11, Pokrovsky boulevard.
Phone: +7 (495) 531-00-00 *27254
Arzhantsev I., Kuyumzhiyan K., Zaidenberg M.
Advances in Mathematics. 2019. Vol. 351. P. 1-32.
Sulimov P., Voronkova A., Danilova Y. et al.
Journal of Proteome Research. 2019. Vol. 18. No. 5. P. 2354-2358.
Grachev A., Ignatov D. I., Savchenko A.
Applied Soft Computing Journal. 2019. Vol. 79. P. 354-362.
Makhalova T., Kuznetsov S., Napoli A.
In bk.: 2019 Data Compression Conference Proceedings. IEEE, 2019.
Шеин А. В., Zaikin A., Poptsova M.
Scientific Reports. 2019. Vol. 9. No. 7211. P. 1-16.
The faculty trains developers and researchers. The programme has been created based on the experience of leading American and European universities, such as Stanford University (U.S.) and EPFL (Switzerland). Also taken into consideration when creating the faculty was the School of Data Analysis, which is one of the strongest postgraduate schools in the field of computer science in Russia. The wide range of elective courses will allow each student to create his or her own educational path. In the faculty, learning is based on practice and projects.
We invite students of 8 – 11 grades, their parents and teachers to the Bachelor's Programmes Open Day
In the programme:
"Data Science: Challenges and Opportunities"
In this information age, data of unprecedented sizes and complexities bring opportunities with challenges to almost all sectors in our society. Companies, governments, and academia increasingly rely on data-driven decision-making, expanding the demand for data analytics expertise. Here, we illustrate the usefulness and the power of data analytics by some successful applications. We also examine some common features of big data, and the limitations of data analysis.
Presentation part, where you can learn more about educational programmes
Interactive part from students of the Faculty:
Date: November, 10
Time: 12:00 – 16:00
Location: Pokrovsky blvd 11