Master’s Degree Program “Data Science and Mathematical Modeling” | Siberian Federal University

Master’s Degree Program “Data Science and Mathematical Modeling”

The program is designed for students with a background in Mathematics, Physics, Natural Sciences, Computer Science or Engineering. The main goal is to train highly-skilled professionals in the field of Data Science and Mathematical Modeling.

The graduates of this program will be very competitive at the international labor market.

The aim

The program is aimed at providing students with fundamental data science education and developing strong mathematical, statistical, modeling and programming skills.

Objectives

The main objectives of the program are the following:

  • to provide students with advanced knowledge in the field of Mathematical Modeling, Analysis,
  • to emphasise the need of using cutting-edge technologies
  • to differentiate between modern programming techniques needed for working with data (such as preparation, pre-processing, processing, and analytics)
  • to solve data analysis problems in various applied fields;
  • to develop soft skills (systemic and critical thinking, teamwork skills, self-management, interaction skills).

To ensure the learning outcomes are achieved, we have brought together highly professional academic staff with good command of English language and experienced researches in the filed of applied data analysis.

Learning outcomes (knowledge, skills, competence)

We work in close cooperation with IT and Engineering enterprises, which provides our students with applied tasks and helps them to develop their project management, teamwork, and client interaction skills.

We use modern training techniques to increase the efficiency of the study, including:

  • interdisciplinary approach
  • case study
  • blended learning
  • teamwork projects
  • active involvement in research activity.

Our students regularly participate in the interdisciplinary Data Analytics seminar of Siberian Federal University.

Graduates of the Program will be able to

  • conduct business and academic communication effortlessly, understand comprehensive professional information sources;
  • formulate analysis tasks at customer request;
  • choose appropriate methods and software, develop machine learning solutions according to a particular client's needs
  • interact with professionals in this field
  • interpret and convey results to the target audience
  • categorize the mathematical foundations of data analysis
  • recognise the limitations on the applicability of various mathematical methods and will be able to assess the relevance of used models
  • conduct research and design cutting-edge data analytics and modeling solutions

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Duration 2 years
Starting date September, 1st
Study intensity Full-time
Delivery mode Blended
Type of degree M.Sc.
Credits 120 ECTS credits
Language of instruction English
Academic requirements
  • Bachelor's degree in Mathematics, Physics, Computer Science or equivalent (a copy of your diplomas from previous university studies and transcripts of completed courses and grades)
  • good command of English (certificate or other official document , English level B1 (European Framework of Reference of Communicative Skills)
  • Skype interview
  • a motivation letter and letters of recommendation may also be required
Tuition fee (per year) 250,000 rubles
The cost does not include accommodation and living expenses. The price could change at the time of signing a learning agreement.
Application deadline July 29th
Accommodation On-campus accommodation is available in double and triple-occupancy rooms (€ 20 per month)
Practicalities Airport transfer and invitation letter for a Russian study visa are provided by the University

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Alexey A. Kytmanov

Alexey A. Kytmanov

  • Ph.D. in Mathematics, D.Sc. in Applied Mathematics, Professor
  • Dean of the School of Space and Information Technology, Siberian Federal University

Tel: +7 391 291-25-75
E-mail: aakytmanov@sfu-kras.ru
CV: in English (.pdf)
Profiles: ResearchGate , Google Scholar, Math-Net.Ru
English: Proficiency (C2 level according to CEFR scale), CPE certificate awarded in 2019.

Alexey Kytmanov is the author and co-author of more than 20 scientific publications. Project leader and research associate in more than 15 national and international projects.

Research interests: Data Science, Computer Algebra, Computational Algebraic Geometry, Applied Computing, Data Analysis, Mathematics and Computer Science Education, Digital Transformation in Education.

Education and Academic Degrees

  • 2010 — Siberian Federal University, D.Sc. in Applied Mathematics.
  • 2002-2005 — Missouri University of Science and Technology, Ph.D. in Mathematics.
  • 2000-2003 — Krasnoyarsk State University, Ph.D. in Mathematics.
  • 1995-2000 — Moscow State University, M.Sc. in Mechanics and Applied Mathematics.

Awards

  • 2013 — Winner of the prize of Open JSC Joint Stock Commercial Bank International Financial Club.
  • 2013 — Winner of the prize of Open JSC Joint Stock Commercial Bank International Financial Club.
  • 2010-2011 — Winner of Vladimir Potanin Foundation contest for young teachers of public higher education institutions in Russia.
  • 2009-2010 — Winner of Vladimir Potanin Foundation contest "Teacher online".
  • 2009-2010 — Winner of Vladimir Potanin Foundation contest for young teachers of public higher education institutions in Russia.
  • 2009 — Winner of the Krasnoyarsk Territory state prize for doctoral students of higher education institutions.
  • 2008-2009 — Winner of Vladimir Potanin Foundation contest for young teachers of public higher education institutions in Russia.
  • 2007-2008 — Winner of Vladimir Potanin Foundation contest for young teachers of public higher education institutions in Russia.
  • 2004 — Outstanding graduate student award, Missouri University of Science and Technology.
  • 2002-2003 — President of Russian Federation Scholarship.

