01.04.02 Applied Mathematics and Informatics

The Master's program is aimed at graduates of IT, mathematical and economic fields of study. It is designed to train research personnel in the field of applied Mathematics and Computer science, along with theoretical knowledge, who fully possess practical skills in software development related to machine learning methods, in particular, neural networks (Deep Learning), Reinforcement Learning, text processing in natural language (Natural Language Processing), time series forecasting, computer vision. Students take part in the process of learning and acquiring data analysis skills, which is full of interesting tasks. To be able to run deep learning algorithms, the I.I.Vorovich Institute of Mathematics, Mechanics and Computer Science has a computer class with sufficiently powerful video cards (GeForce RTX 2080 Ti). An opportunity has been opened to participate in scientific projects of the I.I. Vorovich MMK Institute, which may be related to the topics of master's theses. Undergraduates take part in the work of student scientific conferences of the Southern Federal University, All-Russian and international scientific conferences, actively participate in sports and social life.

1. High demand and leadership in pay

AI specialists are among the top 3 most sought-after and highly paid professions in IT. With the boom of generative neural network modeling (Generative AI), the market is experiencing a shortage of personnel capable of working with large language models (LLM), computer vision, and implementing AI solutions in real business.
2. Internships with technology leaders
The opportunity to practice and work on real-world cases in leading companies in the industry: Sber (SberTech), Yandex, VK, as well as in program partners (SPGSV SOFTWARE, CVisionLab, Spetsvuzavtomatika, RNIIRS). Students gain experience working in production teams, not just academic projects.
3. Training of AI Transformation leaders
The program generates competencies for the AI Team Lead and AI Product Owner roles. Graduates are able not only to develop models, but also to manage the lifecycle of an AI product (MLOps), evaluate the cost-effectiveness of implementation, understand the ethics and safety of AI, and integrate intelligent systems into the company's business processes.
4.Fundamental mathematical base
Unlike short-term courses, the master's degree provides a deep understanding of mathematics (optimization, probability theory, linear algebra) necessary for developing new neural network architectures, fine-tuning models, and solving non-standard problems that cannot be solved with ready-made library solutions.

Graduates of the program will be able to find work at scientific organizations, universities, IT, construction and design fields, business, law enforcement agencies, the banking sector, and manufacturing enterprises. Sample job titles include: Mathematician, Actuary, Budget or Financial Analyst, CAD Designer, Computer Programmer, Data Scientist, Inventory Strategist, etc. Moreover, theres a possibility of continuing education at the PhD program.
Specialists in the field of artificial intelligence and machine learning are consistently among the top 3 most sought-after and highly paid professions in the Russian IT market. Over the past decade, the number of vacancies in the field of Data Science and ML has increased 30-fold, with the highest demand occurring in the last four years.
Relevant roles for graduates:
ML / AI Engineer — development, training and implementation of machine learning models in production.
LLM Engineer / Prompt Engineer — working with large language models, fine-tuning, creating RAG systems and generative AI products.
MLOps Engineer — building infrastructure for the ML model lifecycle: from training to monitoring in production.
Data Scientist / Research Scientist — research work, data analysis, development of new algorithms.
AI Product Manager / AI Team Lead — managing the development of AI products and technical teams.

The Master's program "Artificial Intelligence: Mathematical models and applied solutions" is aimed at graduates of IT, mathematical and economic specialties and fields of study. It is designed to train research personnel in the field of applied mathematics and computer science, along with theoretical knowledge, who fully possess practical skills in software development related to machine learning methods, in particular, neural networks (Deep Learning), Reinforcement Learning, and natural language text processing. Language Processing), time series forecasting, and computer vision.