learning objectives


  • Have knowledge about the fundamental concepts and theories in artificial intelligence (AI)
  • Have knowledge about the algorithmic search and optimisation techniques used in AI, such as depth-first, bread-first search and gradient decent or particle swarm optimisation
  • Have knowledge about how to model uncertainty in AI using probabilistic methods and/or fuzzy logic
  • Have knowledge about machine learning techniques, such as artificial neural networks, Bayesian networks, clustering, classification and its applications


  • Be able to design AI based models and algorithms for specific applications using digital platforms
  • Be able to develop computer programs to implement one or more of the techniques used in artificial intelligence
  • Be able to design AI based solutions and implement them in an embedded processor or computer


  • Independently be able to apply modelling techniques in AI using connectionist and/or probabilistic methods
  • Independently develop artificial intelligence based system solutions in specific problems using digital platforms
  • Have a fundamental understanding of the modern techniques used in AI, such as deep learning and its applications, for example in big data problems

Type of instruction

Lectures with exercises supplemented with e-learning activities.

Extent and expected workload

Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student



Name of examArtificial Intelligence
Type of exam
Written or oral exam
Permitted aids
With certain aids:
For more information about permitted aids, please visit the course description in Moodle.
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleKunstig intelligens
Module codeN-APEL-K3-3B
Module typeCourse
Duration1 semester
Language of instructionEnglish
Empty-place SchemeYes
Location of the lectureCampus Esbjerg
Responsible for the module


Education ownerMaster of Science (MSc) in Engineering (Advanced Power Electronics)
Study BoardStudy Board of Build, Energy, Electronics and Mechanics in Esbjerg
DepartmentDepartment of Energy
FacultyThe Faculty of Engineering and Science