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.


After the course, the student knows how to carry out a scientific project and write a scientific report in the field of machine learning, data science and artificial intelligence.

Credits: 5 - 10

Schedule: 20.09.2023 - 31.05.2024

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Jorma Laaksonen

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:

    A project work, done either alone or in a group, from the field of machine learning, data science and artificial intelligence.  Students can either 1) report the research work carried out during their internships, 2) find a topic and supervisor by themselves, or 3) select a topic among available ones in a matchmaking process run in September.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Assesment based on the report and presentation.

  • valid for whole curriculum period:

    Independent or group work including discussions with a supervisor, programming, experimenting, reporting and presenting the results.


Substitutes for Courses
SDG: Sustainable Development Goals

    1 No Poverty

    2 Zero Hunger

    3 Good Health and Well-being

    4 Quality Education

    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 - Summer
    2023-2024 Autumn I - Summer

    Enrollment :

    The course is primarily available for major students in CCIS Machine Learning, Data Science and Artificial Intelligence (Macadamia) and exit year students in EIT Digital Master School's Data Science major. Other students need to contact the responsible teacher before enrolling.