Every year, in response to IT industry demands, the Higher School of Economics Faculty of Computer Science launches new educational programmes while updating existing ones. In 2026, the faculty introduced Bachelor’s and Master’s degree programmes in robotics for the first time.
Ivan Arzhantsev, Dean of the Faculty of Computer Science, highlighted the well-coordinated work between faculty staff and industrial partners that made the new programmes possible.
Ivan Arzhantsev
‘The launch of programmes in robotics, neural network technologies, and intelligent HR management reflects not only short-term trends but also long-term market challenges,’ he said. ‘Our teachers and experts strive to maintain a balance between fundamental science and practice. Thanks to partners like Yandex and Alfa-Bank, we are confident these programmes will remain in demand for decades. This is not an experiment but a conscious step into the future taken by a team of professionals.’
Bachelor’s Programme in Design of Intellectual Robotic Systems
This programme aims to train a new generation of engineers capable of solving problems at the intersection of artificial intelligence, mechanics, electronics, and control theory. It will educate system engineers who can build robotic complexes from the ground up: from problem analysis and mathematical modelling to designing hardware platforms, developing autonomy software, and conducting comprehensive testing.
Courses in engineering project management and hardware-software systems development will teach students to assess technical risks, production constraints, and economic efficiency of their designs.
Sergey Lebedev
‘Our programme meets a strategic economic demand and aligns with the national technology initiative for training personnel in future-defining sectors: autonomous transport, personal and service robotics, smart manufacturing, logistics, and smart cities,’ explained Sergey Lebedev, Head of the School of Software Engineering.
The programme integrates several trending fields and technologies:
artificial intelligence and machine learning, covering not only control but also creation of robots that learn, adapt, and make decisions in uncertain environments;
computer vision, enabling robots to see and understand their surroundings;
neurotechnology and bionic control at the biology-technology intersection;
cyber-physical systems and the Internet of Things (IoT), where robots function as part of larger networks (eg, smart cities, factories, or homes).
Students will gain in-depth knowledge in higher mathematics, physics, control theory, algorithms, and data structures essential for analysing and modelling robotic systems. They will learn to design and construct mechatronic modules, develop and debug electronic components, and use CAD systems. The curriculum also provides practical skills in computer vision, navigation, simultaneous localization and mapping (SLAM), trajectory planning, and machine learning for adaptive control.
Graduates will possess a uniquely broad scope of competencies, enabling them to work at the cutting edge of technological development.
Master’s Programme in Smart Devices: Hardware Development
Launched in partnership with Yandex, this new programme addresses the growing need for specialists who can not only to develop electronics and embedded software but also understand the entire device cycle—from user requirements and operational features to production, certification, and quality assurance. It meets the demand for engineers with deep knowledge of electronics and embedded systems, along with practical skills in creating modern intelligent devices.
Mark Blumenau
‘Demand for smart devices is growing,’ explained Mark Blumenau, the programme’s academic director. ‘We used to joke about smart toasters and refrigerators, but now many people have smart TVs, speakers, and even kettles. These devices simplify daily life. Our Master’s programme trains the specialists who will develop them. This programme is unique for the Faculty of Computer Science because students learn to create not only software and artificial intelligence models for such devices but also the relevant hardware.’
Cooperation with Yandex, a leading Russian IT company, gives students access real-world engineering problems in smart-device development. They will study circuit design, IoT interfaces and protocols, system programming, and testing and prototyping methods, applying this knowledge to actual projects. Courses in engineering project management and hardware-software systems development will help students to assess technical risks, production constraints, and economic efficiency.
Through mentor seminars, industry engineers will teach modern design methodologies, development management, and principles for building high-tech product solutions.
Master’s Programme in Artificial Intelligence and Product-Based Approach in HR Management
Implemented in partnership with Alfa-Bank, this Master’s programme (formerly ‘Product-Driven Approach and Data Analytics in HR Management’) was originally built around product management and analytics. It is now evolving naturally towards integrating more advanced methods and technologies. The updated educational programme in Artificial Intelligence and Product-Based Approach in HR Management shifts from general data analytics to specialised AI applications in HR. It includes studying machine learning for predictive analytics, intelligent recruitment algorithms, virtual assistant technologies, and data-driven systems for employee assessment and development decisions.
Alisa Melikyan
‘We have significantly reinforced and expanded the AI component,’ said Alisa Melikyan, the programme’s academic director. ‘The content now goes beyond data analytics. Students study various artificial intelligence technologies in depth alongside their HR applications. The curriculum includes courses on machine and deep learning, plus modules on NLP, prompt engineering, and building AI agents.’
Master’s Programme in Applied Neural Network Technologies (formerly Master’s Programme in Data Science)
The Faculty of Computer Science’s first online program is evolving from broad data science education towards a practice-oriented focus on integrating neural network technologies into business. Its new name—Applied Neural Network Technologies—accurately reflects this shift from general analytical approaches to creating and maintaining complex AI solutions.
Ruslan Kayumov
‘One of the first online programmes in our faculty, and perhaps in the country, is changing radically,’ commented its academic director Ruslan Kayumov. ‘The new name reflects a fundamental labour market shift towards specialists who can leverage advanced technologies to solve real business problems from scratch and at pace.
The updated programme remains accessible to beginners; a technical background is not required. However, the educational process is now focused on achieving a specific practical outcome: graduates will be able to design and integrate AI agents, RAG (retrieval-augmented generation—Ed.) systems, and other complex solutions into business processes. This is an overhaul of the programme in response to the challenges and opportunities presented by the latest phase of IT development.’