Frequently asked questions
In which language is the program?
The planned course language is English unless all participants understand German well enough. However, all provided materials are in English.
At what time do the courses start and end?
The winter term 2020 the course was be held as a live online course. Each lecture is divided into 2 days (thursdays, 13:30 -17:00 and fridays, 09:00-12:30). For details please see the curriculum.
How can I get discount?
There are no discount options for the winter term 2020.
Are there any requirements?
The Certificate Program in generally intended for anyone working in any area of the working or educational life. In order to participate, either a university degree with focus in mathematics, statistics, computer science or related disciplines and at least one year of work experience is required or any kind of university degree qualifying and at least three years of work experience in an area relevant to the certified data science training program.
Is R the main programming language used in the course?
Yes. Basic knowledge in R is highly recommended for the Professional Certificate Program "Data Science". A crash course is available before the beginning of every program. For more information follow the link to the website of the Essential Data Science Training. For more detailed information please look at the curriculum.
What is the admission process?
The admission process can only be done online. Please submit your application online via the following link. You will shortly receive a confirmation of receipt via e-mail. Shortly after the deadline, the steering committee decides whether your application is being considered. Not later than six weeks before the beginning of the course the registration is binding.
What does the fee include?
The fee includes course material and a graded certificate.
What if I miss one or several course days?
Participation is not compulsory but highly recommended. All material is available online shortly after each course day. However, participating and passing the exam is mandatory to obtain the certificate.
What happens at the exam?
There will be a an exam on the last unit of the certificate program (see curriculum for latest dates). More infos on the virtual exam will follow shortly.
What if I fail the exam?
A failed exam can be repeated on the next possible regular date and a separate examination fee will be charged for each retest. See the Course Regulations (104 KByte) for further information.
What do I need to participate?
Please use a PC or laptop with camera and microphone function. The course will be held via ZOOM. For the entire course we kindly ask you to provice the current version of the free software R (https://cran.r-project.org) and RStudio (https://www.rstudio.com/products/rstudio/download).
If you do not have administration rights on your laptop (often the case in company laptops), you should also make sure that you can install R packages on your laptop (for example, with the R command install.packages ("mlr")). We will provide Internet access for all participants via BayernWLAN, please make sure that you can access free WIFI hotspots as you may need internet access for some lectures (e.g. for solving quizzes).
Is there any relevant literature?
This bibliography is only a recommendation, not a requirement to prepare for the course.
- T. Hastie, R. Tibshirani, J. Friedman (2009): The Elements of Statistical Learning. Springer
- K. Murphy (2012): Machine Learning: a Probabilistic Perspective. MIT Press
- E. Alpaydin (2010): Introduction to Machine Learning. MIT Press
- C. M. Bishop (2006): Pattern Recognition and Machine Learning. Springer
- C. Eckert: IT-Sicherheit: Konzepte - Verfahren - Protokolle. Oldenburg
- M. Brenner, N. Felde, et al. (2015): Praxisbuch ISO/IEC 27001: Management der Informationssicherheit und Vorbereitung auf die Zertifizierung. Zur Norm ISO/IEC 27001. Carl Hanser Verlag GmbH
- C. Heumann, M.Schomaker, Shalabh (2017): Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R. Springer
- Wickham (2010): ggplot2: Elegant Graphics for Data Analysis. Springer