MSc in Mathematics and Computer Science
Skolkovo Institute of Science and Technology

Data Science

4.5 ausgezeichnet 4 Meinungen
Skolkovo Institute of Science and Technology
In Moscow (Russia)

Preis auf Anfrage

Wichtige informationen

Tipologie Master
Ort Moscow (Russia)
Dauer 2
Beginn September 2019
  • Master
  • Moscow (Russia)
  • Dauer:
    2
  • Beginn:
    September 2019
Beschreibung

Tuition fees: no tuition fee for the applicants who pass the selection process!

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 a high-level knowledge of machine learning, deep learning, computer vision, industrial data analytics, natural language processing, mathematical modelling and other important areas of modern data science.

General submission deadlines:
1) February 3, 2019
2) March 17, 2019
3) April 21, 2019
4) June 05, 2019
5) July 16, 2019

Wichtige informationen
Welche Ziele verfolgt der Kurs?

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.

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

Einrichtungen (1)
Wo und wann
Beginn Lage
Sep-2019
Moscow
Nobelya Ulitsa 3 Moscow, Russia 121205, 121205, Moscow and Moscow Region, Russia
Karte ansehen
Beginn Sep-2019
Lage
Moscow
Nobelya Ulitsa 3 Moscow, Russia 121205, 121205, Moscow and Moscow Region, Russia
Karte ansehen

Meinungen

4.5
ausgezeichnet
Kursbewertung
100%
Empfehlung der User
4.9
ausgezeichnet
Anbieterbewertung

Meinungen über diesen Kurs

S
Student
28.12.2018
Das Beste: The engineering and design school could organise better but the facilities for doing work and layout and rules are fair.
Zu verbessern: -
Kurs abgeschlossen: Dezember 2018
Würden Sie diesen Bildungsanbieter weiterempfehlen?: Ja
B
Brandan Willcocks
23.09.2018
Das Beste: 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.
Zu verbessern: -
Kurs abgeschlossen: September 2018
Würden Sie diesen Bildungsanbieter weiterempfehlen?: Ja
A
Andrei Davydov
25.11.2018
Das Beste: 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.
Zu verbessern: Nothing to improve
Kurs abgeschlossen: November 2018
Würden Sie diesen Bildungsanbieter weiterempfehlen?: Ja
*Erhaltene Meinungen durch Emagister & iAgora

Was lernen Sie in diesem Kurs?

Entrepreneurship
Data analysis
Data Protection
Mathematics
Algebra
Maths
Digital Editing
Data Management
Image processing
Modelling
Applications
Machine Learning
Analytics
Process
Data science
Robotics
Blockchain
Machine Learining
Coding Theory
Biomedical Imaging

Themenkreis

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)

  • Efficient Algorithms and Data Structures
  • Numerical Linear Algebra
  • Machine Learning
  • Foundations of Multiscale Modelling
  • Introduction to Data Science
  • Large-scale Optimization and Applications
  • Perception in Robotics
  • Introduction to Quantum Information and Quantum Computation
  • Convex Optimization and Applications
  • Introduction to Blockchain
  • Advanced Statistical Methods
  • Information and Coding Theory
  • Signal and Image Processing
  • Natural Language Modelling and Processing
  • Geometrical Methods of Machine Learning
  • Biomedical Imaging and Analytics
  • Deep Learning
  • Bayesian Methods of Machine Learning
  • Introduction to Digital Agro
  • High Performance Computing
  • Thermodynamics and Transport at Nanoscale
  • Computational Materials Modelling
  • Fast and Efficient Solvers


Elective courses (24 credits)
Entrepreneurship and Innovation (12 credits)

  • Innovation Workshop
  • Ideas to Impact
  • Leadership for Innovators
  • Business Communication
  • Thinking Disruptive for a Big Future
  • Biomedical Innovation and Entrepreneurship
  • Intellectual Property and Technological Innovation
  • New Product Design: from Idea to Market Launch
  • Management of Research & Development
  • Technology Entrepreneurship


Research and MSс thesis project (36 credits)
Industrial Immersion (12 credits)