Program Description
The Master’s program “Artificial Intelligence” is designed to train highly qualified specialists and researchers capable of developing advanced algorithms, applying machine learning methods, and working with big data. The curriculum combines strong theoretical foundations with practical project implementation and includes active research work.
Graduates of the AI master’s program can work in various fields such as IT companies, research institutions, startups, robotics and automation companies, financial and medical organizations, as well as areas related to smart cities, security, and many other sectors.
Purpose and Objectives of the Educational Program
Program Purpose:
To train highly qualified professionals capable of developing, implementing, and researching intelligent systems and technologies based on machine learning, data analysis, and neural network approaches to address relevant challenges in science, business, and industry.
Key Objectives:
- In-depth study of modern deep learning architectures, including transformers, graph neural networks, and generative models.
- Optimization of machine learning algorithms for low-resource environments (edge AI, federated learning).
- Development of hybrid systems combining machine learning, statistical methods, and expert systems.
- Creation of innovative methods for processing unstructured data (text, images, video, audio) using neural and traditional algorithms.
- Development of self-learning systems resistant to concept drift and dynamic data changes.
- Designing distributed computing systems and parallel algorithms for big data processing.
- Development of intelligent decision-making systems for critical industries (aviation, medicine, finance).
- Research of artificial intelligence’s impact on the labor market and social institutions.
- Designing digital security models and personal data protection systems in AI solutions.
- Applying multi-agent systems and control theory to create complex automated solutions in robotics, financial markets, autonomous transport systems, and other fields.
- Participation in AI research projects, publication of scientific papers, and engagement in grant programs and international hackathons.
These objectives ensure the preparation of specialists capable of not only using modern AI technologies but also creating new technological solutions that influence the development of science, business, and society.
Learning Outcomes (LO / ON)
LO1: Ability to analyze and apply core concepts, technologies, and methods of the Internet of Things (IoT) and Artificial Intelligence (AI), develop IoT devices using modern hardware/software tools, and build AI-based systems for data processing and decision-making.
LO2: Knowledge of fundamental theories, methods, and algorithms of artificial intelligence, including machine learning, neural networks, search algorithms, natural language processing (NLP), computer vision, and others.
LO3: Ability to develop, test, and deploy machine learning, deep learning, and neural network algorithms.
LO4: Ability to effectively process large volumes of data, critically approach their collection, cleaning, and analysis.
LO5: Ability to adapt and apply AI technologies to solve tasks in healthcare, finance, robotics, transportation, and other fields.
LO6: Ability to conduct scientific research and develop new methods and approaches in the field of artificial intelligence; skills in writing and publishing research papers, and participating in conferences and scientific projects.
LO7: Ability to use AI technologies to improve quality of life and solve social problems, analyze ethical aspects of AI usage, and develop sustainable and socially responsible technological solutions.
LO8: Ability to work effectively in interdisciplinary teams involving experts from business, engineering, medicine, and other fields.
Atlas of New Professions
- Universal AI Developer
- Artificial Neural Network Designer
- Multiexperience Monitoring Specialist
- IT Ethics Consultant