We use cookies in order to improve the quality and usability of the HSE website. More information about the use of cookies is available here, and the regulations on processing personal data can be found here. By continuing to use the site, you hereby confirm that you have been informed of the use of cookies by the HSE website and agree with our rules for processing personal data. You may disable cookies in your browser settings.
109028, Moscow,
11, Pokrovsky boulevard.
Phone: +7 (495) 531-00-00 *27254
Email: computerscience@hse.ru
Rodomanov A., Kropotov D.
SIAM Journal on Optimization. 2020. Vol. 30. No. 3. P. 1878-1904.
A. Boldyrev, D. Derkach, F. Ratnikov et al.
Journal of Instrumentation. 2020. Vol. 15. P. 1-7.
Dvurechensky P., Eduard Gorbunov, Gasnikov A.
European Journal of Operational Research. 2021. Vol. 290. No. 2. P. 601-621.
Kuznetsov S., Kaytoue M., Belfodil A.
In bk.: International Journal of General Systems. Iss. 49. 2020. P. 271-285.
Kaledin M., Moulines E., Naumov A. et al.
In bk.: Proceedings of Machine Learning Research. Vol. 125: Proceedings of Thirty Third Conference on Learning Theory. 2020. P. 2144-2203.
The Faculty of Computer Science was created with the goal of becoming one of the world’s leading faculties for developers and researchers in data analysis, machine learning, big data, theoretical computer science, bioinformatics, system and software engineering, system programming, and distributed computing. In cooperation with major companies like Yandex, Sberbank, SAS, Samsung, 1C, and many others, the Faculty provides both deep theoretical knowledge and hands-on practical experience in many branches of contemporary computer science.
The Master of Data Science programme was launched in February 2020. There are winter and autumn admission campaigns. One of the key features of the programme is that it is realized entirely online on Coursera: students watch lectures and complete assignments at their own pace, communicate with fellow students in Slack and with lecturers in Zoom.
The programme brings together around 200 students from all over the world and is taught in English. At the moment, the admission campaign for spring 2021 is over and applications for Fall 2021 are already open.
There are three tracks on the programme: Data Scientist, Machine Learning Engineer and Researcher in Data Science. After the first semester, when students have already levelled up in basic mathematics and programming, they choose a track according to their professional needs. To help them decide, three industry webinars were held with leading IT professionals from Yandex and Google. There was also a consultation with the programme's academic supervisors, where students asked questions about the courses they were about to study in a particular track.
One of the students, Diego Eugenio Páez Martínez, chose the ML Engineer track and talked about his studies on the programme and his plans for the future:
So far the classes have been great; of course, there are always things to improve but overall I am happy with the programme. I also believe that the programme is up to date on topics needed by the industry.
The first semester contained many subjects to introduce us to the fundamentals of data science. I liked it, some of the subjects were a nice refresher of my undergraduate studies, but I also learned new things especially in the advanced Python class of Yuri Goryshni and Dmitry Borisov.
I have chosen the track of Machine Learning Engineer track because I believe I will find DevOps interesting. I know there is a lot of new software that allows people to create the applications in newer and better ways than perhaps ten years ago and I would like to know about this.
Since I work as a Senior Data Scientist and I have had courses in topics related to Data Science, I thought it would be better to study something different. Additionally, I have seen that there is a requirement in the industry not just to make models but to make them productive, so I thought it would be a good idea to learn about the topics in the Machine Learning Engineer track. I also am expecting to study the best practices for deploying these models and Machine Learning using C++.
Some of the first electives in the Data Scientist and Machine Learning Engineer tracks are Applied Statistics and Introduction to Deep Learning, and for the Researcher track, Computational Complexity and Computational Learning Theory. More details about the structure of the programme and its courses can be found here.
The application deadline for autumn 2021 is June 17. You can read about the application procedure on our website.