The aim of this course is to: – position data science as the discipline and explain its relations to statistics; – explain all the necessary notions and methods inherited from mathematics, statistics, and computer science including specific slang used by professionals in this area; – explain data science workflow: data acquisition, data preprocessing, feature engineering, feature selection, model training, model testing, post-hock interpretation; – explain in detail the process of model validation and testing; – explain simple tools used to visualise the results; – explain usage of SQL. Sven Nõmm
