Data Science

General description
A successful graduate of this educational track will

  • Mathematical and algorithmic foundations of Data Science
  • Statements of all major data analysis problems as well as the main approaches to solve them
  • Most important techniques of data analysis and related areas.
  • Main methodological aspects of both, scientific research in Data Science and development of Data Science applications in industry

Be able to

  • Frame real-world tasks as data analysis problems.
  • Choose the most appropriate approach to a particular data analysis problem.
  • Put modern data analysis software tools to use in practice.
  • Develop new methods or adapt existing ones to a particular problem.
  • Implement data analysis algorithms as computer programs.
  • Evaluate the results of data analysis process.
  • Effectively work with technical literature.
  • Clearly and accurately present the results to different audiences in oral and written form.

Other core aspects of the program are the industry immersion and Entrepreneurship&Innovation components. All courses are taught in English. Skoltech offers a highly vibrant international education & research environment and a number of opportunities for students to visit foreign universities and international conferences.

Core courses of the Program

  • Mathematics for Data Science
  • Numerical Linear Algebra
  • Optimization methods
  • Machine Learning
  • High-Dimensional Statistical Methods

Click to see Skoltech Course Catalogue

Entrepreneurship and Innovation component
It includes two courses, one of which is the Innovation Workshop – a trademark Skoltech course introducing newly enrolled students to the culture of entrepreneurship and technological innovation.

Industry internship
8-week full-time internship in one of Russian or foreign companies.

Elective courses and individual research projects
You choose elective courses that fit best your career plans.

Master thesis

Master thesis is the central part of the program. Skoltech Faculty & Research staff members offering Master projects in Data Science are: Mikhail Belyaev, Evgeny Burnaev, Mikhail Chertkov, Maxim Fedorov, Grigory Kabatianski, Stamatios Lefkimmatis, Viktor Lempitsky, Ivan Oseledets, Maxim Panov, Athanasios Polymeridis, Alexander Shapeev, Vladimir Spokoiny, Dzmitry Tsetserukou, Dmitry Yarotsky, Alexey Zaytsev and Andrii Zhugayevich.

They are affiliated with the Center for Computational Data-Intensive Science and Engineering as well as with other CREIs.

The program is accredited in the framework of the educational standard of Russian Federation 09.04.01 Computer Science and Engineering.
Students also have opportunity to enroll into the double-degree program with Moscow Institute of Physics and Technology.