The training program includes the following main topics:
1. Basic Python: An introduction to the Python programming language, its syntax and basic constructs. Learning the basics of working with variables, conditional constructions, loops and functions.
2. Data preprocessing: the study of data purification and transformation methods before analysis. Consideration of tasks such as removing missing values, filling in gaps, converting data types, and normalization.
3. Exploratory data analysis: the application of statistical methods and data visualization to research and understand data. Training in plotting, distribution analysis, correlation analysis and other data research methods.
The program provides practical tasks and projects that allow you to apply the acquired skills in practice. In addition to studying at the Summer School, participants also visit IT companies.

— Alexander D. Pavlov,
academic supervisor

Alexander Pavlov

Senior lecturer of the Automated Data Processing and Control department