SUBJECT

Mathematics

CNNM17-102

seminar

Master

Faculty of Education and Psychology

Cognitive Science MSc

Computational and Cognitive Neuroscience MSc

4

Semester 1

Autumn semester

Aim of the course:

The goal of this course is to gain a better understanding of those branches and fundamental concepts of mathematics that are needed most frequently in cognitive scienceIn addition to well-applicable mathematical ideas I also plan to include some fun ideas and proofs that connect to those with practical importance.

Learning outcome, competences knowledge:

• knows the introductory theories of mathematics

attitude:

• Interest for theoretical issues

skills:

• understanding literature that contains mathematical formulas and terminology
• using mathematical knowledge in building computer models (well, at least some, but the more the better).

Content of the course
Topics of the course

• combinatorics
• probability theory 
• linear algebra 
• the basics of analysis, and differential equations, accompanied by examples of psychological and biological applications.

Learning activities, learning methods:

• Lectures and interactive discussions
• For numerical solutions when we need them, we will use Matlab or R-Studio.

Evaluation of outcomes
Learning requirements, mode of evaluation, criteria of evaluation:
requirements

• Reliable basic knowledge in the domain of mathematics mode of evaluation: examination and practical course mark

criteria of evaluation:

• Knowledge on basic concepts and the skill of utilizing the modells of the big mathematics topics

Crilly, T. (2007). 50 mathematical ideas you really need to know. London: Quercus.
Strang, G. (2009). Introduction to linear algebra. Wellesley, MA: Wellesley Cambridge Press
Holzner, S. (2008). Differential equations for dummies. New York: Wiley.