"Data Analytics and Social Statistics": Sharing Our Achievements

The Master's program in Data Analytics and Applied Statistics received high praise on two levels: it was recognized in four academic leadership categories for the year 2025, and students singled out its courses as the most useful and innovative.

Dear readers! We would like to remind you that the master's programme "Data Analytics and Social Statistics" consistently earns high marks — both within the university's formal evaluation of academic programmes and from our students. Over the past year the programme has been recognised across several areas, and we want to share a brief overview.

University-Level Recognition

Based on the 2025 results, the program was recognized as one of the best in four academic leadership categories:

• "Student Digital Skills"
• "Program Methodological Quality"
• "Interfaculty Interaction"
• "Student Attraction"

These categories are part of a systematic assessment of educational programs and the work of the university's academic leadership. Recognition in several categories demonstrates that the program meets high standards across a range of aspects, from methodological quality and interaction with other departments to student engagement. These 2025 awards were shared between the program's two academic directors—the former Academic Director Ivan Klimov and the current Academic Director Irina Pavlova.

Students' choice

In the 2025–2026 academic year, students separately singled out a number of the programme's courses as the most useful and the best. The vote was held across three criteria:

• "Usefulness of the course for your future career"
• "Usefulness of the course for broadening your horizons and all-round development"
• "Novelty of the knowledge gained"

Among the courses highlighted by students:

• Machine Learning
• Data Mining
• Introduction to Network Analysis
• Time Series Analysis
• Unstructured Data Analysis
• Structural Equation Modeling
• Programming in R and Python
• Data Collection from Web-Scraping and API for Social Scientific Research
• Applied Linear Models

The full list of the programme's courses for 2025/2026 is available on the courses page.

We are truly proud that the programme is highly valued both at the university level and by our students. This means a great deal to us: such trust motivates us to maintain a high standard of work and to live up to expectations. We are grateful to our colleagues and students for their feedback, and we will continue doing everything we can to keep the programme among the strongest!