DATA
SCIENCE
Master of Science in Mathematics and Computer Science
Format and duration:
2 years, full-time
Language of instruction:
English
Scholarship:
student scholarship from
40 000 RUR/month,
no tuition fees
Apply:
applications for Fall 2021 start are closed
Data scientists are already among the most demanded specialists in the hi-tech market. Business, energy, government, healthcare, intelligence and security, logistics and other industries are waiting for professionals in data science. All jobs are changing because of data. In five years, it's going to be very
hard to find a job without any knowledge of data science. And, since the application for data science
is very broad, you can find a field that sparks your
own personal interest. The choice to become a data scientist is a choice for job security.
Skoltech's (TOP-100 Young Universities 2019 Nature Index) Master's program in Data Science goal is to equip the most talented young scientists with high-level knowledge and experience in machine learning, deep learning, computer vision, industrial data analytics, natural language processing, mathematical modelling and other important areas of modern data science. The main scope of the program is to train students in using state-of-the-art techniques of machine learning and data analytics, with a focus on real-world applications of these emerging technologies.
SKOLTECH 365
Everything you need to know about Skoltech in one short video
Why data science?
$103 bln
is the estimated growth of the global big data market by 2027
75%
of organizations will shift from piloting to operationalizing or deploying artificial intelligence by 2024
250 000
professionals shortage of the data science industry in 2020
1,7 MB
in just a second generated every person in 2020
11,5 mln
jobs in data science is predicted to be created by 2026
Data Science is a versatile field with interesting challenges for:
/data scientists/
/machine learning engineers/
/data engineers/
/data architects/
/big data analysts/
/data visualization developer/
/computer vision engineers/
/consultants/
/policy advisors/
/R&D managers/
  • Consult businesses and government
Why earn your
Master's at Skoltech?
Skoltech is an international English-speaking STEM university ranked as one of the top 100 Young Universities in the Nature Index.
Research-based teaching
Study with world-renowned award winning professors. All Skoltech faculty and academic staff are engaged in internationally recognized scientific research across a wide range of topics. We incorporate findings from this research into teaching
Globally renowned
faculty
Teaching staff are the acting research professors who implement advanced technology projects with leading companies in the field.
Top-class
Facilities and Courses
Unique facilities for state of the art research in data science.
International study & Industrial experience
All courses are taught in English. Top students are granted internships for international studies (up to 6 months). The majority of students' projects are in collaboration with industry partners
Partnerships
Close partnerships with major academic and industrial leaders in IT, finance, telecom and other areas
Career
Program graduates work in industry and research institutes. Alternative option is undertaking the research degrees (PhD) in Russia (Skoltech) or overseas
Laboratories
Students of the Materials Science program conduct their research using some of the most advanced laboratory equipment and facilities
Partners
Skoltech has strongly established connections with leading companies in the industry and academia
Industrial partners
Academic & research partners
Degree structure and components
choose courses, design your individual study plan, discover opportunities to visit world-leading universities and international conferences, explore the integration of research, education and innovation
1
Lectures and seminars
Free choice of disciplines. Courses are developed by professors who have worked in the best universities in the world
2
Research
Independent research work on your own project based on Skoltech laboratories
3
Enterpreneurship
Courses in innovation and entrepreneurship, providing knowledge and skills for the commercialization of scientific research
4
Internship
8-week internship at one of the leading companies in the industry
2 years of master's studies are equivalent to 120 ECTS credits. They are awarded for the courses taken, but also for research work, disciplines in entrepreneurship and innovation, and an internship in the industry.
Curriculum
Track A:
Machine Learning and Artificial Intelligence (MLAI)
Machine learning techniques are at the forefront of modern data science and artificial intelligence. The curriculum of the program contains a balanced combination of topics developed very recently together with in-depth teaching of mathematical foundations, such as advanced linear algebra, optimization, high-dimensional statistics, etc.

This track is also available in network form with the Moscow Institute of Physics and Technology.

