Mathematics for Modeling and Data Analysis

Content:

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:

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.

Learning outcomes: 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.

Exam:

The course is concluded with a digital written exam for 90 minutes within a 120 minutes time slot. We offer two dates in the semester of the course and none in the next semester. You are free to pick either of the two dates, but if you pick the second and you fail, the next opportunity to retry the exam is only about one year later. This is an open book exam, thus you may use any tools (e.g. lecture notes or Wikipedia) except communication with other people. Registration for the exam with us happens at the end of the course, you will receive instructions on that in due time. You might also have to register for this exam in your examination office, but this is something you'll have to figure out yourself. Registering with us and with the examination office are independent of each other, and if possible we will report your grade to the examination office in any case, whether you have registered there or not. There are no prequisits for the exam, like 50% points in tutorials or the like.

Lecturers

Details

Course type
Lectures
Credits
5 CP
Term
Summer Term 2024

Dates

Lecture
Takes place every week on Thursday from 10:30 to 12:00 in room NB 3/57.
First appointment is on 11.04.2024
Last appointment is on 18.07.2024
Exercise
Takes place every week on Thursday from 12:15 to 13:45 in room NB 3/57.
First appointment is on 11.04.2024
Last appointment is on 18.07.2024

Requirements

Basic knowledge of calculus and linear algebra.


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