Put together for a Profession in Knowledge Analytics

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Earn your master’s from Russia’s #1 university and learn to make better decisions driven by data.

At this time of intensive economic digitalization, robust data analysis capabilities are essential for any business’ success in the digital economy. Demand for qualified data specialists continues to soar. The new online Master of Data and Network Analytics (MDNA) program on Coursera represents a unique opportunity to master the vital skills necessary to analyze data on a massive scale and to develop the fundamental skills needed to solve key business problems with data. Whether you are just starting your career or looking for a mid-career leap, you can enter the lucrative field of data analytics by earning your master’s from the Russian university ranked #1 by Forbes – 2020.

To learn more about this new program, we spoke with Professor Valentina Kuskova, the Academic Supervisor of the online Data and Network Analytics master’s programs at HSE and Head of the International Laboratory for Applied Network Research. Among the many topics we covered over the course of our conversation, Professor Kuskova talked about the program’s founders and faculty, its structure and focus on innovation, and the parallels between this program and HSE’s Master of Applied Statistics with Network Analysis (MASNA) program. MASNA is a unique offering on the educational market in the broader field of data science as an offline mirror of the MDNA program. To further understand these parallels, we also heard from three MASNA graduates who shared insights about their learning journeys and the role their degrees continue to play in their careers.

Professor Kuskova, thank you so much for taking the time to talk with us, and congratulations on the program launch! Let’s get started with some context. Can you tell us a bit about the creators of the program?

Thank you, and yes, of course. The program was created by leading researchers, experts in applied data analysis, at the International Laboratory for Applied Network Research (ANR-Lab). The Lab is a semi-independent unit within the Faculty of Social Sciences at HSE University. The laboratory develops and tests new methods of data analysis and their wide-ranging applications in empirical research. Affiliated laboratory faculty include researchers in such fields as sociology, political science, economics, management, mathematics, statistics, computational linguistics, and computer science.

The breadth of focus is really impressive, and the program sounds like an excellent opportunity for learners to engage with world-class faculty.

Yes, just as with the on-campus master’s program, students have access not only to high-quality educational content, but the ability to participate in hands-on research and business analytics projects of the Lab. They also benefit from direct contact with expert lecturers in both classes and workshops.

As you think about the curriculum and the structure, what types of learners do you see as benefiting from this program?

Our program offers comprehensive theoretical and empirical training in analytics. It is ideal for those learners who want to use state-of-the-art approaches to working with any data, but especially with unstructured (texts and images) and relational (network) data. Everyone, from students and aspiring researchers to industry experts and managers in the public sector, can benefit from knowing how to use data to make the right decisions in research, practice, and everyday life. 

So is it correct to say that the focus is on fundamental concepts as they apply to the current state of data in the world?

Our program provides competencies that meet the challenges of the modern world. We give students the analytical grounding to solve problems, draw important conclusions, and apply an integrated approach to problem-solving. The program prepares beginners and experts alike to better understand and study complex data and phenomena.

Now that we’re talking about your approach to teaching, we’d love to hear more about the experts who are teaching in the program. Can you share some insights about the faculty?

The program faculty come from the best international universities. We’re proud to have, as our faculty, world-renowned professors who are not only very knowledgeable in modern analytical trends, but who advance these trends by creating new methods. Nearly 80% of the program’s courses are taught by teachers with PhD degrees from the world’s best universities. 

Faculty involved in the program include Anuŝka Ferligoj, a leading expert in cluster analysis and blockmodeling and Nada Lavraĉ, a world-renowned expert in artificial intelligence. We also have Janez Demšar, one of the creators of Orange data-mining software, and Ljupco Todorovski, the co-creator of several machine learning systems. Erik Štrumbelj is a leading expert in Bayesian methods and a co-author of several R libraries for Bayesian analysis. The list goes on.

Given their wide scope of expertise and experience, would you say there is a core set of principles or characteristics that unites the group?

I think it’s the problem-oriented approach that is the core competency of our master’s program. Unlike other educational programs that teach methods, our professors emphasize formulating the problem first, considering both the issues at hand and the data. Once it is clear what types of data are available for solving the problem, only then can we move to selecting a method of analysis. We believe such an approach allows for better, unique solutions that stand out.

What can you tell us about the actual learning experience?

This is an applied program that fully incorporates project-based training using live data and real cases, including cases brought to the program by students themselves. Projects are implemented at three levels (course, specialization, thesis), and by the end of the program students’ portfolios can contain dozens of projects.

And how about the curriculum? Are there different tracks?

Students can choose one of the tracks for their individual study plan: Network Analytics, which emphasizes working with relational data (such as social networks); Business Analytics, which focuses on generating non-trivial, data-driven decisions for modern businesses; and Computational Social Sciences, which is designed for those who want careers in science.

To what extent can the program accommodate learners with different levels of knowledge and experience?

Almost all courses are available at both basic and advanced levels. This allows students with different knowledge backgrounds to study the same topics. The program offers a wide range of subjects to choose from—many more than the required number to earn a degree—which enables students to broaden their analytical horizons as much as possible.

Professor Kuskova, thank you so much for sharing your insights and expertise with us! We’re thrilled that the new program is now live on Coursera, and we look very forward to seeing how learners grow their careers through the knowledge they gain in this master’s program.

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On the topic of learners and career success, we mentioned in the introduction of this post that we also spoke with some on-campus graduates of the Master of Applied Statistics with Network Analysis program at HSE University to learn about their career advancement. Let’s hear from them now!

Dina Yakovleva, as a MASNA graduate, can you tell us about some of the most important skills you learned during your studies?

I would say I acquired three key skills in the program. The first is that I can do data analysis on anything you provide me, no matter what field it is. This means that I can find a job that I like in any location, which I really appreciate! Second, I can learn any software I’m given. I know how to go through programs and understand their language and structure. And third, I am a part of a young, dynamic, scientific community where I can always find help and support. 

Brennan Lewis Larson, we’d love to hear your perspective as a student from the U.S. What led you to HSE, and how do you feel about the learning experience?

I was looking for a master’s degree in statistics, and what attracted me to the HSE program is that the professors are from European universities. I am really enjoying the experience and the support I’m receiving from the faculty. Whenever you want to talk to professors about research ideas or projects, they gladly help you out.

Elizaveta Chernenko, can you tell us about your current role, and how you saw HSE fitting into your career plans?

I am a teacher of Probability Theory and Statistics at the International College of Economics and Finance of HSE University. I am also working as a business consultant, which is an opportunity to apply organizational working analysis. I chose MASNA because I wanted to build a career in social network analysis—especially as it applies to business consulting. I tried several projects that were only half successful. I felt I had a lack of contacts, skills, and knowledge in this sphere. I didn’t know the right people to help me make the right decisions. When I learned about the new MASNA program, I was impressed. The list of professors really inspired me. 

Looking back now, how would you describe the impact earning your degree had on your career?

I would say the most important outcomes are that I made connections with the right people, gained access to the knowledge I needed, and was able to apply that knowledge. Also, I really loved my classmates. The kinds of students that are attracted to this program are really admirable.  I made many friends, and we really worked as a team on our projects. Those two years were some of the best in my life.

That’s wonderful!

~We’d like to thank everyone for their generosity in sharing their perspectives about the learning experience at HSE. We encourage anyone who is interested in developing in-demand data analytics skills, gaining hands-on project experience, and earning a master’s degree from the #1 ranked Russian university, to explore the new Master of Data and Network Analytics program from HSE on Coursera today!

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