NWNR100067 Exercises in Python and machine learning
- Type
- course with continuous assessment
- Semester hours
- 3
- Lecturer (assistant)
- Petrov, Drazen , Sykacek, Peter , Schuh, Marc , Oostenbrink, Chris , Kaiblinger, Norbert , Allmesberger-Riegler, Lisa Marie
- Organisation
- Molecular Modeling and Simulation
- Offered in
- Wintersemester 2025/26
- Languages of instruction
- Englisch
- Content
-
After completing this course, students will be familiar with various tools in the fields of machine learning and artificial intelligence. They will be able to classify methods and understand application areas in image processing, protein structure prediction, and generative models. They will be familiar with core programming concepts and essential Python packages for data analysis and visualization. They will also have gained insights into the social and ethical aspects of using machine learning.
- Objective (expected results of study and acquired competences)
-
Students will be able to use the Python programming language for data processing (data preparation, statistical analysis, and data visualization). Students will be able to transform simple scientific questions into algorithms and program them in Python. They will be able to apply essential machine learning tools in the areas of image processing and structure prediction to biotechnological measurement data.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.