Pipeline development

Machine learning and neural networks have become an integral part of the IT industry, as well as a foundation for a variety of services, platforms, and companies. However, AI has a wider range of applications – including data labeling and enrichment, analysis of texts, images, and audio (mainly speech recordings), as well as intelligent planning methods, graph databases, and semantic technologies. At the same time, there is a growing interest in accelerating calculations for various applications.

These days AI is represented by hybrid systems that require special solutions in terms of architecture, hardware, and software. This is why the labor market is seeking specialists who are not only capable of creating software for AI but deeply understand this technology and thus will be able to design and develop such systems based on tested and predictable engineering solutions. 

Students at the new program will be trained as such specialists, which is one of its defining features. While other AI-oriented programs teach students to come up with technological solutions (neural networks) for specific applied tasks, the Design and Development of AI Systems Master’s program will focus on platform AI architectures and their designs for real-life infrastructure, as well as adaptation for existing business processes and limitations.

“We are not as oriented towards providing specific applied AI solutions. Instead, our program is focusing on topical issues in industrial AI development: organizing processes at a major IT company and ensuring that neural networks could be used for multiple tasks; archivating the results of specific projects for later use; supporting users, maintaining security, and testing such systems. These tasks are important because now the industry is looking for evidence-based and tested AI,” explains Pavel Kustarev, the dean of the Faculty of Software Engineering and Computer Systems and the head of the new program.  

Program curriculum

Students will be able to choose their own learning track within one of the two specializations: 

• Design of AI Systems – for those who want to get into the complex of contemporary methods and technologies for AI systems design and aim to become full-range ML specialists able to occupy managing positions; 
• Development of AI Applications – for those who want to explore the AI industry in applied fields, such as computer vision, image processing, natural language processing, etc.; graduates of this specialization will be able to work as leading specialists in their chosen fields.

Apart from fundamental principles and mathematical foundations of AI, special focus will be made on organizing and creating infrastructure for the development of AI systems within the context of the IT industry, as well as on validation, testing, storage, and support of AI products.

Students will also have the opportunity to take practice-oriented courses from industry experts, such as on basic Java development, software quality assurance, and DevOps – technologies for organizing software development at major IT companies.

Project-based learning

Prospective students with a substantial programming background and experience in applying neural networks will be able to take a project-based approach to education. They will have the opportunity to choose the narrow field they would like to excel in, form their individual learning track, and work on a project with two mentors – one from the university staff and one industry representative.

This Master’s program is a result of collaboration of the faculty and leading IT companies (MTS, Deutsche Telekom, Luxoft, GS Group, 1C, and others), which means that students will be working on projects suggested by these industrial partners. For instance, the MTS Artificial Intelligence Center has suggested the development of solutions based on Kneron processors meant for on-device and not cloud-based AI, which is a crucial technology for the Internet of Things. The joint project with Nanosoft focuses on text processing (primarily, engineering documentation) and its classification based on semantic connections. Moreover, students will be able to receive funding from the university through the system of grants for R&D projects developed by Master’s and PhD students. Master’s students who will be working on projects suggested by corporate partners will earn salaries from respective companies.

Who the program is for 

Some experience in programming and mathematics is essential for being a student at the program. IT specialists wishing to acquire engineering competencies and get experience with the technological approach to contemporary AI systems development will make the core of the program. However, organizers of the program are also expecting that about two thirds of students will come from adjacent (such as robotics or telecom) or even remote fields but after substantial self-study. There is a special selection of courses offered at the faculty to help such students get to the needed competence level.

How to enroll 

This year, the program will welcome 30 students, who can enter either by taking entrance exams or through one of the following contests:

• Contests for best reports at the Congress of Young Scientists;
• ITMO’s Portfolio contest;
• I am a Professional contest;
• ITMO’s MegaContest. 

There are also contests organized by the faculty: Hack for Your Success and SHWare. See here to learn more about enrollment opportunities for international students.

Job prospects 

Graduates of the program will be able to take positions of ML and DevOps/QA engineers, systems analytics or architects, as well as programmers. On the other hand, a serious background in AI methodology will enable graduating students to also work as data scientists, data analysts, or data engineers.

Students will have opportunities to intern at leading IT companies, first of all at the MTS Artificial Intelligence Center, but also at Luxoft, GS Group, Huawei, Yandex, VK, and other companies. This experience can also become a foundation for students’ Master’s theses. 

“Our main idea is that in any practical or research activity – either at university or its partners – our students are oriented towards their educational goals. We want it to not just be a job but a development of their professional qualifications and personal potential,” says Pavel Kustarev. 

Combining studies with a job or an internship is an approach that will offer students more chances to build a successful career in the future, believes Anton Maslov, a leading developer at the MTS Artificial Intelligence Center.

“Generally, ambitious students start working part-time already in the final years of their studies. That is why it’s so important to choose your field as soon as possible and begin to gain practical experience in the real sector – it would be wonderful to get it through internships at major IT companies. Specialists with experience from well-known corporations, even as interns, are really sought-after on the market. You have to be ready to get into each company’s interests, understand the mechanisms at work in the market, keep track of trends in your field, and learn on your own. You will need to find a balance between being a good specialist in your field and handling the most complex tasks – while at the same time having a good overview of the industry as a whole,” concludes Anton Maslov.