Computer Science and Mathematics Preparatory Course
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
Jan Tekülve, M.Sc.Lecturer 
(+49) 2343224201 jan.tekuelve@ini.rub.de NB 02/73 
Details
 Course type
 Lab courses
 Term
 Summer Term 2019
Dates
 Lab course

Takes place
every day on Monday, Tuesday, Wednesday, Thursday and Friday from 15:30 to 18:00 in room IA 0/69.
First appointment is on 19.09.2019
Last appointment is on 02.10.2019
Documents
Lecture slides  Introduction to Variables and Control Statements 
Exercises  Task Solutions Lecture 1 
Lecture slides  Functions in Math and Programming 
Exercises  Task Solutions Lecture 2 
Lecture slides  Programming Session 
Exercises  Solutions Programming Session 
Lecture slides  Coordinate Systems and Trigonometry 
Exercises  Task 3.1 Template 
Exercises  Task Solutions Lecture 3 
Lecture slides  Function Limits and Differentiation 
Exercises  Task 4.1 Template 
Exercises  Braitenberg.png 
Exercises  Task Solutions Lecture 4 
Lecture slides  Lecture 5 Integration 
Exercises  Task Templates 5 
Exercises  Lecture 5 Task Solutions 
Lecture slides  Differential Equations 
Exercises  Task 6 Template 
Exercises  Lecture 6 Task Solutions 
Document  Exam Topics 
Lecture slides  Programming Session 2 
Exercises  Hangman Template 
Lecture slides  Object Oriented Programming 
Exercises  Uni Manager Module 
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