| Titel | Zeit | Ort | Dozent |
|---|---|---|---|
| Introduction to Python Programming | 17.10.2025 09:00 - 17:00 (Fr) | TUM Graduate School: Boltzmannstr. 17, 85748 Garching bei München, Room 101 | Raphael Boidol & Dr. Michael Oberparleiter |
This workshop introduces the basics of Python programming. It aims to teach programming beginners how to automate solving problems of any kind using Python. Participants will gain a solid understanding of Python syntax, data structures, and essential libraries. The workshop will cover topics including:
- Introduction to Python and its ecosystem
- Basic data types, variables, and control structures
- Functions, modules, and file input/output
- Data manipulation and analysis using lists, dictionaries, and other data structures
- Regular expressions and pattern matching
- Error handling and debugging techniques
- Best practices for writing clean, readable, and maintainable code
- Understand the fundamental concepts of Python programming
- Apply Python to solve everyday problems and automate tasks
- Utilize essential libraries from the Python ecosystem
- Write efficient and well-structured code using an Integrated Development Environment (IDE)
Presentation, interactive tutorials, exercises.
At the beginning of the doctorate │ during the doctorate │ at the end of the doctorate
No prior programming experience is required.
Please bring your laptop.
None.
Raphael Boidol studied mathematics with a focus on engineering at TUM. He joined TNG Technology Consulting in 2011, where he has been supporting clients from a wide spectrum of industries in providing bespoke software solutions. He has ample experience as a full-stack developer, tech lead and architect in designing, developing, and implementing high-end solutions.
Dr. Michael Oberparleiter is a senior consultant at TNG Technology Consulting with a background in theoretical plasma physics. He worked mostly as a full-stack software engineer before starting a journey into various AI applications in the last year. While he covered different aspects of Generative AI including image generation in industrial applications, so far he found the field of code generation the most interesting. Some days, he wonders how this topic will affect the old Fortran codebases he worked with as a scientist.