Objective of Educational Program

The goal of the study program is to provide practice-oriented training of highly qualified specialists in the field of computer science for enterprises with general cultural and professional competences in the field of big data analysis, as well as create conditions for continuous professional self-improvement, development of social and personal competencies of specialists, expansion of social mobility and competitiveness on labor market.

List of a specialist’s positions

• Data Analyst
• Big Data Analyst
• Software Developer
• Deputy head of the structural unit
• Expert of the republican center
• Data Scientist
• Big Data Engineer
• Technician
• Head of the structural unit
• Employee of the national scientific and practical center, university.

Learning outcomes

• Apply hardware and software services to ensure the continuity of the process of developing software systems.
• Explain and understand the regulatory framework, including documents, standardization and certification procedures in the development of information and communication technologies.
• Apply algorithms for collecting data from open sources, methods for preprocessing the collected data, basic and advanced models for predicting and making decisions based on this data.
• Use knowledge of the regularities of random phenomena, their properties and operations on them, models of random processes and modern software environments to solve problems of statistical data processing and building predictive models.
• Demonstrate knowledge of the architecture of computer systems, manage operating systems.
• Apply domestic and foreign standards for software development in organizations.
• Apply mathematical tools for analyzing software systems and data based on statistical and probabilistic models.
• Design, develop and analyze algorithms for solving computational and logical problems, evaluate the efficiency and complexity of algorithms based on formal models of algorithms and calculated functions.
• Independently analyze modern sources, draw conclusions, argue them and make decisions based on information.
• Apply methods and algorithms of artificial intelligence, data mining, machine learning, neural network and fuzzy data processing to solve problems of classification, forecasting, cluster analysis and recognition of various objects.