Introduction
In science, engineering and business, decisions are usually based on data obtained through experiments, observations or surveys ("data science"). These data are subject to uncertainty and random variation, and automated collection systems can produce big data sets that are difficult to interpret.
Statistics provides the framework for analyzing data and turning it into credible conclusions. While many degree programs cover basic techniques, complex questions often require more advanced, specialized methods.
Our course is designed for scientists, engineers and business professionals who already analyze data but feel limited by their current statistical knowledge. It is ideal for those who need a broader set of methods to achieve more reliable results.
The CAS / DAS in Applied Statistical Data Science provides a comprehensive understanding of statistical methods for data analysis and modelling. It is targeted at practitioners who regularly conduct statistical analyses as part of their daily work, and who need a broader set of methods to reach more reliable results.
Participants are introduced to useful and modern statistical methods and learn to adapt them to the specific requirements of their own professional context.
Within the individual topics
- various methods are presented (typically using examples) and applied using the software R,
- the mathematical and probability theory fundamentals are taught, insofar as they are necessary for understanding the methods,
- more general aspects of statistical method selection and experimental design are also covered.
The course builds on a university degree in which probability and statistics were introduced (these basics are repeated in the introductory part).
The continuing education program can be completed after approx. 12 months with a “Certificate of Advanced Studies” (CAS). If you are interested, you have the option of acquiring a "Diploma of Advanced Studies (DAS)" after a further 12 months.