Preparatory Course: Mathematics and Computer Science for Modeling
The "Computer Science and Mathematics" preparatory course will combine a handson introduction to programming in python with a revision of elementary mathematical concepts. The topics include data types, data structures, control structures and data visualisation on the programming side and they will be applied to vector/matrix calculation, integration/differentiation of functions and differential equations.
The course is meant for students who are about to start the Cognitive Science Master Program at the RuhrUniversity .
Lecturers
Dr.Ing. Jan TekülveLecturer 
(+49) 2343227976 jan.tekuelve@ini.rub.de NB 02/75 
Details
 Course type
 Lab courses
 Term
 Summer Term 2021
Dates
 Lecture

Takes place
every day from 15:00 to 17:30 in room CIP Insel IA 0/15879.
First appointment is on 26.09.2021
Last appointment is on 08.10.2021
Documents
Lecture slides  Lecture 1  Introduction to Variables and Control Statements 
Video  Recording Lecture 1 
Exercises  Task Solutions 1 
Lecture slides  Lecture 2  Functions in Math and Programming 
Video  Recording Lecture 2 
Exercises  Task Solutions 2 
Lecture slides  Programming Session 1 
Exercises  Solutions Session 1 
Lecture slides  Lecture 3  Trigonometry 
Exercises  Template Task 3 
Exercises  Task Solutions 3 
Lecture slides  Lecture 4  Differentiation 
Exercises  Task Template 4 
Exercises  Task Solution 4 
Lecture slides  Lecture 5  Integration 
Exercises  Task Template 5 
Exercises  Task 5 Solutions 
Video  Recording Lecture 5 
Lecture slides  Lecture 6  Differential Equations 
Video  Lecture 6 Recording 
Exercises  Task 6 Template 
Exercises  Task 6 Solutions 
Document  Exam Topics 
Lecture slides  Programming Session 2 
The Institut für Neuroinformatik (INI) is a central research unit of the RuhrUniversität 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
D44801 Bochum, Germany
Tel: (+49) 234 3228967
Fax: (+49) 234 3214210