The academic program Data Science is aimed at training specialists in the analysis of ultra-large and heterogeneous data, capable of extracting knowledge from real-time data streams and making informed business decisions based on mathematical, statistical, and computational methods.The program develops interdisciplinary competencies in mathematics, statistics, information technologies, and economics, necessary for working with distributed computing systems and modern Data Science challenges.

— Machine Learning II

— Neural Networks

— Reinforcement Learning and Its Applications in AI

— Optimal Control

— Exploratory Data Analysis

— Deep Learning for Applied Mathematics

— Nonlinear Programming Methods

— Deep Learning for Inverse Problems

— Methods for Solving Ill-Posed Inverse Problems.

— Ability to build mathematical models using modern information technologies methods

— Ability to analyze received information

— Ability to develop new algorithms

— Ability to design optimization methods and control algorithms

— Ability to process large volumes of data.

— Interdisciplinary foundation: The program ensures systematic integration of knowledge and skills in the field of mathematics, statistics, information technologies, and economics for comprehensive data analysis

— Big and heterogeneous data work: The training is focused on the methods of collecting, storing, processing, and analyzing large, complex, and dynamically updated datasets in distributed environments

— Practice-oriented learning: Formation of professional competencies is implemented in solving real-world problems through projects and research using real datasets

— Modern data analysis methods and tools: The program ensures mastering current methods of statistical analysis, modeling, machine learning, and specialized Data Science tools

— Alignment with professional and educational standards: The program content and learning outcomes are consistent with the requirements of professional standards and ensure that graduates are prepared for professional activities and further education.

— Software Support Specialist

— Neural Networks Specialist

— Machine Learning Specialist

— Database and Network Librarian.