Supervision of Funded Projects

  • 2017-2018 — "Mathematical modeling of critical phenomena in kinetics of complex chemical reactions"', supported by the President of the Russian Federation grant MD-197.2017.1 for young researchers with D.~Sc. degree.
  • 2015-2016 — "Computer algebra in computationally hard related problems of complex algebraic geometry and several complex variables"', supported by the Russian Foundation for Basic Research grant 15-31-20008-mol\_a\_ved.
  • 2014-2016 — "Computer algebra algorithms in the problems of study of equations and systems of equations of different types", supported by the Russian Foundation for Basic Research grant 14-01-00283-a.
  • 2013-2016 — Local work group coordinator for the project "Applied Computing in Engineering and Science" (ACES), supported by EACEA grant 544609-TEMPUS-1-2013-1-AT-TEMPUS-JPCR.
  • 2012-2013 —"Theory of functions and toric geometry methods in the problems of systems of nonalgebraic equations research"', supported by the Russian Foundation for Basic Research grant 12-01-31021-mol\_a.
  • 2009-2012 — Local work group coordinator for the project "Modernization of Master Program NETWORKS\&COMMUNICATIONS" (MoNetCom), supported by EACEA grant 159386-TEMPUS-1-2009-1-DE-TEMPUS-JPCR.
  • 2007-2008 — "Integral representations, residues, holomorphic extension and systems of nonlinear equations", supported by the President of the Russian Federation grant MK-914.2007.1 for young researchers with Ph.~D. degree.

Recent articles and papers in peer-reviewed journals

Tatiana Kustitskaya

Tatiana Kustitskaya
Current Position: Associate Professor of Applied Mathematics and Computer Safety Department
Research Interests: Data Analysis, Learning Analytics, Probability and Statistics, Risk theory
Education and Academic Degrees:

  • 2003–2006 Institute of Computational Modelling SB RAS, Krasnoyarsk, Ph.D. in Mathematics
  • 1998–2003 Krasnoyarsk State Technical University, Specialist in Applied Mathematics

Address: room 311, 26-1, Kirensky st., Krasnoyarsk, Russia
Phone: +7 (391) 291-27-90
E-mail: tkustitskaya@sfu-kras.ru
Google Scholar: scholar.google.com
Personal webpage: ikit.sfu-kras.ru
Profile on another site: researchgate.net
CV (.pdf)

Tatiana Yamskikh

Tatiana  Yamskikh
Current Position: Associate Professor, Head of Foreign Language Department
Research Interests: Methods of teaching English, Distance learning
Education and Academic Degrees:

  • 2004 — Buryat State University, Ulan-Ude (Russia), PhD in Pedagogy
  • 1994 — Krasnoyarsk State Pedagogical University, Krasnoyarsk (Russia), Teacher of English as a foreign language

Address: 26-1, Kirensky st, Krasnoyarsk., Russia
Phone: +7 (391) 249-72-91
E-mail address: TYamskikh@sfu-kras.ru
Google Scholar: scholar.google.com
Personal webpage: structure.sfu-kras.ru
Profile on another site: ikit.sfu-kras.ru
CV (.pdf)

Anna Kosheleva

Anna Kosheleva
Current Position: Associate Professor of Applied Mathematics and Computer Safety Department
Research Interests: Data Science, Mathematical Logic
Education and Academic Degrees:

  • 2003 — 2007 Krasnoyarsk State University, Ph.D. in Mathematics
  • 1998 — 2003 Krasnoyarsk State University, Specialist in Mathematics

Address: room 311, 26-1, Kirensky st., Krasnoyarsk, Russia
Phone: +7 (391) 291-27-90
E-mail address: akosheleva@sfu-kras.ru
Google Scholar: scholar.google.com
Personal webpage: structure.sfu-kras.ru
CV (.pdf)

Valeriy Loginov

Valeriy Loginov
Current Position: Professor of Mathematics, Physics and Informatics at School of Space and Information Technologies
Research Interests: Interests Statistical description of dynamical systems driven by stochastic actions. Development of mathematical tools for modeling of time series of natural objects. Analytic and computer calculations.
Education and Academic Degrees:

  • 1999 — Krasnoyarsk State Polytechnical University, D.Sc. in Physics and Mathematics
  • 1981 — L.V.Kirensky Institute of Physics SB RAS, PhD
  • 1966 — 1971 Krasnoyarsk State University

