Master of Science in Data Science

Machine learning techniques are at the forefront of modern data science and, therefore, courses on different aspects of machine learning constitute an integral component of the program. The application component of the program includes several important topics such as:

• Computer vision
• Industrial data analytics
• Natural language processing
• Image and signal processing

The main scope of the data science 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. Students will learn how to develop automated methods to analyze massive amounts of data with the goal of extracting knowledge from them to create an impact on organizational decisions. The graduates of the program are trained to perform original research in their chosen area of machine learning and data analytics and apply the results of their research in an industrial context.

The MSc program is 2 years long: the first year is to strengthen your theoretical background, and the second year is to focus on research. Students have the freedom to choose courses and extracurricular activities to shape their individual trajectory, acquire soft skills, and gain entrepreneurial skills to prepare for employment.

A successful graduate of the program will know:

• Mathematical and algorithmic foundations of data science, and a balanced vision on mathematical foundations and practical tools and applied problems in data science;
• Statements of all major data analysis problems as well as the main approaches to solve them;
• State-of-the-art techniques of data analysis and related areas. Knowledge of main classes of applied problems;
• Main methodological aspects of both scientific research and application development in data science.

A successful graduate of the program will be able to:

• Formulate/model real-world tasks like data analysis problems;
• Choose the most appropriate method to solve a particular data analysis problem;
• Apply data analysis methods in practice using modern data analysis software tools;
• Develop new methods or adapt existing methods to a particular problem;
• Implement algorithms as computer programs;
• Evaluate results of data analysis processes;
• Work with technical literature (e.g. conduct bibliographical research, read and critically analyze scientific articles, use scientific metrics and important databases);
• Present results to different audiences (specialists, users, stakeholders, etc.) in an effective oral and written manner.

Aim and objectives

The aim of the program is to prepare the technological leaders of the future. The objective of the Data Science MSc program is to bridge the gap between fundamental science and cutting-edge computational techniques.

Machine Learning and Artificial Intelligence (MLAI) Track

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

Math of Machine Learning (MML) Track
(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

©The Skolkovo Institute of Science and Technology (Skoltech)

Content

The curriculum of the program contains a balanced combination of topics developed very recently (e.g. deep learning) together with in-depth teaching of mathematical foundations (advanced linear algebra, optimization, high-dimensional statistics, etc.).

Program structure

The 2-year program comprises compulsory and recommended elective courses on the most important topics, a wide set of elective courses (depending on the research and professional needs of the student), components of entrepreneurship and innovation, research activity, and 8 weeks of industry immersion.

Research

Students are actively involved in research activities starting from Term 3.

Main research areas:

• Machine Learning and Deep Learning
• Industrial Analytics
• Computer Vision
• Image Processing
• High-dimensional statistics and Statistical learning
• Next Generation Multi-scale Modeling
• Fast Solvers for Large Scale/High-Dimensional Problems

Career opportunities and paths

The Data Science MSc program was developed to meet the high demand for data science specialists in the growing national and international high-tech market. Graduates of the program may begin an international research career or work with a company (even during the period of study).

Data science MSc graduates significantly enhance their employability by developing their subject-specific knowledge in the field of data science and machine learning, as well as their analytical and research skills. Students gain the opportunity to obtain early access to the national and international research and innovation landscapes and can approach international employers with confidence. In addition, the program enhances students’ soft skills, enabling them to compete effectively in the job market.

• Ph.D. positions in academic & research institutions
• Specialist positions such as data analyst, data scientist, consultant in various economic sectors:
  • Finance
  • TeleCom
  • IT
  • Skolkovo resident companies and startups

Entry requirements

IT-related Bachelor’s degree, or its equivalent in mathematics, computer science, information and communication technology, applied physics, or other technical areas.

• Calculus
• Differential equations
• Linear algebra
• Basic probability, random processes and mathematical statistics
• Discrete mathematics (including graph theory and basic algorithms)
• Programming

English language requirements:

If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

Application requirements

The online application​ makes the process easier for potential students. We advise you carefully read the application instructions, requirements, and deadlines for the chosen academic program.

The application includes the following documents: a CV, two letters of recommendation, a TOEFL/IELTS score report, and a motivation letter. Applicants who do not have proof of English proficiency may take the TOEFL ITP during a Selection Weekend at Skoltech.

Selection process

1. Prepare your portfolio
   Prepare your competitive selection application materials.
2. Submit your application
   Upload your materials into the application system and submit your application.
3. Online testing
   Every candidate must take an online profile test. You will be notified by email about the specific date and time of your test.
4. In-person interviews (online)
   The final selection stage takes place in Moscow. You have to pass the TOEFL ITP exam on-site, or present a valid TOEFL certificate and pass an in-person interview. Extra written examinations may be required for certain programs during this time (you will be notified in advance).

©The Skolkovo Institute of Science and Technology (Skoltech)

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."