Contents:

1. Machine learning and AI development
2. AI architecture and design
3. Applications in fintech, industry, and more
4. Product management in AI
5. AI systems security
6. How to apply

Machine learning and AI development

Program content

Fundamental training. The Deep Learning and Generative AI Master’s program teaches students to interpret how neural networks learn from a probabilistic viewpoint, understand the theoretical grounds of originally heuristic principles found in modern-day deep neural networks, and work with new architectures such as KAN, PINN, and FNO. Graduates of the program are able to independently build and employ ML algorithms and AI systems in science and industry. For instance, they can develop computer vision solutions – such as image generation and style transfer models for vector designs – or design LLM-based agents that can check solutions and maintain conversations to help students master higher mathematics. During their studies, students can also join ongoing research projects and intern at R&D laboratories, be that ITMO’s Computer Technologies Lab, SBER AI Lab, or MTS AI. 

Practical training and business cases. Students of the Big Data and Machine Learning program explore big data analysis and ML methods, as well as go through the full cycle of the development process, from preparing datasets and building ML pipelines to scaling up and implementing the developed models. Students work on real-world cases and complete their internships at partner companies: Sberbank, Yandex, Huawei, and many others. The program is taught in English, which means that students can more easily keep up with the latest trends in the field and immerse themselves in the language.

Career boost. Those who are already working in the field or have a robust mathematical background should take a closer look at Programming and Artificial Intelligence and Artificial Intelligence. The programs offer remote classes, individual learning tracks, and varied thesis options: students can choose to develop a practical project for a partner company or their employer – or work on a research project.

Among the program’s partners are industry leaders. For instance, Artificial Intelligence collaborates with Napoleon IT, X5 Group, Ozon Bank, MTS, Sber AI, Raft, and other companies, which allows students to try their hand at real projects in engineering, research, or education. While working on these projects, students can try themselves as analysts, ML engineers, developers, or data engineers. Each semester, their role will change and so will the set of courses they will need to take. 

Prospective students. The programs are designed for tech majors who are well-versed in machine learning and data analysis, as well as proficient in at least one programming language. Big Data and Machine Learning and Programming and Artificial Intelligence also require applicants to have basic programming skills, as well as a solid background in mathematics and English.

Job prospects. Depending on the program of choice, possible career options include ML engineers, as well mid-level and senior data engineers. Graduates of the Deep Learning and Generative AI and Big Data and Machine Learning can also qualify as deep learning developers, data scientists, AI and data architects, and research engineers at researcher centers. A degree in AI also comes with an opportunity to work as an AI product developer or data analyst.

AI architecture and design

Program content. Future AI and big data system architects can opt for one of the following programs: 

• Design and Development of AI Systems. Here, students learn to select architectures for AI systems and approaches to their design, choose the appropriate AI technology stack, and develop and deploy ML systems.

• Design and Development of Big Data Systems. The program will help extend your knowledge of network programming, organization of distributed calculations in clusters, specialized structures, as well as algorithms for storage, search, and compression in databases. During practical classes, students learn to develop custom subsystems for data storage or processing and new solutions for existing applications based on cases provided by the program’s partners – OZON and Wildberries.

If you want to study voice assistants, your best choice is Speech Technologies and Machine Learning program – a Master’s program that offers an in-depth study of architectures of AI systems for speech recognition and processing. Over the course of two years, you will master basic and advanced ML algorithms as well as learn to solve relevant tasks in voice and multimodal biometrics, recognition of speech and acoustic events, speech synthesis, and natural language processing using machine learning. The program partners up with the Speech Technology Center, where students can intern starting in their first semester. 

Prospective students. The programs are intended for applicants with a programming background; students of Design and Development of Big Data Systems are expected to have experience in backend development.

Job prospects. With a degree in AI system design, you can pursue a career as a ML engineer, AI architect, or an ML project manager. Those who will opt to focus on big data are able to work as data engineers, data architects, and backend developers. Whereas speech technology graduates are qualified to be ML researchers, Python developers, and data analysts. Additionally, all graduates are able to focus on a career in research. 

Applications in fintech, industry, and more

Program content. Students of the program Artificial Intelligence and Behavioral Economics learn to apply ML models in the field of financial technologies: in developing credit strategies or customer behaviour prediction systems for banking, retail, and logistics. Studies follow the full cycle of data processing: from dataset creation to integrating ready solutions into business processes. The program offers two tracks: a Sberbank-sponsored track revolving around working with real financial data and a track focused on global modeling of financial systems.

The application of AI in the oil-and-gas industry, instrumentation, and other fields is the focus of the Master’s program AI in the Industry. Its students develop methods of equipment diagnostics and optimization of industrial processes. This is done with the use of real data at ITMO labs and at the facilities of the university’s partner companies.

In the Data Analytics Master’s program, students learn about methods of storage and processing of structured and unstructured data, intelligent text analysis, and computer vision. This knowledge comes in handy in a variety of fields: from research and medicine to school- and university-level teaching.

Prospective students. The programs are designed for applicants with a background in tech and practicing IT specialists who are familiar with coding and ML models. The program AI in the Industry also welcomes industry specialists: engineers, geologists, and technologists.

Job prospects. Graduates of the first two programs can build their careers as ML engineers, data engineers, and AI architects. Graduates of the Data Analytics program can work as data analysts, data scientists, or ML engineers – or pursue the role of a research engineer.

Product management in AI

Program content. In the program AI Product, students learn to create innovative AI solutions and turn them into viable products. Over the course of two years, they become familiar with various practical applications of machine learning, analyze data using Python, conduct market research, work with cross-functional teams, develop AI prototypes, and manage these programs’ life cycles. The program is implemented jointly with Alfa-Bank, meaning that each student has the chance to work on real business cases, complete an internship, and even receive a job offer.

Prospective students. The program welcomes graduates of tech- and economics-focused Bachelor’s programs with experience in AI product development – as well as tech managers, founders, and startup members with experience in AI design.

Job prospects. Graduates can pursue a career as team leads, product and project managers, or product analysts.

AI systems security

Program content. In the program AI Systems Security, students are familiarized with the basics of machine learning, methods for interpretation, verification, and validation of ML models, dataset verification, and security of AI systems. They also learn to develop and implement ML algorithms and AI systems that are better protected from cyberattacks.

Prospective students. The program suits Bachelor’s graduates with a background in IT. It also welcomes those who have studied natural sciences as their Bachelor’s – however, these applicants will need to complete additional training in order to acquire experience with programming (preferably Python) and basics of linear algebra.

Job prospects. Graduates can work as researchers or programmers in the field of AI security, conduct AI-assisted data analysis, automate data analysis processes, or ensure AI systems security.

How to apply

Exams aren’t the only way to enroll in these Master’s programs – tuition-free studies are available to successful participants of various entrance competitions, including the ones held by ITMO University.

Here are the key options:

• Become a winner or runner-up of the I Am a Professional national contest.
• Become a winner or runner-up of ITMO’s Mega Contest.
• Win ITMO’s Mega School.
• Win ITMO’s Portfolio Contest.
• Present a letter of recommendation from the head of your chosen program.
• Win the report contest at ITMO’s Congress of Young Scientists.
• Win the project contest AI Technologies or any other program-specific competition.

Each individual Master’s program has its own enrollment opportunities – for instance, the Junior ML Contest, Roboforce, the Winter School in Robotics, SCAMT Workshop Week, the Datacon workshop, and others.

Learn more about enrollment opportunities for international students here.