Master in Big Data Analytics & Artificial Intelligence


Program Description

The innovative project-oriented training in Data Science led by the minds that envision and hands that shape the future of Big Data World. Your diploma will read Master of Science. Only because our "Wizard" degree is not yet official.

Program goal

True Data Scientist solves the problem by combining the hardcore science and breakthrough data mining technologies with the inexplicable art of human understanding. As a student you will take part in real projects, working with the team through all the project stages to acquire deep knowledge and master your skills in analyzing the core problems of your customer, planning and managing project resources, engineering software, collecting and processing all sorts of data, and discovering the precious insights that put the whole data puzzle together.


Benefits of the program Big Data Analytics & Artificial Intelligence

  • Research opportunities in real world-class science. You will learn not only how to apply data science and machine learning methods, but will have an opportunity to develop new or upgrade existing ones, for example improvement training procedure of state of-the-art neural network

  • Project based and practical-oriented learning. You will gain experience in projects with real tasks from our partners. Program is designed so that you are involved in all stages of Data Science and Machine Learning project development and implementation cycle beginning with understanding of business needs, trough detailed project planning and management, ending up with implementation of new product or technology.

  • PhD opportunities. This program also opens up possibilities for a PhD in NSU and the world's leading universities.

  • Wide range of hot domains. You will have an opportunity to apply your data science and machine learning skills in leading scientific and industrial domains such as Oil and Gas, Healthcare, Social networks, Cognitive data science, Telecommunications, Instrumentation.

  • Hackathons and data science competitions with tricky and unsolved tasks. You will have an opportunity to participate or to manage hackathons held by Big Data Analytics & Artificial Intelligence master program and our partners.

Duration of study

2 years

Language of instruction



First year, Fall Semester

Core courses

  • Business Analysis
  • Python programming language
  • Introduction to machine learning
  • Frontiers of Big Data Analysis and Artificial Intelligence
  • Methods of Operations Research
  • Information Theory and Cryptography
  • Philosophy of Artificial Intelligence
  • Project Seminar
  • Scientific Seminar
  • Internship

Optional courses

  • Russian for foreigners

First year, Spring Semester

Core courses

  • Machine Learning
  • Frontiers of Big Data Analysis and Artificial Intelligence
  • Storage Technologies
  • Project Management
  • Scientific Seminar
  • Natural Language Processing
  • Internship
  • Research work

Elective courses

  • Deep Learning
  • Formal Semantics

Optional courses

  • Russian for foreigners

Second year, Fall Semester

Core courses

  • Digital Image Processing
  • Distributed Computing Systems
  • Technology Entrepreneurship
  • Project Management Practice
  • Scientific Seminar
  • Internship
  • Research work
  • Academic writing (English)

Elective courses

  • Social Mining
  • Biomedical Engineering

Second year, Spring Semester

  • Research work
  • Pre-graduation practice
  • Scientific Seminar
  • Thesis defense

Master dissertation

Example subjects to work on:

  • Development of a system for predicting blood sugar levels based on machine learning
  • Developing a subsystem for retrieving event data.
  • Development of a module of an expert system for analysis and monitoring of communications, solving the subscriber's identification problem
  • Developing Big Data platform for cognitive analysis
  • The application of the principle of rival similarity search for significant features in the processing of large amounts of data (Big Data)

Training base

  • Oil and gas – oil products price prediction, well production optimization, health-safety environment. Companies: Digital Field technologies, Gazpromneft.

  • Healthcare – medical experiment data processing; real-time patient data processing for alarming and prevention of risks, analytic modules for healthcare information systems. Organizations: Novosibirsk Research Institute of Circulation Pathology, Novosibirsk Research Institute of Traumatology and Orthopedics, Institute of fundamental medicine and physiology SB RAMS, Federal Neurosurgery center.

  • Social networks – Identifying social event preparation by social network activity, A/B testing, semantic analysis, sentiment analysis, reputation management systems Companies: Game Banners Network (game development), Singularity.NET, Aigents Group.

