Courses offered in Machine Learning available for students of other fields of study

In the 2021 and 2022 academic years, students from other fields of study were not permitted to register for some of the courses designed for Machine Learning students ( with the code 1000-3xxx). Instead, open to all versions were available with a separate code:

• Deep neural networks with a Course ID: 1000-2M16GSN (ML equivalent: 1000-317bDNN)
• Robot Control with a Course ID: 1000-2M22RC (ML equivalent: 1000-317bRC)
• Ideas and informatics with a Course ID: 1000-217bIII (ML equivalent: 1000-317bIII)
• Statistical data analysis with a Course ID: 1000-714SAD (ML equivalent: 1000-317bSML)
• Explainable Machine Learning with a Course ID: 1000-1M18WUM (ML equivalent: 1000-319bEML)
• and the equivalent of the elective course for ML: Convex optimisation with the code: 1000-2M22OW.

From the academic year 2023, the Deep neural networks course will be available to students of other fields of study from the first round of registration. Other obligatory courses for Machine Learning, with the exceptions described below, will be available to students from other fields of study during the Direct registration for groups (BRDG round), depending on vacancies.

For non-ML students, however, the following courses will not be available:

• Bootcamp MAT (Bootcamp – introduction to mathematics) and Bootcamp ML (Bootcamp – introduction to machine learning)
• Ideas and Informatics (a Polish version of the course: Ideas and Informatics is available for non-ML students)
• Statistical Machine learning (available equivalents are: SAD for bioinformatics and mathematics students, and WUM for computer science students)
• Team programming project in machine learning ( requiring prior completion of all obligatory courses for the first year of ML)

Elective courses dedicated to ML: 1000-2M22OW and 1000-2M21IUM will be available to students from other fields of study during the Direct registration for groups (BRDG round), depending on vacancies.