Enrollment: To enroll in this course with me, you just have to enroll in the Moodle course and participate. You also might have to enroll with your examination office, but that is something you have to figure out yourself.
Credits: 5 CP
Workload: 150 h
Semester: any semester Bachelor
Cycle (Turnus): each SS
Duration (Dauer): 1 semester
Contact time (Kontaktzeit): 4 SWS (60 h)
Self studies (Selbststudium): 90 h
Group size (Gruppengröße): ca 20
Requirements: Basic knowledge of calculus and linear algebra.
Learning outcomes (Lernziele): After the successful completion of this course the students
- know the material covered in this course, see Content,
- do have an intuitive understanding of the basic concepts and can work with that,
- can communicate about all this in English.
Content (Inhalt): This course covers mathematical methods that are relevant for modeling and data analysis. Particular emphasis is put on an intuitive understanding as is required for a creative command of mathematics. The following topics are covered:
- Functions and how to visualize them
- Vector spaces
- Matrices as transformations
- Systems of linear differential equations
- Qualitative analysis of nonlinear differential equations
- Bayesian theory
- Markov chains
Teaching format (Lehrformen): This course is given with the flipped/inverted classroom concept. First, the students work through online material by themselves. In the lecture time slot we then discuss the material, find connections to other topics, ask questions and try to answer them. In the tutorial time slot the newly acquired knowledge is applied to analytical exercises and thereby deepened. I encourage all students to work in teams during self-study time as well as in the tutorial.
Exam (Prüfungsformen): The course is concluded with a digital written exam.
Condition for granting the credit points (Voraussetzungen für die Vergabe von Kreditpunkten): Passed written exam.