Data Science Certificate Programm - Extra-Occupational Education at LMU Munich

The program consists of 9 lecture days, each dedicated to one of the following topics:

1. First Steps in Data Analysis (Dr. Casalicchio)
2. Statistical Foundations (Prof. Kauermann)
3. Statistical Modeling (Prof. Kauermann)
4. Large-Scale Data Science and AI (Prof. Kranzlmüller)
5. Unsupervised Methods (Dr. Casalicchio)
6. Supervised Machine Learning 1 (Prof. Bischl)
7. Supervised Machine Learning 2 (Prof. Bischl)
8. Supervised Machine Learning 3 (Prof. Bischl / Dr. Casalicchio)
9. Introduction to Deep Learning (Prof. Rügamer)

For detailed module descriptions and learning objectives, please refer to the curriculum.

The Steering Committee decides if applicants meet the requirements for the Professional Certificate Program. The basic requirements are: 

• University degree and work experience (exceptions to the following requirements may be possible):
  
  • either a university degree in a field related to mathematics, statistics, computer science, or other related disciplines (e.g., if you took multiple courses in the related fields) and at least one year of work experience or
  • any kind of university degree and at least three years of work experience in an area relevant to the certified data science training program.
• The Data Science Certificate Program includes some minor practical sessions and demos where basic knowledge of the statistical programming language R can be an advantage (some practical sessions may supplement the R code with additional Python code; however, our current emphasis remains on R). Therefore, if you lack basic proficiency in R or seek to refresh your skills, we advise either undertaking self-study to learn R or enrolling in a dedicated R course (e.g., Essential Data Science Training GmbH, a LMU Spin-off, offers a specialized R course before the beginning of every program). 
• See the Course Regulations (140 KByte) for more information.

The course is currently offered once per year in an in-person format only. As we generally avoid mixed or hybrid delivery, remote participation on specific dates may be granted only in exceptional, well-justified cases and is at the participant's own risk (we cannot guarantee the reliability of the technical setup). The exam is always in-person. We expect attendance at a minimum of six in-person course days. If you can already anticipate needing remote participation on specific days, please email those dates immediately after your submission to [email protected]

Duration: The program consists of 9 lecture days (e.g., each from 09:00 to 17:00 in case of an in-person course) and one exam day.

Workload (estimated): 200 hours (including participation in lectures, preparation time, follow-up work, and for the exam).

Language of instruction: English (unless all participants understand German well enough, however, the course material itself will always be in English)