Furtwangen, Germany

Data Analysis Concepts with Python

The basic workflow of data analysis encloses the potential pre-processing, suitable storage, beneficial visualization and statistical analysis of complex data. The goal of this workshop aims to enable the participants to design and implement computational approaches to data analysis tasks in a sustainable pythonic manner. In order to provide a common working ground, the workshop starts with a brief but profound introduction to the interpreter language Python and a successive set-up of the common data scientific Python stack, organised in multiple virtual Python environments. To provide a convenient workflow throughout the workshop, the basics of object-oriented programming are refreshed.

The workshop introduces the guiding principles of data science in general and data analytics in particular via hands-on examples covering:
- efficient strategies for the computation with and the organisation of large data sets
- introduction to explorative, descriptive and inferential data analysis
- discussion of statistical principles guiding data analysis concepts
- application of state-of-the-art Python packages on prominent data sets
- visualization techniques of complex data
- usage of an agile working environment via GitLab projects

Course leader

Dr. rer. nat. Nadine Berner

Target group

female STEM-students and professionals

Credits info

1 EC
To do: Data analysis task performed an a given data set, as a documented jupyter notebook within the GitLab project of the workshop and presented in a virtual session to the other workshop participants.

Fee info

EUR 45: Student-price. Fee is for attending the complete course and includes snacks and drinks in our cafeteria. Workshops ans Social program is for free, but needs registration, too.
No travel expenses or accommodation included.
Early Bird until May, 31: 40€.