Preparatory Course: Mathematics and Computer Science for Modeling
The "Computer Science and Mathematics" preparatory course will combine a hands-on 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 Ruhr-University .
Lecturers
Dr.-Ing. Jan TekülveLecturer |
(+49) 234-32-27976 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 0/158-79.
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 interdisciplinary research unit of the Ruhr-Universität Bochum. We aim to understand fundamental principles that characterize how organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by insights into 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, theoretical approaches from physics, mathematics, and computer science, including, in particular, machine learning, artificial intelligence, autonomous robotics, and computer vision.
Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany
Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210