‘Today Data Is Processed and Interpreted at a Completely Different Level’

© iStock

Additional enrollment in the online programme ‘Master of Data Science’ is now open. Daniil Kopylov, 1st-year student of the master's programme, told HSE News Service why an international financial specialist should study Data Science.

Daniil Kopylov

— Daniil, why did you decide to get a second degree in the field of data science?

— I graduated from MGIMO with a degree in international finance, and I work in foreign trade. From my own experience, I can see that the methods of information processing used in companies are outdated: an elementary knowledge of Microsoft Excel is regarded as data analysis. Today, data needs to be processed and interpreted on a completely different level, and many organizations simply cannot keep up with modern trends. I don’t want my data processing skills, which are required in almost any field, to become obsolete, so I decided to study Data Science.

For me, data science is not about mechanical actions with tables, but understanding mathematics and creating ready-made products and models that simplify our lives

I see everything related to analysis as the most popular direction in Data Science, because regardless of the methods, everyone likes to get a ready-made review, so there is a lot of work. I am interested in such areas as computer vision and Natural Language Processing: when you start understanding the mechanisms of work, you begin to perceive the concept of data in a different way.

— Why did you choose the HSE Master's programme? Have you analyzed the online software market?

— I wanted to quickly learn how to work with data, this requires full-time study, while any vocational courses eventually reduce all training to performing monotonous tasks. During studying for an Msc you walk a long and difficult path, but eventually your knowledge evolves: you go from the simple to the complex and therefore completely understand what you are doing.

I studied the market thoroughly and among all the options I narrowed it down to a couple of programmes from Russian universities, as well as the University of Michigan and Imperial College London. An opportunity to take exams was an important criterion, so I focused only on the universities in the Russian Federation: I wanted to really try my hand at this, and not just leave with a portfolio. At the same time, being taught in English was important to me: studying original materials and terminology is more interesting than anything in translation.

I liked the HSE Master of Data Science programme more than the others: it offers the ability to learn SQL and a fully-fledged course in mathematical statistics - those who do not study economics with a focus on mathematics really will have something lacking. In addition, enrollment for the programme takes place twice a year. In fact, I regret not having the opportunity to study at HSE Faculty of Computer Science previously, and I am glad that I have now become a student of the FCS programme.

— Is it convenient for you to study online?

— I had taken HSE online courses previously, and enjoyed them. Another very important point is that many employers have a negative attitude towards employees who study on campus in parallel with work. Therefore, online education with time-friendly webinars eliminates any possible conflict in this area. There is no opportunity to apply the acquired skills in my current job, but there is that special pleasure of studying before and after it. When this happens, you realize that you are learning for yourself and that no one can take this away from you.

Despite the online format, a full-fledged community of students has formed on the programme. Classmates are active in every subject. Many people work, we have very little time, but it is enough to communicate about our studies and other topics. When you’re studying online, your age doesn’t matter, and it is much easier to communicate. We have very different interests and levels of training, but, in my opinion, this only makes the learning process much more lively.

— What competencies acquired during your studies will you apply in your work in the future?

— In real life, you can't get by without algorithms and data structures (although I believe that the ability to operate matrices will be a plus for anyone) — this will help in preparing for an interview in IT, and will allow you to see any shortcomings in work that is not related to data analysis.

— What turned out to be the most difficult thing for you in the learning process?

— To maintain my motivation. But my mother always supports me. I don’t have a specialized education, but I am sure that without special skills a person can achieve a lot, for example, to reprogram a router, you just need to be persistent. It happens that deadlines loom over all disciplines at the same time, and then you have to study all weekend.

I usually spend a lot of time with friends and family, and due to studying, this time has been reduced by 50-70%, but their support makes it clear that this percentage is relative.

If you decide to enrol on the programme, study the page with its description, be sure to look at the curriculum, all related subjects, and make inquiries at the study office. Determine why you need to study, you can return to this thought to refuel your motivation. I would definitely recommend HSE's online Master's programmes to my friends, but it's better to try online courses first - then you’ll better understand the specifics of off-site education.

The programme includes 3 tracks:

 A Data Scientist is a machine learning specialist capable of solving both traditional business tasks (demand forecasting, outflow prediction, text data analysis, segmentation, etc.) and modern formulations (building question answering systems, image analysis, generation of realistic examples, etc.).

 A Machine Learning Engineer is a specialist at the intersection of data science and development who understands and applies modern technologies for collecting, storing and analyzing large amounts of data, and is able to write effective code and design complex systems related to machine learning services.

 A Researcher in DS is a machine learning specialist familiar with state-of-the-art results who understands the theoretical foundations of machine learning and can improve existing methods.

Learn more and apply