| Lecturer: | Klaus Diepold |
| Assistants: | Sven Gronauer, Alice Hein |
| Target: | Students from non-technical fields |
| ECTS: | 3 |
| Contents: | (SWS Lecture/Exercises/Practical Work) |
| Semester: | Every Summer Term |
| Registration: | TUMOnline beginning from 01.02.2023 |
| Time & Location: | Block Course from 27.03. - 06.04.2023, Online (Zoom), 08:30-16:30 |
| Start: | first Lecture on 27.03.2023 |
Contents
In case of late registration please contact us directly via email.
Objectives of the module
The module Learning of Data and Linear Algebra teaches important mathematical basics and tools from the field of Linear Algebra and deepens them by acquiring practical programming skills (Python) in the application field Machine Learning.
The module is aimed at students of non-technical fields of study, such as students of political science or in the field of MCTS.
An important goal here is to create an improved connectivity to technical subjects for the participating students, i.e. that the students are enabled to successfully attend more advanced technical modules.
Course Description
Students of non-technical subjects should find it easier to join technical-scientific subjects. This module aims to provide them with basic knowledge and practical experience in the use of linear algebra and its application in technical subjects. The module focuses on practical computational methods and numerical algorithms as currently used in many data-centric disciplines (e.g. machine learning, simulation). Participants will acquire practical skills in the subject area by learning basic programming skills in languages such as Matlab or Python. The practical programming tasks are mainly taken from the subject area machine learning.
Upon successful completion of the module, the participants will be able to map typical computational problems of machine learning to standard linear algebra problems, to select appropriate algorithms and to implement them in the form of executable Matlab/Python programs. Afterwards, students will be able to attend a wide range of technical courses at TUM and follow the content there or participate in application-oriented hackathons and contribute technically. Non-technical students will be exposed to a "maker" mindset and motivated to do their own implementation work.
Course Schedule
The course will take place before the start of the lecture period of the summer semester, in the period 27.03. - 06.04.2023, over a period of 9 working days as a block course.
Classes will be offered online via Zoom. If students have any questions, they can contact the teaching assistant: sven.gronauer@tum.de.
On the course days there are 2 x 90 minutes lecture and exercise hours for linear algebra in the morning. In the afternoon, there will be 2 x 90 minute programming classes (Matlab/Python).
Course materials will be provided electronically. The course is credited with a total of 3 ECTS.
The course is held in English, but can also be held in German if required. The course materials are in English.
Additional offer for course participants
Staff members of the Chair of Data Processing supervise and accompany the participating students if they take a technical module in the following summer semester.
Prerequisites
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Students need only A-level math skills and no special programming skills.
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Students should have their own Internet-enabled laptop on which Matlab/Python can be installed free of charge.