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Regular version of the site
Data Analytics and Social Statistics
2 years
Full-time programme
Online programme
400 000 RUB/year
Tuition Fee in 2024
Russian government and HSE scholarships and tuition fee waivers not applicable
ENG
Instruction in English

Presentation of the Programme

Partner Universities

Facts about the programme

Has no analogues in Russia, the only programme on applied statistics and network analysis
Created on the basis of the International Laboratory for applied network analysis (ANR-Lab)

Classes are taught by Russian and foreign teachers – partners from the University of Ljubljana

Master's degree in the field of study 01.04.02 'Applied mathematics and computer science'
Based on the best practices for teaching applied statistics at Indiana University and the University of Ljubljana
The educational process is based on the expertise of academic research and applied projects
We train highly qualified practitioners who are able to apply advanced complex data analysis techniques in their daily work in various organizations in the public, commercial and scientific sectors

Key Advantages

Online programme with full-time status
the opportunity to study from anywhere in the world and combine it with work
Flexible study schedule
online classes in the evening, access to recordings for the entire period of study
Individual trajectories

selection of track and courses to study, feedback from teachers

Best expertise
studying with leading Russian and foreign specialists
deferment from conscription for military service according to Russian legislation
Practical orientation
project-based learning based on real data and business problems
Student privileges
access to university infrastructure and facilities
Study in English
programme in English with a choice of electives in Russian

Programme opportunities

 Access to data analytics expertise

Entrance to the professional community

Access to university facilities

Teaching students without a mathematical background

✔ Consultations with research fellows

Practive in a scientific laboratoty

 

Ivan Klimov
academic supervisor of the online master's programme 'Data Analytics and Social Statistics'
Anna Semenova
graduate of the online master's programme 'Data Analytics and Social Statistics'

Watch other videos

Two learning trajectories

When enrolling in the programme, we will help you design your individual plan and choose courses to follow your educational path:

Computational Social and Network Sciences
is devoted to the study of actively developing quantitative methods in the social sciences, including network analysis
Applied Statistics and Data Analytics
is devoted to the study of advanced methods of mathematical statistics and data sciences

Prospects after study

Start of an analyst's career

Opportunity to apply for positions as a data analyst, business analyst, consultant in government and corporate analytical centers, international companies

Start of academic career

Opportunity to engage in scientific research in the field of data analytics and network analysis in graduate school in an international laboratory in Russia or abroad

The programme allows students to become highly qualified practitioners who apply advanced complex data analysis techniques in various fields of knowledge (banking, insurance, consulting, IT, medicine, pharmaceuticals, sociology, marketing)

How the educational process is organized

✔ Asynchronous learning format (pre-recorded lectures)
✔ Scored and Ungraded Tests

✔ Access to all course materials for the entire period of study

✔ Synchronous format (online meetings in real time)
✔ Project assignments
✔ Term paper and master's thesis

Contents of the programme

Admission requirements

 

Higher education diploma

at least bachelor's degree, uploaded to portfolio
 
 

Knowledge of school math course

no confirmation required
 

Confident English language skills

confirmation by documents in portfolio and participation in interview

At the beginning of study we offer adaptation courses:

  • Introduction to Statistics
  • Introduction to R and Python Programming

Admission to the programme

Key dates and deadlines

 
April 1
Start of documents acceptance
September 16
Deadline for documents acceptance
September 23
Deadline for signing documents for enrollment in the programme

Portfolio composition

15
points
Basic education
Compliance with the focus of the programme and the presence of a honors diploma are taken into account
20
points
Motivation letter
Approximate content: previous education, motivation for enrolling in a master's programme, a story about current employment, what areas of development you are interested in, what you want to learn in the programme
10
points
Letters of recommendation (2 letters)
From professors, employers or industry representatives. One letter – 5 points
20
points
CV
10
points
TOEFL, IELTS 
Or equivalent
15
points
Other documents
Experience in project and scientific activities, publications, grants (including a diploma of a winner or prize-winner of the Olympiad for students and graduates of the National Research University Higher School of Economics in related fields)
10
points
Interview
Conducted in English

Tuition fees for 2024

Per term
200 000 ₽

Payment is made by term

Per year
400 000 ₽
 
DISCOUNTS
Possibility to get a discount
on several grounds
LOAN FROM SBERBANK
Opportunity to obtain
an educational loan
with government support
TAX DEDUCTION
Opportunity to apply
for a social tax deduction
for educational expenses

 

INSTALLMENT
Possibility to get tuition fees
in installments in several payments
PAYMENT BY EMPLOYER
Possibility of a tripartite agreement with the employer paying for the cost of study
PAYMENT WITH MATERNITY CAPITAL
Possibility of paying for education
using maternity capital

News

The expert of the new issue of the "+/- 10 minutes" column is Anna Kartasheva, PhD in Philosophy, research fellow at the International Laboratory for Applied Network Research at the National Research University Higher School of Economics, and director of the publishing house "Business Book". In the lecture, we will look at how data becomes information, and information becomes knowledge. We will also discuss whether data can be a neutral and error-free record of facts, and how the specifics of knowledge formation affect modern information systems.
October 02
In the "+/-10 minutes" release, Anna Semenova, a junior research fellow at the Laboratory of Applied Network Research and the International Centre of Decision Choice and Analysis, a postgraduate student at the Faculty of Computer Science and a representative of the online master's programme "Data Analytics and Social Statistics", told how one can explain why Moscow became the capital of Russia or why you received fake news last week. Anna analyzed such problems from the point of view of centrality measures, and also explained what types of centrality exist and what other studies can be conducted in this way.
September 11
The International Laboratory of Applied Network Research invites you to watch the recording of the DASS open house event "On Data Analyst Career Strategies", which took place on September 10th. A graduate of the programme Elena Stegnii shared her experience and told who the programme is designed for, as well as what career prospects are possible. An important issue was also discussed: how to combine study and work in order to successfully develop in your chosen profession. The language of the seminar is Russian.VK Video:
September 10
The International Laboratory of Applied Network Research invites you to watch the recording of the webinar "How to analyze the labor market: comparison of Russian and international recruiting platforms for data analyst vacancies", which took place on September 5th.
September 05
More news