Data Science was characterized as an interdisciplinary field that extracts knowledge and patterns from structured and unstructured data using scientific methods, processes, algorithms and software systems.

The connection of data science with the concepts of data mining and big data was highlighted.

A. Hovakimyan touched upon the main problems and application areas of data science, such as healthcare, finance and banking, education, advisory systems, smart agriculture, linguistics and natural language processing, social media, personalized systems, etc.

It was noted that the application of data science methods in various professional fields involves the creation and study of mathematical statistics, machine learning and artificial intelligence models.

The main stages of the data science life cycle were presented: data discovery and collection, data preprocessing and statistical analysis, machine learning model selection, training, testing and evaluation, model implementation and operation, preparation and presentation of reports for different categories of stakeholders. These stages were interpreted on the example of the problem of diagnosing diabetes mellitus in patients.