A successful graduate of this track will be able to:
  • understand and formulate complex real-world tasks as data analysis problems
  • contribute to the development of the next-generation machine learning software competitive with or superior to the existing examples of software in critical and emerging application fields
  • apply relevant software tools, algorithms, data models, and computational environments for the solution of real-world problems

Compulsory courses:
  • Numerical Linear Algebra
  • Machine Learning
  • Deep Learning
Recommended electives:
  • Introduction to Data Science
  • Introduction to Artificial Intelligence
  • Computational Imaging
  • Foundations of Software Engineering
  • Efficient Algorithms and Data Structures
  • Theoretical Methods of Deep Learning
  • Convex Optimization and Applications
  • Introduction to Computer Vision
  • Statistical Natural Language Processing
  • Principles of Applied Statistics
  • Perception in Robotics
  • Introduction to Digital Agro
  • Advanced Statistical Methods
  • Statistical Learning Theory
  • Geometric Computer Vision
  • Biomedical Imaging and Analytics
  • Geometrical Methods of Machine Learning
  • Neural Natural Language Processing
  • Planning Algorithms in Artificial Intelligence
  • Bayesian Methods of Machine Learning
  • Matrix and Tensor Factorizations
  • Neuroimaging and Machine Learning for Biomedicine
  • Reinforcement Learning
  • Models of Sequential Data
  • More recommended courses in the Skoltech Course Catalog>>
Entrepreneurship and Innovation:
  • Leadership for Innovators
  • Hack Lab: Laboratory for Ideas
  • Startup Workshop
  • Ideas to Impact: Foundations for Commercializing Technological Advances
  • Intellectual Property, Technological Innovation and Entrepreneurship
  • Technological Innovations: from Research Results to a Commercial Product
  • Developing Products and Services through Design Thinking
  • More courses in the Skoltech Course catalog>>
      Track B:
      Math of Machine Learning (MML)
      (in network form with Higher School of Economics)
      Modern Machine Learning is at the cutting edge of various disciplines of mathematics and computer science. Math of Machine Learning is one of the most dynamic areas of modern science, encompassing mathematical statistics, machine learning, optimization, and information and complexity theory. From the start of the program, students collaborate in thematic working groups and actively participate in research, learning from Skoltech and Higher School of Economics scientists as well as leading global specialists in statistics, optimization and machine learning.

