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.


Intended as follow-up for CS-EJ3211 Machine Learning with Python.

Credits: 2

Schedule: 24.10.2022 - 11.12.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Alex Jung, Shamsiiat Abdurakhmanova

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:

    In this course, you will learn how to use state-of-the-art deep learning methods with the programming language Python.
    We will discuss key concepts of deep learning, such as artificial neural networks, data augmentation and transfer learning in a hands-on fashion. The grading is based on coding assignments and student projects.


Substitutes for Courses


Further Information
  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Autumn I-II

    2021-2022 Autumn I-II

    Course Homepage:

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu ( instead of WebOodi.