Crash Courses

The chair of Transportation Systems Engineering offers occassional and on-demand crash courses for requested topics. Crash courses are short (e.g. one- to two-month), weekly, ungraded, and zero-ETCS point courses that can be visited voluntarily besides the student's usual curriculum.

Crash courses aim to provide students with basic understanding of topics that support future courses. Currently, the following crash course is being offered:

NOW OPEN: Data Science with Python and R (WS22/23)

The crash course "Data Science with Python and R" conveys the fundamentals of (statistical) programming and the tools used in usual programming environments. Instead of, e.g. object-oriented programming, this crash course's programming focus on reading, modifying, storing, analysing, and visualising data (tables). In four interactive seminars, each of three-hour length, and with additional material that is being provided, the participants are given a basis with which they can continue to delve into data science independently after the course.

Each seminar presents a mixture of lecture-style presentation of programming concepts and terms, followed by programming tasks to be completed by the participants in-course. The crash course is lectured by Cheng Lyu, and Santa Maiti.

The crash course is held fully online via Zoom between 09:30 and 11:45 (CET), include a 15-minute break, and will take place at the following for dates. The course content is being reworked and still subject to change:

  • 11.10.2022 (Tuesday), Programming fundamentals and environment/tools
  • 12.10.2022 (Wednesday), Data science basics in R with RStudio
  • 13.10.2022 (Thursday), Programming basics in Python with scripts
  • 14.10.2022 (Friday), Data science basics in Python with Jupyter

To register for the crash course, please send your name and student ID to qinglong.lu@tum.de.

Past Crash Courses

  • Data Science with Python and R (WS21/22)
    • 11.10.2021 (Monday), Programming fundamentals and environment/tools
    • 12.10.2021 (Tuesday), Data science basics in R with RStudio
    • 13.10.2021 (Wednesday), Programming basics in Python with Spyder
    • 14.10.2021 (Thursday), Data science basics in Python with Jupyter
  • Data Science with Python and R (WS20/21)
    • 11.11.2020 (Wednesday), Programming fundamentals and environment/tools
    • 18.11.2020 (Wednesday), Data science basics in R with RStudio
    • 25.11.2020 (Wednesday), Programming basics in Python with Spyder
    • 02.12.2020 (Wednesday), Data science basics in Python with Jupyter
    • 09.12.2020 (Wednesday), Voluntary intensification and training