      A successful graduate of this track will:
      • possess active knowledge of modern methods and approaches in statistical learning, including mathematical statistics, stochastic processes, convex optimization
      • be able to apply and further develop such methods for solving complex practically motivated problems of data analysis
      Compulsory courses:
      • Numerical Linear Algebra
      • Machine Learning
      • Deep Learning
      Recommended electives:
      Entrepreneurship and Innovation:
      • Leadership for Innovators
      • Hack Lab: Laboratory for Ideas
      • Startup Workshop
      • Ideas to Impact: Foundations for Commercializing Technological Advances
      • Intellectual Property, Technological Innovation and Entrepreneurship
      • Technological Innovations: from Research Results to a Commercial Product
      • Developing Products and Services through Design Thinking
      • More courses in the Skoltech Course catalog>>
      Main research areas
      • Industrial Analytics
      • Machine Learning
      • Deep Learning
      • Computational Imaging & Graphics
      • Computer Vision
      • Robotics
      • Computational Intelligence
      • Digital Agriculture
      • FinTech
      • Natural Language Processing
      • Reinforcement Learning
      Research groups
            What our students say
            Julia Molchanova
            BSc, Moscow State University → MSc, Skoltech → Indie Game Developer
            Skoltech's Data Science program provides an opportunity to learn almost all the necessary skills for an academic or industrial career in machine learning. While I'd been studying the same topic previously, at Skoltech I became proficient in the required disciplines. Also, the university's language policy has boosted my English significantly. Broader-discipline activities, such as Innovation Workshop, actually can lead to some unexpected outcomes. I've tried so many different things during these lessons and developed a liking for some of them. They are a great way to acquire unique knowledge and get a different life perspective.
            Alfredo De La Fuente
            BSc, Universidad Nacional de Ingenieria → MSc, Skoltech → Schlumberger Software Technology Innovation Center
            I cannot help but smile as I remember my crazily productive period during Skoltech's Master's program in Data Science. Adapting to a drastic change of atmosphere (moving from Peru and a different academic background) was certainly a tough challenge. However, the impact this program had in my career, the amazing friendships acquired and the exposure to numerous opportunities, made it worth it. Overall, the whole coursework of the Data Science program provided me confidence and a wide range of skills to tackle Machine Learning projects both from an industrial and research perspective. Undoubtedly, one of the best choices of my life.
            Elena Orlova
            BSc, Higher School of Economics → MSc, Skoltech → PhD, University of Chicago
            The Master's program in Data Science at Skoltech allows students to gain all the necessary knowledge both academically and in industry. Students have a unique opportunity to work with famous professors, access high-performance computing resources, and as far as I know, there are cool laboratories at Skoltech. The study is quite stressful, but always interesting, and definitely worth all the effort. It was easier for me because I already had a similar background. The decision to study at Skoltech was definitely the right one. After all, it is also an opportunity to meet many interesting people from all over the world. I remember with warmth the time when I studied there. NLA, ML and DL courses and, of course, innovation workshop. If you are thinking about whether to try to enroll here - the answer is definitely yes. At least, you should try. After completing your Master's degree here, you will be able to continue in the industry or build an academic career.
            Andrei Davydov
            MSc, Skoltech → Huawei
            When I first heard about Skoltech, I was skeptical: students who studied at traditional Russian universities may not believe in the possibility of a high scholarship and innovative facilities and labs. After 2 years of studying here, I can confidently say that my decision to apply to the Data Science Master's program was right. Skoltech has everything to turn students into professionals of their fields, and the faculty is comprised of the leading instructors from all over the world.
            Mahmud Allahverdiyev
            BSc, Qafqaz University → MSc, Skoltech → Snowflake (The Data Cloud)
            Pursuing a master's degree at Skoltech boosted my knowledge in the area of High-Performance Computing and opened new doors for my future career. Already, at the end of the first year of my studies, I got an internship offer from a giant German tech company for summer industrial immersion. While having continuous support and guidance from the Skoltech side, I did my master's thesis work at the same company as well. All these experiences not only expanded my academic surrounding but also let me land a full-time position at a Tech Unicorn. Right now, I'm feeling happy for coming to Skoltech and especially, for taking great courses related to Scientific and High-Performance Computing.
            Mohammad Ali Sadri
            BSc, National University of Iran → MSc, Skoltech
            As a graduate student in the Data Science program at Skoltech, I would like to mention some pros and cons of studying Data Science here. Firstly, there are so many well-known and highly professional professors in this department. Secondly, industrial partners are coupled with Skoltech very well for research on cutting-edge technologies and, they are always looking for collaboration or cooperation with them. Finally, with such an incredible high-tech equipped campus and multinational friendly environment, you feel comfortable. As you can see, there are so many opportunities in studying Data Science at Skoltech, and I am very grateful for such an opportunity I had in my life. I almost forgot to talk about the disadvantages of studying Data Science at Skoltech. I could not find any.
            Alexandr Rubashevskii
            BSc, Moscow Institute of Physics and Technology → MSc, Skoltech → PhD, Skoltech
            I remember several things from Skoltech Master's program. Speaking about specific courses, I liked Ivan Oseledets' course on linear algebra and Evgeny Burnaev's course on machine learning. They had a huge emphasis on practice, so taking these courses helped a lot for the successful writing of a thesis and a deeper understanding of the subject area. At Skoltech, I also remember working with my scientific advisor Dmitry Dylov. We developed a project on the detection and adjustment of the forearm vein mask in the near-infrared light domain. As a result, we even published a conference paper about this study. I think this experience pushed me to further my PhD.
            Also, I have pleasant impressions from the summer industrial practice. I interned at Nvidia and worked on the detection of text blocks in screenshots of game images to create an automated testing bot. I gained valuable knowledge about imaging and deep learning in real-world tasks, as well as simply experienced the industry and understanding the internal processes of companies. This experience can be useful both in future work in the industry and in academic activities.
            Faculty
            enjoy courses and mentorship from world-renowned scientists and engineers
            Instructors at HSE University
            Admissions
            the admission and enrollment process includes several steps
            Admission requirements
            Knowledge and skills:
            If your education has not been conducted in English, you will be expected to demonstrate evidence of an adequate level of English proficiency.

            Education:
            • Bachelor's degree, or its equivalent
              in Physics, Chemistry, or Materials Science.
            Application requirements
            • Resume or CV
            • Motivation letter
            • 2 Letters of recommendation
            • Diploma or current transcript
            • English language certificate (TOEFL, IELTS), if any
            • Other relevant documents: awards, certifications, achievements
            Sample entrance exams
            1
            Prepare your portfolio
            Prepare your application materials.
            2
            Submit application
            Upload your materials into the application system and submit your application.
            3
            Online testing
            Every candidate must take an online subject test. You will be notified by email about the specific date and time of your test.
            4
            Interviews (online)
            The final admissions stage will take place online this year. You will need to pass an interview with the admissions committee, participate in an entrepreneurship challenge and take an English language test.
            Application
            The application period for Skoltech Master's programs for the 2021-2022 academic year is now closed. Subscribe below to receive a notification as soon as the application opens in the Fall.
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            Contact
            e-mail: admissions@skoltech.ru
            phone: +7 (495) 280-1481_ext.3387
            address: 30с1 Bolshoi boulevard, Skolkovo, 121205, Russian Federation, Room E-R3-2030