Enrolment options

Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

  1. Understand how several important problems arising from diverse fields can be cast and solved as optimisation problems;
  2. Know the main techniques for solving large scale numerical optimisation problems and how to apply them in practice;
  3. Know how to use optimisation software for implementing and solving optimisation problems.

Credits: 5

Schedule: 24.02.2025 - 07.04.2025

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Harri Hakula

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    Concepts familiar from Calculus courses are connected with modern linear algebra. First convexity and methods applying computable second derivatives are discussed. The effect of linear constraint on the structure of the related linear systems of equations is covered in detail. The idea of minimisation via gradient descent including the practical randomised very large scale variants is introduced.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Homework and exam.

Workload
  • valid for whole curriculum period:

    Contact hours: 48h (12 x 2h lectures and 12 x 2h exercises). Attendance is not compulsory.

    Self study: 83h (5 home exercises - 4h each; remainder for revising content of lectures and exercise sessions and for preparing for the exam)

DETAILS

Study Material
  • valid for whole curriculum period:

    Main material: Lecture notes and slides.

    Supplementary bibliography: Gilbert Strang, Linear Algebra and Learning from Data, Wellesley -- Cambridge Press

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    4 Quality Education

    5 Gender Equality

    7 Affordable and Clean Energy

    8 Decent Work and Economic Growth

    9 Industry, Innovation and Infrastructure

    11 Sustainable Cities and Communities

    12 Responsible Production and Consumption

    13 Climate Action

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching Language: English

    Teaching Period: 2024-2025 Spring IV
    2025-2026 Spring IV

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