The Professional Certificate Program "Data Science" is an extra-occupational training at LMU. Its purpose is to communicate adequate knowledge of the theory and methods of Data Science. With this background we would like to meet the potential in the practical work experience. The program orients itself along the following guidelines:

• Introduction to the theoretical and practical concepts in the field of Data Science
• Transfer of solid expertise in a wide scope of areas
• Training of analytical and strategic skills

With an estimated workload of 200 hours (including time for preparation, follow-up work and preparation for the exam) the Certificate Program is developed as a one semester course. The Professional Certificate Program is spread over nine days of teaching excluding the day of the exam.

On this Moodle-Platform you can download seminar material.

For more Information click here or visit the Curriculum.

The Professional Certificate Program "Data Science" is an extra-occupational training at LMU. Its purpose is to communicate adequate knowledge of the theory and methods of Data Science. With this background we would like to meet the potential in the practical work experience. The program orients itself along the following guidelines:

• Introduction to the theoretical and practical concepts in the field of Data Science
• Transfer of solid expertise in a wide scope of areas
• Training of analytical and strategic skills
  

Please note: This Winterterm 20/21 the Data Science for Researchers exceptionally will be held as a live online course. Please find more information below.
This course is specifically aimed at young and advanced researchers from any research field who want to acquire a more in-depth theoretical understanding of several data science-related topics. Researchers from universities, research institutes, and research departments are welcome to join the course. Participants should already have basic knowledge in statistics, data analysis and machine learning as the course will have a strong focus on methodological and theoretical foundations of advanced topics. As a prerequisite for the course, participants should be familiar with the content of the online lecture "introduction to machine learning" (see https://compstat-lmu.github.io/lecture_i2ml). If this is not the case, participants are expected to study the contents from this online lecture either in a self-study or by visiting a separate machine learning course, e.g., https://www.essentialds.de/kurse/machine-learning-r.

General Information

• Duration: LIVE ONLINE COURSE 18 days, between 11.11.2020 and 10.12.2020 (time: 09:00 - 12:30), 1 contact day (11.12.2020) and 1 assessment of the learning progress in a test with short questions (14.12.2020)
• Language of instruction: The planned course language is English unless all participants understand German well enough

• Lecture 1 (11. and 12.11.2020): Visualisierung, Wiedemann
• Lecture 2 (16. and 17.11.2020): Statistical Foundation, Kauermann
• Lecture 3 (18. and 19.11.2020): HPC / Data Privacy, gentschen Felde
• Lecture 4 (23. and 24.11.2020): Advanced Statistical Modeling, Prof. Dr. Göran Kauermann
• Lecture 5 (25. and 26.11.2020): Machine Learning, Dr. Giuseppe Casalicchio
• Lecture 6 (30.11.2020 and 01.12.2020): Optimierung, Prof. Dr. Christian Müller
• Lecture 7 (02. and 03.12.2020): Machine Learning, Prof. Dr. Bernd Bischl
• Lecture 8 (04.12.2020 - WHOLE DAY): Deep Learning, Dr. Janek Thomas
• Lecture 9 (09. and 10.12.2020): Unsupervised Learning, Prof. Dr. Peer Kröger
• Day 10 (11.12.2020): Contact hours for Students
• Day 11 (14.12.2020): Assessment of the learning progress in a test with short questions