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Regular version of the site
Master of Data and Network Analytics
Master’s Programme

Master of Data and Network Analytics

2 years
eLearning programme
600 000 –
1 200 000 RUB for the entire period of study
Instruction in English

Presentation of the Programme

What is this online degree about?

The main goal of this degree is to provide state-of-the art Master’s education focused on two main areas:

applied data analytics
network analytics

Who should consider this online degree?

The master’s programme in Data and Network Analytics is designed for anyone wanting to learn to use any type of available data, with a special focus on unstructured (text) and connected (network) data, in order to make better decisions in both academia and practical real-world situations.

Data analytics is an overarching science that encompasses the complete management of data, including data collection, organization, storage, and all the tools and techniques of the broader field of data analysis (not just statistics). The key advantage of Master of Data and Network Analytics is the applied approach to data analytics.

Network analysis is a special field focused on analysis of relational data. Networks are everywhere, including the Internet and other infrastructure networks, social, political and economic networks, scientometric and text-representational networks, as well as food webs and molecular-level biological networks. Master of Data and Network Analytics will emphasize network data analysis.

Although the programme is open to academics, it is ideally structured for professionals from industry and government, as it will utilize real-life practical cases and examples to demonstrate state-of-the-art approaches to data acquisition, data description, data visualization, as well as prediction and prescription for better decision-making. It is especially well suited for IT professionals who are responsible for programming, monitoring security systems, working with neural networks and artificial intelligence (AI), and NFV, as well as those responsible for social network analysis.

The online delivery of this programme gives considerable flexibility to students who do not want to sacrifice education quality and do not want to take time off work. This program provides the best of both worlds.


  • Open to students from all backgrounds. We start from scratch and provide all the information necessary to successfully acquire all data analytic tools.
  • Applied focus of our training. We offer an applied perspective: we start with problem formulation, understanding the data that are necessary to solve a particular problem, and selection of tools that could be used for solving the problem. We help our graduates become highly sought-after network analysts
  • Earn your master’s without quitting your current job. Lectures are organized into weekly modules, which you can absorb via video playback or interactive transcript. Pace yourself through online lectures before meeting with the teaching team and your classmates to dive deeper into the material.

Results and Career Prospects

Our programme is designed to help graduates become highly sought-after network analysts and is ideally suited for those who plan to continue or pursue a career in industry. That said, some graduates of the programme choose to pursue further study in PhD programmes. Our rigorous approach to data analytics training is certainly sufficient for an academic career in any field.

Master of Data and Network Analytics programme offers more than just a master's degree. It offers a rounded, theoretically-driven and empirically rigorous training in the newest state-of-the art analytics.

Our students will know every aspect of working with the data, from data management to advanced analysis, and will be able to apply the skills they have learned in any setting, from medicine to linguistics to social sciences.

Most importantly, they will have the advantage of understanding relational data and become trained network analysts—a rare skill even in the data science profession.

Admission Requirements

Admission to the programme is based on prospective students’ existing achievements. There are no entrance exams, although students should demonstrate sufficient scholastic aptitude, critical thinking skills, and career motivation to gain admittance.

The application process requires you to submit a portfolio containing the following:

A bachelor’s degree from any field of study from an accredited educational institution.
Accreditation must be sufficient for nostrification at HSE.

A motivation letter demonstrating an understanding of the benefits that the programme will provide, as well as your past achievements and future career plans; evidence of your ability to study in English (e.g., an English-language undergraduate programme, sufficient number of courses taken in English, or official test results such as IELTS, TOEFL, etc.; a current resume; at least one letter of recommendation from an employer or university professor highlighting your strengths.

During your Studies

By pursuing a master’s degree (MSc) in Data and Network Analytics, you will receive well-rounded, theoretically-driven and empirically rigorous training in the latest state-of-the art analytics. You will learn every aspect of working with data, from data management to advanced analysis – including quantitative analysis – and you will be able to apply the skills you’ve learned in a number of settings, from medicine to linguistics to social sciences.

Every course offered in the programme covers the mathematics necessary to master the content, the software and programming skills required to perform analysis, and practical examples to work from. Moreover, since our programme has an applied focus, we start from problems rather than mathematics and proofs.

The programme starts with the basics of data analytics. We then move to progressively more advanced topics applicable to different types of data. As the programme progresses, training will become increasingly rigorous.

To enhance the flexibility of the programme, students are given the freedom to tailor their education to their specific needs by selecting courses they want to take from a large pool of available electives. Each topic brings a focus on specific problems and challenges that real-life analytics present. You will work through these problems, attempting to find the best solution, combining methods and tools from different courses, all while continuing to master advanced programming and software skills.

Towards the end of the programme, you will have a well-rounded understanding of the possible problems that can be solved with data analytic approaches.

Partner University

Core Faculty

Valentina Kuskova

Head of International Laboratory for Applied Network Research, Ph.D Indiana University

Anuška Ferligoj

Academic Supervisor:International laboratory for Applied Network Research, Ph.D University of Ljubljana

Dr. Janez Demsar

Ph.D University of Ljubljana

Dmitry Zaytsev

Leading Research Fellow:International laboratory for Applied Network Research, Ph.D in Political Sciences, Master of Applied Mathematics and Informatics

Elena Beylina

Analyst: International laboratory for Applied Network Research, Master of Applied Mathematics and Informatics

Alexander Byzov

Lecturer, Doctoral Student:Faculty of Social Sciences, Master of Sociology

Erik Štrumbelj

Ph.D University of Ljubljana

Ljupco Todorovski

Ph.D University of Ljubljana


Inter-campus courses will continue to be held online
December 29, 2021
Till December 19, 2021 HSE students will have an opportunity to assess the quality of their teachers’ work.
November 29, 2021
Till October 17, 2021 HSE students will have an opportunity to assess the quality of their teachers’ work.
September 28, 2021
HSE University continues to develop its new study format for students embarking on a research career: the Combined Master's-PhD track. This year, there will be 75 places for Master’s students on the track—two thirds more than last year. HSE Vice Rector Sergey Roshchin talks about the appeal of the combined-track option, how to enrol, and the achievements of last year’s applicants.
July 19, 2021
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