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Postgraduate course

Research Topics in Artificial Intelligence

Level of Study

Master level

Teaching semester


Objectives and Content

The students should obtain advanced theoretical knowledge and technical skills on the topics covered in the course. The course will enable students to carry out advanced research projects on topics within artificial intelligence and apply the knowledge to complex intelligent system design and development.

The course covers advanced theoretical and technical issues in artificial intelligence. It will focus on some selected topics and applications, such as artificial life, agent and multi-agent systems, machine learning, neural networks, genetic algorithms and programming, data mining, natural language processing, case-based reasoning, cognitive science, and neuro-computing.

Learning Outcomes

A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:


  • The student understands advanced theoretical and technical issues in artificial intelligence.


The student

  • can apply knowledge for complex intelligent system design and development.
  • can carry out advanced research on artificial intelligence.

Recommended Previous Knowledge

Solid background in Informatics/Information Science/Computer Science

Access to the Course

Master's programme in Information Science. Other students may apply for admission.

Teaching and learning methods


Compulsory Assignments and Attendance

Mandatory participation: Attendance at 80 % of course sessions is mandatory.

Compulsory requirements are only valid the semester they are approved.

Forms of Assessment

  • Oral individual exam (40%)
  • Group based assignment(s) (60%)

Grading Scale

The grading system has a descending scale from A to E for passes and F for fail.

Assessment Semester

Assessment in teaching semester

Course Evaluation

INFO381 is evaluated by students every three years, by the Department every year.


Contact Information


Exam information

  • Type of assessment: Semester thesis and one oral exam

    Withdrawal deadline
    • Exam part: Semester thesis

      Submission deadline
      02.06.2020, 14:00
      Examination system
      Digital exam
    • Exam part: Oral exam

      Exam period