## 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

## Daniel Sabinasz, M.Sc.Lecturer |
(+49) 234-32-27973 daniel.sabinasz@ini.rub.de NB 02/74 |

## Details

- Course type
- Lab courses
- Term
- Winter Term 2023/2024

## Teaching Units

##### Unit 1: Introduction to Programming in Python

Document | Jupyter notebook |

Link | Python documentation |

Link | Bonus exercises with varying difficulties |

Document | Jupyter notebook with all exercise solutions |

Lecture slides | Lecture slides |

##### Programming Session

Lecture slides | Slides |

Reference solution | Solution task 1 |

Reference solution | Solution task 2 |

Reference solution | Solution task 3 |

##### Unit 2: Functions in math

Lecture slides | Functions in math |

Reference solution | Exercise solutions |

##### Unit 3: Linear Algebra

Document | Slides |

Reference solution | Exercise 1 solution |

Reference solution | Exercise 2 solution |

##### Unit 4: Calculus

Lecture slides | Slides |

Reference solution | Exercise solutions |

##### Unit 5: Integration

Lecture slides | Slides |

## Documents

Document | Exam topics |

Document | Practice exam |

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