Summary of Degree Programme
01.04.02 Applied Mathematics and Informatics
No
2 года 
Full-time, 120
ENG
Instruction in English
Master
No
2026/2027 Academic year
Computer Vision
KEO - 2 - Is able to apply modern data analysis tools, including the use of programming, algorithmic skills and mathematical methods.
KEO - 3 - Applies advanced neural networks to solve applied problems in the field of computer vision
KEO - 4 - Implements software systems for image and video analysis and processing
KEO - 5 - Analyzes specific scientific literature and performs comparative analysis of results in the field of computer vision
PC - 2 - Able to conduct independent scientific research, critically analyze interdisciplinary scientific and technical achievements, and modify mathematical methods to solve advanced problems in artificial intelligence.
PC - 3 - Able to create interdisciplinary scientific and technical texts, document and present the results of professional activities publicly, and describe and responsibly monitor the implementation of technological requirements and regulatory documents.
Mathematical Module (1 course): Provides fundamental theoretical training necessary to understand machine learning algorithms.
Programming Module (3 courses): An IT foundation aimed at developing skills in highly effective software development.
Professional Module (9 courses): A specialized core covering the theoretical foundations and modern tools of computer vision, deep learning, and data analysis.
Project module (2nd year): a practice‑oriented block for testing the acquired knowledge on real industrial tasks.
The final element of the programme is the completion of a large‑scale applied graduation project, which demonstrates the graduate’s readiness to solve complex industry tasks.
2025/2026 Academic year
Computer Vision
KEO - 2 - Is able to apply modern data analysis tools, including the use of programming, algorithmic skills and mathematical methods.
KEO - 3 - Applies advanced neural networks to solve applied problems in the field of computer vision
KEO - 4 - Implements software systems for image and video analysis and processing
KEO - 5 - Analyzes specific scientific literature and performs comparative analysis of results in the field of computer vision
PC - 2 - Able to support collective scientific communication, organize scientific events
PC - 3 - Able to organize training of specialists in the field of applied mathematics
PC - 4 - Able to analyze and reproduce the meaning of interdisciplinary texts using the language and apparatus of applied mathematics and computer science
PC - 5 - Able to create interdisciplinary texts using the language and apparatus of applied mathematics and computer science
PC - 6 - Able to design and publicly present the results of professional activities using information technologies
PC - 7 - Able to carry out a purposeful multi-criteria search for information on the latest scientific and technological achievements on the Internet and in other sources
PC - 8 - Able to create, describe and responsibly control the fulfillment of technological requirements and regulatory documents in professional activities
PC - 9 - Able to acquire, cleanse, analyze and visualize large amounts of data
PC - 10 - Able to implement models and algorithms of applied mathematics in the form of computer programs
The programme consistes of 16 online training courses, divided into 4 blocks:
“Mathematics" (1 course) Basic course in the field of mathematics, necessary for the further development of disciplines
“Programming" (3 courses) Basic courses in the field of IT, necessary for the further development of disciplines
“Professional block" (9 courses) A professional block containing a modern theoretical and instrumental base in the field of computer vision. This block is focused on the study of theoretical approaches and tools for solving applied problems encountered in professional activities
“Project block" (2 courses) A project block that allows to test all the knowledge gained within the professional block on applied projects provided by partner companies)
A large final project (A final project providing you the opportunity to demonstrate a complexity of knowledge (both theoretical and practical) acquired in the program)
TOP QUALITY LEARNING
Program team has been working on computer vision more than 11 years
International Laboratory of Algorithms and Technologies for Network Analysis LATNA is deeply working on data analysis research projects in computer vision field, so all students are able to participate in professional researches and pretend to be included into list of publications and papers authors
The rigorous curriculum combines core data science courses (like machine learning, 2D image processing, object oriented programming) with very specific and narrow courses to master exactly professional skills (like Deep learning in computer vision, Applied tasks in computer vision)
The Students will learn the subjects from real practicing CV engineers from top IT companies including Intel and Huawei
INTARACTIVE AND ENGAGING
All teaching staff works around the teaching of computer vision their students and solving real computer vision problems daily at work that allows both sides to be in trends in computer vision field
Students get access to direct communication with program team through several online channels
Online student has all the same access to the HSE on campus student services
Students are able to participate in computer vision research projects held by scientific research group of HSE university
Asynchronous and adaptive synchronous events for dofferent time zones
MODULAR AND STACKABALE
The rigorous balance of theory and practice. Program includes only few theoretical basic courses while others involve applied projects.
To start the degree students don`t need to have particularly kind of bachelor degree. Students will need experience in Mathematics, Python and C++ to enter the program and there is a great possibility to brush up on these skills in advance through
Free application process and entrance examination
The Master’s program in Artificial Intelligence and Computer Vision trains elite engineers and researchers capable of creating next-generation autonomous systems. The curriculum bridges the gap between deep learning theory and practical software engineering, equipping students to solve complex real-world tasks in visual data processing, scene understanding, and automation.
Professional Career Paths
What graduates do:
- Computer Vision Engineer / CV Developer
- AI Research Scientist / Machine Learning Engineer
- Perception Software Engineer for autonomous systems
- R&D Engineer in intelligent robotics
- Solutions Architect in Artificial Intelligence
Employment sectors: autonomous vehicle companies, robotics startups, retail and industrial automation corporations, healthcare technology labs, and leading IT research centers.
Key Competencies of the Graduate
- Advanced deep learning architecture: designing, training, and optimizing deep neural networks for complex visual and sensory recognition tasks.
- Image and video analytics: implementing algorithms for object detection, semantic segmentation, video tracking, and 3D scene reconstruction.
- Embedded AI and edge computing: deploying and accelerating machine learning models on resource-constrained hardware and robotic platforms.
- Generative AI and graphics: developing generative models for synthetic data creation, image restoration, and neural rendering.
- Full-cycle AI engineering: managing the entire pipeline from data collection and annotation to production-ready deployment and monitoring.
This degree programme of HSE University is adapted for students with special educational needs (SEN) and disabilities. Special assistive technology and teaching aids are used for collective and individual learning of students with SEN and disabilities. The specific adaptive features of the programme are listed in each subject's full syllabus and are available to students through the online Learning Management System.
All documents of the degree programme are stored electronically on this website. Curricula, calendar plans, and syllabi are developed and approved electronically in corporate information systems. Their current versions are automatically published on the website of the degree programme. Up-to-date teaching and learning guides, assessment tools, and other relevant documents are stored on the website of the degree programme in accordance with the local regulatory acts of HSE University.
I hereby confirm that the degree programme documents posted on this website are fully up-to-date.
Vice Rector Sergey Yu. Roshchin
Summary of Degree Programme 'Artificial Intelligence and Computer Vision'
