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.


Students can formalize applications as ML problems and solve them using basic ML methods.

Students can perform basic exploratory data analysis.

Students understand the meaning of the train-validate-test approach in machine learning.

Students can apply standard regression and classification models on a given data set.

Students can apply simple clustering and dimensionality reduction techniques on a given data set.

Students are familiar with and can explain the basic concepts of reinforcement learning.

Credits: 5

Schedule: 05.09.2022 - 14.10.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Pekka Marttinen, Stephan Sigg

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


  • valid for whole curriculum period:

    Exploratory data analysis.

    Dimensionality reduction, PCA.

    Regression and classification.


    Deep learning.

    Reinforcement learning.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Assignments, project report, participation in peer-grading.

  • valid for whole curriculum period:

    5 credits approx. 134 hours of work divided into 

    Lectures + self-study: 10*(2+3)=50 hours

    Assignments: 6 * 9 = 54 hours

    Project work: 26 hours

    Peer-grading: 4 hours


Substitutes for Courses
SDG: Sustainable Development Goals

    1 No Poverty

    2 Zero Hunger

    3 Good Health and Well-being

    5 Gender Equality

    6 Clean Water and Sanitation

    7 Affordable and Clean Energy

    8 Decent Work and Economic Growth

    9 Industry, Innovation and Infrastructure

    10 Reduced Inequality

    11 Sustainable Cities and Communities

    12 Responsible Production and Consumption

    13 Climate Action

    14 Life Below Water

    15 Life on Land

    16 Peace and Justice Strong Institutions

    17 Partnerships for the Goals


Further Information
  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Autumn I
    2023-2024 Autumn I