  • Cognitive data science – development quantum FRiS methodology of cognitive data mining. Organizations: Sobolev Institute of Mathematics (scientific), Stream Data Analytics and Machine Learning lab.

  • Telecommunications – network traffic analysis, advertisement targeting, mobile marketing. Companies: Eltex LLC (business), Eyeline Communications CIS (business), Huawei.

  • Instrumentation – analyzing data from CERN, software for new electronic equipment. Organizations: Budker Institute of Nuclear Physics (scientific), Uniscan, LLC (business, instrumentation), TION (air purification).


  • Evgeniy Pavlovskiy, PhD in Math, certified EMC Data Science Associate.
  • Yuri Anikin, PhD in Tech, Deputy academic secretary of Siberian Branch of RAS
  • Ivan Bondarenko, Researcher at Neural Networks and Deep Learning Lab, MIPT, Solution Architect at DataMonsters, Neural networks for Natural language processing lecturer.
  • Denis Bondarenko, Chief Technology Officer at IMTS.Pro, Storage Technology courses lecturer
  • Alexander Savostyanov, PhD in Biology, PhD in Philosophy, Senior Researcher at Research Institute of Physiology.
  • Grigoriy Khazankin, Certified CCNA, leading engineer at Research Institute of Physiology, Distributed Computing Systems and Biomedical Engineering course lecturer.
  • Stukachev Alexey, PhD in Math, Senior Researcher at Sobolev Institute of Mathematics, Formal Semantics course lecturer (Natural language processing)
  • Florian Gouret, Researcher in Novosibirsk State University Formal Semantics course lecturer (Natural language processing)
  • Valeria Idrisova, PhD in Math, Engineer-researcher at Sobolev Institute of Mathematics.
  • Vyacheslav Mukhortov, Project Management course lecturer, director of Inteks LLC.


Fees and Financial support

$5200 per year

Every year foreign students have an opportunity to apply for the Russian Government Scholarship which covers full tuition and a monthly allowance. Travel costs, living expenses, and health insurance policy are not included. The Scholarships are granted on a competitive basis. Selection criteria and procedure, as well as the number of scholarships, depend on the country of the applicant. The application procedure starts in January. Deadline depends on the country of the applicant (March-June).

For further information, follow the link

Career opportunities

There are several possibilities: to work for University, Research Institutes of Russian Academy of Sciences, or to work for IT-business, such as our companies ExpaSoft, UniPro, Inteks, Parallels and so on. All our students have a part-time work in IT-company during the tuition period. In addition, you can find that many of our alumni work for Yandex, Google, Microsoft, Parallels, and Intel.

How to apply

Entrance requirements

For both foreign students and graduates of the Russian higher education institutions (including bachelor graduates of NSU):

  • Educational diploma (certificate or analogous document) on a program of the level of bachelor degree or of a specialist qualification of any specialization;
  • Strong motivation to be Data Scientist;
  • Proved background and strong knowledge of statistics and programming.

Application procedure and deadlines

Until June, 15 to fill out the application form on our website and provide with the following documents:

  1. Application for admission to the master program.
  2. Diploma (or some analogous document) on a program of the level of a bachelor degree or certificate (ordering) about passing now such program.
  3. TOEFL certificate (score 50-70: intermediate or upper intermediate level) or other international certificates (BEC etc.) of similar level.
  4. Curriculum Vitae of the applicant.
  5. Motivational letter (1-2 pages) on entrance to the Program.
Last updated Mar 2019

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About the School

Novosibirsk state university (Russia), located in the heart of Akademgorodok, is a world-famous research center of Siberian Branch of the Russian Academy of Sciences. Results of the research conducted ... Read More

Novosibirsk state university (Russia), located in the heart of Akademgorodok, is a world-famous research center of Siberian Branch of the Russian Academy of Sciences. Results of the research conducted by the university staff in the fields of nuclear physics, particle physics, biotechnology, the creation of nano-materials, laser systems of new generation, innovative methods of cancer treatment, are known all over the world. Read less