A national initiative on education and competence in Artificial Intelligence

Supervised Machine Learning

Computer Science

Data Science

Machine Learning

Applications of AI

Please be aware that this course is no longer available. Explore our current selection of AI courses suitable for professionals.

This course provides a broad introduction to Machine Learning (ML). Students will learn about standard supervised ML techniques for regression and classification as well as best practices in ML, and gain practice implementing ML algorithms in Python. The course “Supervised Machine Learning” is broken down into three modules of 2.5 credits each:

  • Introduction to regression and classification (8 x 45 min)
  • Overfitting and generalization (8 x 45 min)
  • Neural networks (10 x 45 min)

    • Each of the lectures delivered through Zoom is followed by practical lab assignments in Python, provided as a Jupyter notebook, which allows the participants to dig into the concepts presented in the lecture and put them to practice. Exams consist of the practical lab assignments, as well as a test that will be conducted online on Blackboard at the end of each module. The course instructors teach a similar course in our master’s programmes.

    This course is for professionals with an undergraduate degree in engineering (or similar). Prerequisites include knowledge in Python programming, as well as very basic linear algebra. This course is for people who have not had basic Machine Learning and AI in their undergraduate degree. The course is held online in English. Pace: 50%, flexible.