## Markus Dahinden: Catalogue data in Autumn Semester 2017 |

Name | Dr. Markus Dahinden |

Address | Lehre D-INFK ETH Zürich, CAB H 31.1 Universitätstrasse 6 8092 Zürich SWITZERLAND |

Telephone | +41 44 632 53 52 |

markus.dahinden@inf.ethz.ch | |

Department | Computer Science |

Relationship | Lecturer |

Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|

252-0839-00L | Informatics | 2 credits | 2G | L. E. Fässler, M. Dahinden | |

Abstract | Students learn to apply selected concepts and tools from computer science for working on interdisciplinary projects. The following topics are covered: modeling and simulations, visualizing multi-dimensional data, managing data with lists and tables and with relational databases, introduction to programming, universal methods for algorithm design. | ||||

Objective | The students learn to - choose and apply appropriate tools from computer science, - process and analyze real-world data from their subject of study, - handle the complexity of real-world data, - know universal methods for algorithm design. | ||||

Content | 1. Modeling and simulations 2. Visualizing multidimensional data 3. Data management with lists and tables 4. Data management with a relational database 5. Introduction to macro programming 6. Introduction to programming with Python | ||||

Lecture notes | All materials for the lecture are available at www.evim.ethz.ch | ||||

Prerequisites / Notice | This course is based on application-oriented learning. The students spend most of their time working through projects with data from natural science and discussing their results with teaching assistants. To learn the computer science basics there are electronic tutorials available. | ||||

252-0852-00L | Foundations of Computer Science | 4 credits | 2V + 2U | L. E. Fässler, M. Dahinden, H. Lehner | |

Abstract | Students learn to apply selected concepts and tools from computer science for working on interdisciplinary projects. The following topics are covered: modeling and simulations, introduction to programming, visualizing multi-dimensional data, introduction matrices, managing data with lists and tables and with relational databases, universal methods for algorithm design. | ||||

Objective | The students learn to - understand the role of computer science in science, - to control computer and automate processes of problem solving by programming, - choose and apply appropriate tools from computer science, - process and analyze real-world data from their subject of study, - handle the complexity of real-world data, - know universal methods for algorithm design. | ||||

Content | 1. The role of computer science in science 2. Introduction to Programming with Python 3. Modeling and simulations 4. Introduction to Matrices with Matlab 5. Visualizing multidimensional data 6. Data management with lists and tables 7. Data management with a relational database 8. Universal methods for algorithm design | ||||

Lecture notes | All materials for the lecture are available at www.gdi.ethz.ch | ||||

Literature | L. Fässler, M. Dahinden, D. Komm, and D. Sichau: Einführung in die Programmierung mit Python und Matlab. Begleitunterlagen zum Onlinekurs und zur Vorlesung, 2016. ISBN: 978-3741250842. L. Fässler, M. Dahinden, and D. Sichau: Verwaltung und Analyse digitaler Daten in der Wissenschaft. Begleitunterlagen zum Onlinekurs und zur Vorlesung, 2017. | ||||

Prerequisites / Notice | This course is based on application-oriented learning. The students spend most of their time working through projects with data from natural science and discussing their results with teaching assistants. To learn the computer science basics there are electronic tutorials available. |