Sign up:

This course is offered to MSc and PhD students.

PhD students please sign up for the course using the credit student application » at this link. The course code to enter is NFYK20002U.

For questions or problems with sign-up, please contact Aiga Voite. 

Skills

The student should in the course obtain the following skills:
•Understand the use of ML in data analysis
•Use ML on a given (suitable) dataset
•Be able to optimise the performance of the ML algorithm
•Be capable of quantifying and comparing ML performances

Knowledge

The student will obtain knowledge about ML concepts and procedures, more specifically:
•The fundamental methods used in ML.
•Various Cost-Functions and Goodness measures.
•The most commonly used ML algorithms.

Competences

This course will provide the students with an understanding of ML methods and knowledge of (structured) data analysis with ML, which enables them to analyse data using ML in science and beyond. The students should be capable of handling data sparcity, non-uniformities, and categorical data.