July 25, 2021

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Hear from Students Pursuing their Master of Data Science Degrees from Russia’s HSE University

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The Master of Data Science (MDS) from the National Research University Higher School of Economics (HSE University) is the first fully online data science master’s program from a Russian university on Coursera. Students can take courses in contemporary data analysis, machine learning development, and research taught by experts at Russia’s leading technology companies, such as Yandex.

Because the program is entirely online, students can earn this MDS degree from a top-10 Russian university from around the world. Current students are located in more than 30 countries, including Russia, Belarus, Kazakhstan, India, the United States, Canada, China, Japan, Germany, Great Britain, Switzerland, and others.

We spoke with students Mehmet Namli, based in the United Arab Emirates (UAE), and Alexander Olekhnovich, based in Russia, to learn how they decided to become part of the global data scientist community and find out how their experience in the program has been so far.

 Mehmet Namli (UAE) compares the Machine Learning revolution to the internet boom in the 1990s and believes the knowledge he’s building will help him develop his business.

 How did you become interested in data science?

I’ve been working in finance and foreign exchange trading for the past 10 years. Before starting this program, I studied many different things to improve my skills. I’ve observed how modern trading is becoming more automated and focused on machine learning. Many companies are integrating machine learning into their processes — using artificial intelligence and machine learning algorithms for financial trading.

The knowledge I gained from the Master of Data Science program will be useful during the next 10–20 years in fintech or trading, as these industries have become automated and focused on machine learning. I believe we need to get insights from data and use them to inform business decisions—that’s why I’ve chosen data science for my future. Recently, my friends and I decided to start a company that applies machine learning techniques to portfolio management and trading. I’ll be focusing my HSE’s MDS thesis on our business project and use the findings for its benefit.

Why did you choose the online MDS program from HSE University? What attracted you the most?

I looked into many online programs provided by British and American universities and online courses from my own country. In my opinion, the HSE’s program is the most complete because of its emphasis on hands-on, project-based training. I also loved the deep focus on mathematics, programming, future professions, and projects. Most of the program is devoted to machine learning, which is very important for me. Unlike other programs, HSE’s MDS is flexible and offers three tracks based on types of roles: Researcher in Data Science, Machine Learning Engineer, and Data Scientist. Other programs often had only a single track. Overall, the curriculum of HSE’s program met my expectations.

I also considered HSE’s credentials worldwide and was satisfied by their performance in math and science. The global ranking of HSE is high, and so it played a role, too. 

The admissions process is rather easy: students must have a bachelor’s degree and then fill out an application form. An online exam then tests your understanding of mathematics. Although I studied a lot of math at my former university and feel very confident in my math skills, I don’t necessarily have the requirements needed for programs at other universities since they often require a bachelor’s degree in engineering. However, for HSE’s MDS program, I was able to apply with my bachelor’s degree in economics. 

Have you considered on-campus data science programs, and what prompted you to choose an online one?

I have a full work schedule and want to be able to spend time with my family, including my two kids. So traditional on-campus programs and relocation aren’t suitable for me. HSE MDS students can enroll in the program from anywhere in the world and complete the courses on their own schedule. Studying takes me about 15 hours a week, so sometimes I sleep a little less to catch up on everything. Not everything is like the campus programs, but I believe in life-long learning, and this online program makes it possible without changing my location or lifestyle.

In what practical projects and tasks were you involved in? What projects within the program did you find the most interesting?

I took part in several projects, mainly assignments as final exams that were connected with data-based predictions. We created a controller to collect data from the IMDb database and attempt to make classification models. I was involved with another project related to financial time series data analysis where I built statistical models and used machine learning techniques to compare results.

 What did you find the most challenging during your studies?

Definitely time management! It was a real challenge to find enough time for studying between work and family. But somehow, everything worked out!

 What wisdom can you provide to future students of the program?

I’m excited about the impact that machine learning and artificial intelligence is having on our lives. These algorithms are already in use nearly everywhere, in every machine. We just need a bit more speed on the hardware. In the next 10 years, we’ll see big, new corporations like Amazon or Facebook utilize machine learning. Shortly, I’d like to call them the champions of the machine learning era. The machine learning revolution is as bright as the internet boom of the 1990s. And we’re at the beginning of a new era now. New knowledge opens new doors for me — so that I can run my own business and be a part of the machine learning revolution.

Alexander Olekhnovich (Russia), a 2019 graduate of the National Research Nuclear University MEPhI, was looking for a promising field that would help him become an in-demand expert today and for the future. With a mathematical background and some basic programming skills, he decided to become a data scientist and chose the MDS program.

Why was the HSE online program attractive to you?

I liked that the MDS online program is suitable for people from various fields. If you’re interested in data science and are willing to push yourself, you’ll be a great candidate for this program. A big advantage is that you receive a degree after completing the program rather than a certificate, which is what most continuing education platforms offer.

What has turned out to be the hardest part of your studies?

One of the reasons I finally decided to apply to MDS was the idea that studies would be easily combined with work and family, but—spoiler alert!—it’s not that easy. Time optimization proved to be the main problem. Sometimes, I plan every five minutes of my daily schedule so that no one and nothing is left unattended. But if you stay enthusiastic, you can do it.

What practical projects throughout your studies have you found the most interesting?

The data scraping project was pretty great and thrilling: we parsed data from IMDb and played the “Six Degrees of Kevin Bacon” game based on the six degrees of separation theory. The NaturalLanguage Processing project was also really cool; we made chatbots. I also keep remembering all my mathematics courses. And really, all of the courses I took will be useful for my development in fintech.

While studying, I started working at a bank, dealing with big data and data engineering. I’m now starting on a course in large-scale machine learning and look forward to it being helpful in my work. In the MDS program, I’ve learned how to find approaches to solving different tasks and master new knowledge faster.

Is it convenient to study online?

Yes, because the program uses several types of communication tools: Coursera forums, Zoom, Slack, and Telegram. During the last year during the lockdown especially, I think that everyone learned to communicate online better. And if we have any difficulties, the program tutors quickly help sort out everything.

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