Mathematics for Modeling and Data Analysis

Due to the corona crisis this course will be offered as an online course in SS 2020.

I offer a pre-meeting 17.4. 14:00 to get used to the virtual room I am going to use and discuss the format.

Mor information is available at the moodle course where RUB students should be able to log in without password.

This course covers mathematical methods that are relevant for modeling and data analysis. Particular emphasis will be put on an intuitive understanding as is required for a creative command of mathematics. The following topics will be covered:

  • Functions and how to visualize them
  • Vector spaces
  • Matrices as transformations
  • Systems of linear differential equations
  • Qualitative analysis of nonlinear differential equations

possibly also (though not in SS 2020)

  • Bayesian theory
  • Multiple integrals

Lecturers

Details

Course type
Lectures
Credits
6 CP
Term
Summer Term 2020
E-Learning
moodle course available

Dates

Lecture
Takes place every week on Thursday from 12:15 to 13:45 in room virtual.
First appointment is on 23.04.2020
Last appointment is on 16.07.2020
Exercise
Takes place every week on Thursday from 10:30 to 12:00 in room vitual.
First appointment is on 30.04.2020
Last appointment is on 16.07.2020

Requirements

Basic knowledge of calculus and linear algebra.

Documents

Link Moodle course page: https://moodle.ruhr-uni-bochum.de/m/course/view.php?id=26614

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through 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 approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

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

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