731139 Scientific computing
- Type
- Lecture and exercise
- Semester hours
- 2
- Lecturer (assistant)
- Schmidt, Johannes , Regner, Peter
- Organisation
- Offered in
- Sommersemester 2024
- Languages of instruction
- Englisch
- Content
-
Scientific computing is a fundamental skill in all fields of quantitative modeling of the environment. More recently, machine learning has been increasingly applied in the field too. This class will introduce the students to Python, one of the most widely used languages in scientific computing today and state-of-the-art tool in machine learning. The class will introduce students to the basic concepts of programming in python, to basics of algorithms and data structures, and to the concept of neural networks, one of the most important machine learning algorithms applied today. We apply neural networks to pattern recognition, and regression analysis for problems in energy system analysis.
- Previous knowledge expected
-
In principle, everyone can take the class, but pre-knowledge in any programming language will facilitate the successful completion of the class.
- Objective (expected results of study and acquired competences)
-
After taking the class, students understand the concepts
-of programming in python
-opportunities and challenges of machine learning
-the basic functioning of neural networks.
Also, the students are able to
-apply Python to problems of scientific data analysis
-and use Keras to create, train, and apply neural networks
You can find more details like the schedule or information about exams on the course-page in BOKUonline.