Statistical Learning Theory

Master of Science Program

Skoltech CDISE  Higher School of Economics SLT

MSc program Statistical Learning Theory is conducted jointly with Higher School of Economics. This program stands at the crossroads of various disciplines of modern mathematics and computer science, including statistics, optimization, learning theory, information theory, complexity theory, as well as at the intersection of science and innovation in the field of modern information technology. Leading experts at HSE and Skoltech jointly provide instruction in this unique research-driven program.

Key information


 

Program starts
September 2018
   
Modes and duration
Full time:
2 years
Tuition fees
No tuition fee
 for the applicants who pass the selection process
Application dates
All applicants:

General submission open: October 16, 2017

Awarded degree
Master of Science in Mathematics and Computer Science
Language of instruction
English
 Accreditation
Program is accredited by the Russian Government, certificate №2568 from April 14, 2017. License № 2534 from February 7, 2017.

Entry requirements
Successful candidates must know:

  1. Calculus
  2. Differential equations
  3. Linear algebra
  4. Basic probability, random processes and mathematical statistics
  5. Discrete mathematics (including graph theory and basic algorithms)
  6. 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.

Degree information


Overview
This program stands at the crossroads of various disciplines of modern mathematics and computer science, including statistics, optimization, learning theory, information theory, complexity theory, as well as at the intersection of science and innovation in the field of modern information technology.

Students participate in one or more working groups (research seminars), where they determine focus areas for an initial survey report and then solve challenges at the intersection of cutting-edge research and technology in statistical learning theory. These seminars are built on teamwork, as the tasks undertaken are so complex that they can’t be solved by one person alone. Students learn how to effectively collaborate, bringing together their diverse collective skills, competencies, and experiences to determine successful solutions for complicated issues.

Aims and objectives
The program aims at preparing researchers in the most dynamic and high-demand fields related to mathematics and computer science.

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.).

Graduates are expected to poses a combination of deep mathematical background and practical skills (software, algorithms, tools, etc).

Careers


 

Career opportunities and paths
Graduates of the MSc program may pursue a practical or research-oriented career, both of which are popular in one of the following areas:

- carrying out analysis in industry, consultancy, various types of associations and foundations, government agencies, banks, investment funds, etc.;
– expert activities related to methodological development, probabilistic modeling, statistical estimates, transport planning, optimization and forecasting tasks, as well as coming up with efficient methods, control technologies and data analysis in a variety of professional specializations;
– providing technical support for analytical and consulting groups engaged in machine learning, engineering design, financial analysis, modeling and optimization of transport networks;
– participating in management teams of analytical, research and administrative departments.

The program prepares specialists for the following positions:

  1. PhD positions in academic & research institutions
  2. Specialist positions such as Data Analyst, Data Scientist, Consultant in various economy sectors:
  • Finance
  • TeleCom
  • IT
  • Skolkovo resident companies and startups

Faculty

Program courses are taught by leading Skoltech experts, including such renowned scholars as Dr. Vladimir Spokoiny, Dr. Ivan Oseledets, Dr. Viktor Lempitsky, Dr. Evgeny Burnaev, Dr. Alexey Naumov and Dr. Yury Maximov.

From HSE lectures are delivered by prominent professors including Dr. Yurii Nesterov, Dr. Denis Belomestny, Dr. Dmitry Vetrov, Dr. Andrei Sobolevski, and Dr. Quentin Paris.

Research
Students are actively involved into research activity starting from Term 3.

Main research areas:

  • Machine Learning 
  • High-dimensional statistics and Statistical learning
  • Large-scale optimization
  • Financial mathematics

 

Apply now!