Computer Science is a fundamental scientific and technological discipline that forms the foundation of the entire modern information technology industry. Unlike purely engineering or applied fields, Computer Science combines deep mathematical and algorithmic training with the practical development of complex intelligent systems, artificial intelligence (AI/ML), big data analytics systems (Big Data), and high-performance computing.

A Computer Science specialist (Data Scientist, AI Engineer, Solution Architect, Systems Analyst) is a professional who understands the fundamental nature of computing, knows how to build mathematical models of the real world, and creates smart, high-load, and efficient IT solutions based on them.

The training of Computer Science specialists is based on studying the following objects:

- data models and representation: mathematical, information, and simulation models of real phenomena, objects, and processes; classical and graph data models, knowledge bases, and ontologies;

- information processing methods and technologies: algorithms for data mining, machine and deep learning (Machine Learning / Deep Learning), computer vision (Computer Vision), and natural language processing (NLP);

- algorithms and computation: computability theory, algorithm complexity analysis, high-performance and parallel computing (Parallel & Distributed Computing), and quantum computing;

- intelligent systems and decision-making: decision support systems (DSS), recommendation systems, multi-agent systems, and generative artificial intelligence;

- computer systems and infrastructure: processes of collection, storage (Big Data), transmission, and protection of information in cloud (Cloud Computing) and distributed environments.

Learning goals by higher education levels:

First (Bachelor's) level — training specialists capable of conducting theoretical and experimental research in the field of Computer Science; applying mathematical methods and algorithmic principles in the modeling, design, development, and maintenance of information technologies.

Main focuses of Bachelor's degree training:

- mastering foundational mathematics (discrete mathematics, mathematical statistics, probability theory, linear algebra) and algorithm theory;

- programming in modern languages (Python, C++, Java, C#, SQL, etc.), studying data structures, and object-oriented design;

- mastering the fundamentals of machine learning, data analysis, database design, and web/mobile application development;

- applying algorithmic principles to optimize and solve practical problems in technical, business, and social domains.

Second (Master's) level — training specialists capable of developing, implementing, and maintaining intelligent systems for data analysis and processing in organizational, technical, natural, and socio-economic systems, as well as acquiring the ability to solve research and/or innovative problems in the field of Computer Science.

Main focuses of Master's degree training:

- developing complex artificial intelligence architectures, deep learning systems (Deep Learning), language processing, and computer vision;

- designing distributed systems, processing large volumes of data in real time (Big Data Architecture, Stream Processing);

- conducting scientific and applied research, developing new mathematical and algorithmic models under conditions of uncertainty;

- managing scientific and technical IT projects, evaluating the efficiency of algorithms and innovative solutions.

Third (Educational-Scientific) level — training highly qualified scientific and pedagogical personnel capable of generating new ideas, solving complex scientific and applied tasks and problems in the field of Computer Science, which involves a deep rethinking of existing knowledge and the creation of new holistic knowledge and professional practice.

Main focuses of PhD (Doctor of Philosophy) training:

- conducting fundamental scientific research in artificial intelligence, theory of computation, new neural network architectures, quantum, and evolutionary computing;

- creating new mathematical methods and algorithms for intelligent analysis of complex ultra-large systems and data arrays;

- publishing scientific results in leading international journals (Scopus / Web of Science) and presenting at CORE A/A* level conferences;

- scientific and pedagogical activity in higher education institutions, leading research R&D laboratories, preparing scientific grant projects.

Key competencies of a graduate:

- artificial intelligence and ML (AI/ML Engineering) — designing, training, and optimizing machine learning and deep learning models (PyTorch, TensorFlow, LLMs, Transformer architectures);

- analytics and Data Science — data mining (Data Mining), mathematical statistics, knowledge extraction, building predictive-analytic models;

- Big Data architecture and Cloud — working with big data processing platforms (Hadoop, Spark, Kafka), designing cloud systems (AWS, GCP, Azure);

- mathematical and simulation modeling — building mathematical models of complex systems, numerical methods, modeling decision-making processes;

- development of complex systems — understanding algorithmic complexity, developing high-performance, parallel, and content-oriented software systems.

Specialty F3 Computer Science provides graduates with one of the broadest ranges of career opportunities in the IT industry, R&D centers, and academia worldwide:

- artificial intelligence and data engineering: Data Scientist, Machine Learning Engineer, AI/ML Researcher, Computer Vision Engineer, NLP Specialist, Big Data Architect;

- analytics and modeling: Data Analyst, Systems Analyst, Business Intelligence (BI) Developer, Quant Analyst;

- software development and architecture: Software Engineer (C++, Python, Java), System Architect, Solutions Architect;

- High-Performance & Cloud Computing: High-Performance Computing (HPC) Specialist, Cloud Architect, DevOps/MLOps Engineer;

- research and R&D: Research Scientist in research centers of global IT giants (Google Research, Microsoft Research, OpenAI, etc.) and product R&D labs;

- science and education (for PhD and Master's degree holders): researcher at the National Academy of Sciences of Ukraine, lecturer/professor of computer science at leading Ukrainian and foreign higher education institutions.

Training is provided by:

- Department of Information Technologies of Design (Department 105);

- Department of Computer Science and Information Technologies (Department 302);

- Department of Mathematical Modeling and Artificial Intelligence (Department 304);

- Department of Radio-Electronic and Biomedical Computerized Means and Technologies (Department 502);

- Postgraduate and Doctoral Studies Department.

Education is provided under the following educational programs:

Educational Program	Degree	Mode of Study	Duration of Study
Information Technologies of Design	Bachelor based on complete general secondary education	Full-time	3 years and 10 months
Virtual and Intelligent Programming Technologies
Intelligent Systems and Technologies
Computer Technologies in Biology and Medicine		Full-time and Part-time
Information Technologies of Design	Master, professional educational program	Full-time	1 year and 4 months
Computerization of Information Processing and Management
Intelligent Systems and Technologies
Information Technologies of Design	Master, educational-scientific program	Full-time	1 year and 9 months
Information Technologies	Doctor of Philosophy	Full-time and Part-time	4 years