Topic outline

  • Lecturer: Antti Punkka
    Course assistant: Pekka Laitila


    Why this course?

    The future impacts of a decision made today are often uncertain. These impacts may need to be evaluated with regard to multiple objectives, the relative importance of which may be viewed differently by different people involved in the decision process.

    This course introduces ways to support such complex decision-making processes through formal decision models. After the course, the student can 
    • recognize real-life decision problems where the use of decision models brings added value,
    • build decision models to support solving such problems,
    • solve such models with the help of software tools, and
    • interpret the results of decision these models to generate defensible decision recommendations.

    The student will also become aware of
    • the possible discrepancy between formal models and human behavior and
    • ways to mitigate the adverse effects of this discrepancy.


    Practical matters

    Teaching: Lectures (24h) and exercise sessions (24h)

    Assessment methods: Home assignments and exam; grading principles:

    • Maximum points 39 – you have to get at least 17 to pass the course

    1. Three home assignments (max points 3 + 5 + 5 = 13)
    2. Exam (max points 24) – at least 10 exam points needed to pass the course
    3. Participation to the guest lecture: 1 point
    4. Succesful submission of course feedback: 1 point

    Grading scale: 0-5

    Study material: Lecture slides and exercises

    Language of instruction: English

    Prerequisites: MS-A0501 Todennäköisyyslaskennan ja tilastotieteen peruskurssi (or equivalent), MS-C2105 Optimoinnin perusteet (or equivalent)