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Contacts

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Phone: +7 (495) 531-00-00 *27254

Email: computerscience@hse.ru

 

Administration
First Deputy Dean Tamara Voznesenskaya
Deputy Dean for Research and International Relations Sergei Obiedkov
Deputy Dean for Methodical and Educational Work Ilya Samonenko
Deputy Dean for Development, Finance and Administration Irina Plisetskaya
Article
A randomized coordinate descent method with volume sampling

Rodomanov A., Kropotov D.

SIAM Journal on Optimization. 2020. Vol. 30. No. 3. P. 1878-1904.

Article
ML-assisted versatile approach to Calorimeter R&D

A. Boldyrev, D. Derkach, F. Ratnikov et al.

Journal of Instrumentation. 2020. Vol. 15. P. 1-7.

Article
An accelerated directional derivative method for smooth stochastic convex optimization

Dvurechensky P., Eduard Gorbunov, Gasnikov A.

European Journal of Operational Research. 2021. Vol. 290. No. 2. P. 601-621.

Book chapter
On pattern setups and pattern multistructures

Kuznetsov S., Kaytoue M., Belfodil A.

In bk.: International Journal of General Systems. Iss. 49. 2020. P. 271-285.

Book chapter
Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise

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.

Choosing the Learning Track of the Master of Data Science Online Programme

Choosing the Learning Track of the Master of Data Science Online Programme

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:

Diego Eugenio Páez Martínez
Student of Master of Data Science programme

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.