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Data Science

4.7
7 opinions
  • Extreme
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Master

In Moscow (Russia)

£ 401 VAT inc.

*Indicative price

Original amount in RUR:

40,000

Description

  • Typology

    Master

  • Location

    Moscow (Russia)

  • Duration

    2 Years

  • Start

    Different dates available

Description

Data scientists are going to be among the most demanded specialists in the hi-tech market. The purpose of our program is to meet this demand and 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.

Facilities

Location

Starts

Moscow (Russia)
See map
Bolshoy boulevard 30/1, 121205

Starts

Different dates availableNow taking bookings

To take into account

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 job placement. A successful graduate of the program will know: Mathematical and algorithmic foundations of Data Science Main methodological aspects of both, scientific research and application development in Data Science State of the art techniques of machine learning and related areas

Our graduates shape their own futures by choosing from a variety of career opportunities in industry, science and business: Industry Landing specialist positions such as Data Analyst, Data Scientist, Industrial Research Scientist, Consultant in various industry sectors (IT, Finance, Telecom and others). Science Landing PhD positions and continuing research at leading Russian and international research bodies. Startup Starting a business on their own or through the Skolkovo innovation ecosystem with its extensive pool of experts, consultants and investors.

Calculus, Differential Equations, Linear algebra, Probability theory and mathematical statistics, Discrete mathematics (including graph theory and basic algorithms), Programming. IT related bachelor's degree, or its equivalent in Mathematics, Computer Science, Information and Communication Technology, Applied Physics or other technical areas. If your education has not been conducted in English, you will be expected to demonstrate evidence of an adequate level of English proficiency.

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Opinions

4.7
excellent
  • Extreme
    |
  • I registered
    |
  • Im not accepeted yet
    |
100%
4.9
excellent

Course rating

Recommended

Centre rating

Rushikesh Bagde

5.0
12/05/2020
About the course: Extreme
Would you recommend this course?: Yes

Rushikesh Bagde

5.0
10/04/2020
About the course: I registered
Would you recommend this course?: Yes

Gabriel Lara

5.0
20/03/2020
About the course: Im not accepeted yet
Would you recommend this course?: Yes

Student

4.0
28/12/2018
What I would highlight: The engineering and design school could organise better but the facilities for doing work and layout and rules are fair.
What could be improved: -
Would you recommend this course?: Yes

Mark Vinogradov

4.0
26/11/2018
What I would highlight: Skoltech offers a world-class professional education with incredible people at the faculty
What could be improved: Nothing to improve
Would you recommend this course?: Yes

Andrei Davydov

5.0
25/11/2018
What I would highlight: Before applying to Skoltech, I was very skeptical about this place. There were a lot of ads everywhere about it with shocking studying conditions like worthy stipend for each student, technically equipped study rooms and cozy kitchens. It seems as a miracle for everyone who studied in universities, established still in Soviet Union, with month stipends less than 50$ and furniture left a lot to be desired. I had talked with several professors of Skoltech to understand what this place exactly is and whether all I heard is true. After confirmation, I started to gather all necessary documents and prepare for exams. Finally, I was enrolled to Data Science as I wanted. This place has everything for developing highly-qualified specialists in different fields of sciences. The majority of teaching staff are leading researchers from different fields of technical sciences. In addition, there are enterpreunership courses, which are appealed to broaden students' horizons and show them ways for translating ideas to products. After two years I am able to say that choosing Skoltech was right decision for getting Master degree. I circumscribed the area that is interesting to me to work in. Probably it has already determined my future life.
What could be improved: Nothing to improve
Would you recommend this course?: Yes

Brandan Willcocks

5.0
23/09/2018
What I would highlight: I wanted a challenge so I choose Skoltech and I can't believe that I made it studying in the most promising university in the world in Moscow.
What could be improved: -
Would you recommend this course?: Yes
Reviews gathered by Emagister & iAgora

Subjects

  • Technology
  • Innovation
  • Entrepreneurship
  • Data analysis
    3

    3 students say they acquired this skill

  • Data Protection
    2

    2 students say they acquired this skill

  • Mathematics
    1

    1 students say they acquired this skill

  • Algebra
  • Maths
  • Digital Editing
  • Data Management
    1

    1 students say they acquired this skill

  • Image processing
  • Modelling
  • Applications
    1

    1 students say they acquired this skill

  • Machine Learning
    1

    1 students say they acquired this skill

  • Analytics
    2

    2 students say they acquired this skill

  • Process
    1

    1 students say they acquired this skill

  • Data science
    3

    3 students say they acquired this skill

  • Robotics
    1

    1 students say they acquired this skill

  • Digital Editing
  • Blockchain
  • Entrepreneurship
  • Machine Learining
    1

    1 students say they acquired this skill

  • Coding Theory
  • Biomedical Imaging
    1

    1 students say they acquired this skill

Teachers and trainers (1)

Faculty members Members

Faculty members Members

teachers and administrators

Course programme

Program structure:

The 2-year program comprises of 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.

Coursework (36 credits)
  • Introduction to Data Science
  • Efficient Algorithms and Data Structures
  • Numerical Linear Algebra
  • Machine Learning
  • Theoretical Methods of Deep Learning
  • Information and Coding Theory
  • Large-scale Optimization and Applications
  • Deep Learning
  • Bayesian Methods of Machine Learning
  • Matrix and Tensor Factorizations
  • Introduction to Artificial Intelligence
  • Computational Imaging
  • Digital Signal Processing
  • Introduction to Computer Vision
  • Introduction to Blockchain
  • Convex Optimization and Applications
  • Advanced Statistical Methods
  • Perception in Robotics
  • Biomedical Imaging and Analytics
  • Statistical Natural Language Processing
  • Geometrical Methods of Machine Learning
  • Introduction to Digital Agro
  • Omics Technologies
  • Uncertainty Quantification
  • Neural Natural Language Processing
  • Geometric Computer Vision
  • Foundations of Multiscale Modelling: Kinetics
  • Scientific Computing
  • Thermodynamics and Transport at Nanoscale
  • Numerical Modeling
  • High Performance Computing and Modern Architectures
  • Stochastic Methods in Mathematical Modelling
  • Machine Learning in Chemoinformatics
  • Soft Matter in Practice
  • Modern Methods of Data Analysis: Stochastic analysis (HSE course)
  • Methods of Multidimensional Statistics (HSE course)
  • Modern Algorithmic Optimization (HSE course)
  • Probabilistic Graphic Models (HSE course)
  • Elective from the HSE Catalog "MAGO-LEGO" (HSE course)
Elective courses (24 credits)

Entrepreneurship and Innovation (12 credits)

  • Innovation Workshop
  • Ideas to Impact: Foundations for Commercializing Technological Advances
  • Leadership for Innovators
  • Business Communication
  • Biomedical Innovation and Entrepreneurship
  • Intellectual Property and Technological Innovation
  • Technology Entrepreneurship: Foundation
  • Technology Entrepreneurship: Advanced
  • Product Innovation: User-Centered & Iterative Design Process
  • Technology Planning and Roadmapping: Foundation
  • Technology Planning and Roadmapping: Advanced
  • Technological Innovations: from Research Results to Commercial Product
Research and MSс Thesis Project (36 credits)

Industry Immersion (12 credits)

Call the centre

Data Science

£ 401 VAT inc.

*Indicative price

Original amount in RUR:

40,000