Mathematics for Modeling and Data Analysis

Lecturers

Details

Course type
Lectures
Credits
5 CP
Term
Summer Term 2025
E-Learning
moodle course available

Dates

Exercise
Takes place every week on Thursday from 9:00 to 10:30 in room NB 3/57 (self-study time without teacher).
First appointment is on 17.04.2025
Last appointment is on 17.07.2025
Tutorial
Takes place every week on Thursday from 10:30 to 12:00 in room NB 3/57.
First appointment is on 17.04.2025
Last appointment is on 17.07.2025
Lecture
Takes place every week on Thursday from 12:15 to 13:45 in room NB 3/57.
First appointment is on 10.04.2025
Last appointment is on 17.07.2025

Lecturer: Laurenz Wiskott.

Enrollment: Students simply enroll in the Moodle course and participate. You might also have to enroll for this course in your examination office, but this is something you'll have to figure out yourself.

From our examination office I have the following information: "Students of RUB’s Mathematics and Physics faculties will register via FlexNow (with only a selection of exams available, as per our website). These students will appear on the regular participant lists that you generate in FlexNow prior to your exams."

Credits: 5 CP

Workload: 150 h

Semester: any

Cycle (Turnus): each SS

Duration (Dauer): 1 semester

Contact time (Kontaktzeit): 4 SWS (60 h)

Self studies (Selbststudium): 90 h

Group size (Gruppengröße): ca 30

Language: English

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 some 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

See also the corresponding learnscape (click here to get to a clickable version):

Mathematics Learnscape

Teaching format (Lehrformen): One unit consists of a lecture of 90 min, self-study time over the week, group work on exercises without teacher for 90 min the week after the lecture, discussion of exercises and general Q&A session with teacher for 90 min right after, followed by the lecture of the next unit.

Exam (Prüfungsformen): The course is concluded with an oral exam (possibly also a digital written exam, if there are many participants, as will be decided within the first two weeks).

Condition for granting the credit points (Voraussetzungen für die Vergabe von Kreditpunkten): Passing the exam.

About the INI

The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.

Contact

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210

sekretariat@ini.rub.de
www.ini.rub.de