Applied Statistics with Network Analysis

The master's programme "Applied Statistics with Network Analysis" of HSE University is based on the International laboratory for Applied Network Research (ANR-Lab). It is based on the best practices of educational programmes in applied analytics universities as Indiana University and the University of Illinois in the USA.

The programme was founded by Indiana University professors Stanley Wasserman and Valentina Kuskova.

The programme trains highly qualified specialists (Data Scientists) in applied statistics and network analysis, becoming more and more in demand in business sphere, public sector, and science both in Russia and abroad. In other words, the programme trains highly qualified data analysts for international and Russian businesses, analytical centers, and universities in Russia, the USA, and Europe.

The programme is fully English-taught, and international instructors teach the courses from University of Ljubljana (Slovenia), Graz Technical University (Austria), Central European University (Hungary and Austria).

Unlike traditional statistics or data science programmes, students are allowed to create their learning trajectory by choosing one of the tracks:

• Business Analytics (focused on preparing students for employment in business companies and corporations),
• Computational Social Science (focused on preparing students to enter leading Ph.D. programmes at prestigious universities in Europe and the United States).

The programme's primary goal is to teach students to use advanced statistical and network analysis methods regardless of the initial education to solve both research and practical problems.

The educational process is not limited to, learning theories and methods of data analysis. Students can engage in academic research at the HSE International Laboratory for Applied Network Analysis. They can also participate in the Statistical Consulting Center's commercial projects, created by the Laboratory researchers and the programme professors.

The programme is learning based on real data and tasks. The teachers do not focus on the tools but teach them how to work with the available data and select the appropriate analysis methods for their processing.

This programme is unparalleled in Russia and has the following advantages:

• applied statistics from scratch;
• choice of the track: business, science, or universal;
• learning in English;
• the possibility of foreign internships;
• dual degree programmes with the University of Ljubljana;
• predominantly foreign instructors;
• using real data as examples during the course. This helps students understand how the method works and on what data it can be used;
• regular consultations from scientific supervisors at the International laboratory for Applied Network Research;
• individualized learning plans that allow students to create their learning trajectory;
• full-time classes that will enable ongoing contact and feedback from instructors;
• evening classes that enable students to combine work and study;
• in the second year, students complete an internship.

The master's programme has no analogues in Russia. It is based on the best practices of educational programmes in applied analytics at universities such as Indiana University and the University of Illinois.

There are several similar programmes at European universities, particularly at the University of Ljubljana and Northwestern University, which are affiliated partners of our programme.

Compared to similar programmes in applied statistics in Europe and the U.S., our master's programme is several times cheaper.

The programme will benefit sociologists, economists, mathematicians, chemists, biologists, political scientists, lawyers, managers, computer scientists and statisticians, and anyone for whom data analysis is part of their job.

After completing your master's degree, you will be able to:

• build data analysis into the research cycle: from setting up a research question to interpreting the findings;
• use modern approaches and methods of
  • data science (Data Science);
  • research and data mining (Data Mining & Deep Learning);
  • Machine Learning;
  • Neural Networks & Bayesian Statistics;
• work with Big Data;
• work with different packages and databases for data analysis and reporting: R, Python, SAS, STATA, Orange, Lisrel, MPlus, Pajek, Gephi, Visone, Vertica, SQL, LaTex, etc.;
• proficiency in mathematical English;
• present the results of their research or business project.

Before the start of the course, there is a test, based on which masters are helped to design an individual plan and choose the courses they consider necessary in the future; find a balance between the main blocks: business analytics, computational social science, network science and network analysis methods.

Adaptation courses in introduction to statistics and programming in R and Python are implemented at the beginning of the course. This helps students who do not have a major in mathematics or statistics.

Within the programme, students can choose one of two trajectories:

• Business Analytics (focused on preparing students for employment in business companies and corporations),
• Computational Social Science (focused on preparing students for entry into leading Ph.D. programmes at prestigious universities in Europe and the United States).

Students of the programme learn to use modern approaches and methods of data science (Data Science), research and in-depth data analysis (Data Mining & Deep Learning), Machine Learning, neural networks and Bayesian statistics, work with big data (Big Data), and work with different packages and databases for data analysis and visualization, construction of reports: R, Python, SAS, STATA, Orange, Lisrel, MPlus, Pajek, Gephi, Visone, Vertica, SQL, LaTex, etc.

Students can do academic research at the HSE International laboratory for Applied Network Research. They can also participate in commercial projects at the Statistical Consulting Center, created by Laboratory researchers and programme faculty.

The programme cooperates with SAS, Deloitte, Volkswagen Group Rus, Rosatom, and other companies.

Thus, during their studies, students take part in real projects and can choose the programme's internship placements or independently.

The knowledge and competencies acquired by graduates of the master's programme will allow them to become highly skilled practitioners capable of applying advanced complex techniques of data analysis in their daily work in organizations of various types: both in commercial companies specializing in various industries (banking, insurance, consulting, I.T., medicine, pharmaceuticals), and in research organizations (sociology, marketing). 

Graduates of the programme can also work as consultants in government and corporate analytical centers, do research in international companies, continue their postgraduate studies in Russia or enter Ph.D. programmes abroad.

Read more about the future profession.

The university also organizes career events for students and graduates, advises on how to write a resume, publishes direct vacancies from employers interested in HSE University graduates, and assists in job placement.

In 2023, 25 fee-paying places for citizens of the Russian Federation and 5 fee-paying places for foreigners are opened in this programme. After graduation, you will receive a master's degree in the field of study 01.04.02 "Applied Mathematics and Informatics". For admission, it is sufficient to know a high school mathematics course and understand English. Certificates confirming knowledge of English and mathematics are not required.

The programme offers adaptation courses in introduction to statistics and programming in R and Python. This allows students with a non-core bachelor's degree to tighten their knowledge and fully explore all further courses. 

To get an education in this programme, you must pass a competitive portfolio selection process. To do so, applicants must submit a bachelor's or master's degree, resume, motivation letter and recommendation letter. Certificates, diplomas, and other documents showing the applicant's level of knowledge or achievements are also considered.

Applications are accepted in December-August 2023. Enrollment takes place at the end of August 2023.

How to Apply section will help you learn about admission policies, deadlines, and more information.

   How to Apply section will help you learn about admission policies, deadlines, and more information.

Tuition fees are paid in installments (semesters) or in full (per year). There is also an installment plan option.

The terms and conditions for the discounts are available on the website.