Address: 26-1, Kirensky st., Krasnoyarsk, Russia
Phone: +7 (391) 291-27-90
E-mail address: valog_1949@mail.ru
Personal webpage: ikit.sfu-kras.ru
Profile on another site: scholar.sfu-kras.ru
CV (.pdf)

Roman Esin

Roman Esin
Current Position: Associate Professor of Applied Mathematics and Computer Safety Department, School of Space and Information Technology
Research Interests: Data Analytics in Education, Statistical Data Processing, Adaptive Learning Systems, Individual Educational Trajectory
Education and Academic Degrees:

  • 2020 — Siberian Federal University, Technology and Engineering Teacher
  • 2019 — Siberian Federal University, Ph.D. in Education
  • 2018 — Siberian Federal University, Postgraduate (Research teacher) in Mathematical Modelling, Numerical Methods and Software
  • 2014 — Siberian Federal University, Specialist (Engineer) degree in Applied Mathematics

Address: room 311, 26-1, Kirensky st., Krasnoyarsk, Russia
Phone: +7 (391) 291-27-90
E-mail address: resin@sfu-kras.ru
Google Scholar: scholar.google.com
Personal webpage: structure.sfu-kras.ru

CV (.pdf)

Alexey Shmidt

Alexey Shmidt
Current Position: Associated Professor
Research Interests: Mathematical modelling, Turbulence
Education and Academic Degrees:

  • 2001 — Institute of Computational Modelling SB RAS, Ph.D. in Mathematics

Address: 79, Svobodny pr., Krasnoyarsk
Phone: +7 (391) 206-20-87
E-mail address: ashmidt@sfu-kras.ru
Google Scholar: scholar.google.com
Personal webpage: math.sfu-kras.ru
CV (.pdf)

Program structure

Study Plan MSc Data Science and Mathematical Modeling
Courses Exam / credit ECTS credits
First year
1st semester
Basics of Machine Learning exam 6
Data Storage and Management Systems credit 2
Mathematical Modeling exam 6
Numerical Linear Algebra exam 6
Foreign Language for Business and Professional Communication. Part 1 credit 3
elective: Python Language for Scientific Research credit 2
Field Internship I credit 4
2nd semester
Simulation Modeling exam 6
Numerical Analysis and Optimization exam 6
Foreign Language for Business and Professional Communication. Part 2 credit 3
Advanced Methods of Data Analysis exam 5
Bioinformatics Algorithms. Part 1 credit 3
elective: Julia Language for Scientific Research credit 2
Scientific Research I credit 5
Field Internship II credit 5
Second year
1st semester
Multi-Agent Systems exam 6
Statistical Modeling exam 6
Applied Data Analysis credit 4
Big Data credit 3
Bioinformatics Algorithms. Part 2 credit 3
Scientific Research II credit 4
Field Internship III credit 3
2nd semester
Field Internship IV credit 25
Final certification 6
TOTAL 124/120 without elective

More information?

Please contact our Department of International Educational Programs, SibFU

e-mail: study [at] sfu-kras [dot] ru
phone: +7 391 206-39-28
fax: +7 391 206-21-66
address: 82/6 Svobodny pr., room 427, Krasnoyarsk, 660041 Russia

Facebook: facebook.com/StudySibFU
Skype: StudyatSibFU
VKontakte: vk.com/international_education_sibfu

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The University

Today Siberian Federal University (SibFU) with over 35,000 students enrolled in its programmes is one of the most actively developing universities in Russia. Annually more than 200 visiting professors — leading scientists from UK, Germany, Spain and USA — deliver their lectures at SibFU.

The University is a winner of the Russian Government grants supporting research projects under the guidance of top-level scholars from Russia and all over the world.

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The campus of Siberian Federal University is located in a forested area of the city of Krasnoyarsk. Academic buildings and dormitories of the university are surrounded by natural forest lands and easily accessible by the public transport. More information about the University Campus can be found here.

The City of Krasnoyarsk

Krasnoyarsk is the administrative capital of Krasnoyarsky kray — second largest region of Russia. It is a big industrial and educational centre with a population of more than 1 million people, and also an important junction of the Trans-Siberian Railway.

The city is located on the banks of the Yenisey River in the valley formed by the Eastern Sayan Mountains. Nature reserve Stolby ("pillars") has become the city’s visiting card.

Among the famous people born in Krasnoyarsk are artist Vasily Surikov, opera singer Dmitri Hvorostovsky, biathlete Evgeny Ustyugov, skeletonist Alexander Tretyakov and ice-hockey player Alexander Semin.

In March 2019 Krasnoyarsk proudly hosted the XXIX Winter Universiade.

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