Graduate of MSAI 2023, data analyst at a resident company of the Skolkovo Innovation Technology Cluster. Alina has been working on predicting driver behavior on toll roads, personalizing pricing, creating loyalty programs, and more. The master's program enabled her to master new tools for solving more complex professional tasks.

What did you like most about the program?
Most importantly, I was able to fill major gaps in areas where I had previously lacked knowledge, which would have been difficult to fill elsewhere. I acquired the necessary foundation to understand what to build on and where to delve deeper. I've even been able to implement some things directly in my work to see how they function in practice. It's great that all lectures remain accessible, and I can return to them even after graduation. This is a completely different level of knowledge transfer compared to when we were studying face-to-face; if you're not in class and you don't write everything down, then it's lost to you forever. I still review the MSAI lectures when I need to clarify something or study more deeply to solve work tasks. Another pleasant aspect was our study group. We still communicate and support each other as people with common interests and aspirations, as like-minded individuals. We had a real spirit of studentship and mutual support, despite the fact that the program was online and we mostly saw each other through a screen. And of course, I am very grateful to the teachers—they always supported us throughout the learning process and helped us get started and carry out our own projects. I really liked my final project, which was focused on malfunctions based on audio data in autonomous vehicles. It was very interesting to delve into the topic, gain this valuable experience, and ultimately achieve a really good result in the form of a diploma. Now I'm looking forward to more large-scale and interesting personal projects in the field—I'm striving towards that.

What aspects of the program or the study experience would you like to improve?
I would like more work on errors after major homework assignments, especially laboratory works. They were creative; there was no right or wrong answer—you do as you think, as you come up with. And because of this, I would have liked a more detailed analysis of the outcomes at the end, although I understand that it’s impossible to devote so much time to each student. But it could have been very useful for us.

What advice would you give yourself if you were just starting the program?
Stock up on patience and believe in yourself! And, of course—secure the support of loved ones because your master's degree affects not just you but your entire family, really. Everyone has their own family responsibilities, and you need to be ready to either delegate them if you have to sit over your studies all weekend, for example, or be confident that they’ll be taken care of and that you’ll be supported.

Graduate of MSAI, 2023, is currently job searching in the field of voice technologies. Before entering the master’s program, she worked at the company Mercedes as a manager for manufacturing and logistics processes. The program helped her master a technical specialty and find her area of interest in the field of artificial intelligence.

Why did you decide to pursue a master's degree and learn a new direction?
I wanted a technical education. I love mathematics, and my first degree was in economics, but it didn’t allow me to delve into the exact sciences. At some point, sitting at work, I realized that I liked optimizing and automating things and that many manufacturing and logistics processes could be made faster and more efficient with the help of artificial intelligence. That’s when I went looking for a suitable program and found MSAI.

How did MSAI help you choose the direction you would like to pursue in the near future?
There’s a little story connected with this as well. Last autumn, when I was thinking about my final project for the master's program, I decided to attend a Yandex conference where a very talented and smart guy was speaking to the audience. He was the winner of several intellectual and technological competitions and clearly had a lot to tell the audience. But he had a problem – he stuttered, and almost no one listened to him because his speech was hard to perceive, and he felt even more uncomfortable because of it. Then I thought: "It would be great if people like him could freely share their ideas with a large audience and perform on stage despite their physical limitations." Some people cannot overcome stuttering for their entire lives, no matter how hard they try. And this defect can significantly hinder them both psychologically and socially. Then I decided to approach my academic advisor and propose a project on voice cloning. The idea is that to correct someone's speech, you just need to take their voice and create a technology that could mimic it by hiding the stuttering moments so that in the end, you get a clean, understandable, and logically structured statement. Such technologies are already used in some voice assistants to make their responses clearer and more logical, but there is still much to learn and develop in this area to ensure flawless cloning results. Now I am thinking about how to properly apply all the knowledge I received during the program and while preparing my final project. They have sufficient commercial and inclusive potential, so I will be able to choose the area that seems most interesting to me.

What advice would you give yourself if you had just entered MSAI?
The main advice is to make the most of these two years. This is the time you need to dedicate to studying because it gives you the opportunity to grow as a specialist in a new field and acquire knowledge you probably wouldn't get anywhere else.

Graduate of MSAI, 2022, works at Yandex on the development of autonomous vehicles, focusing on computer vision. He previously completed a bachelor’s degree in law and worked as a lawyer for several years. Thanks to MSAI, he was able to radically change his profession and find his place in one of the most promising areas of the technology industry.

How did the program help you reach new heights professionally?
I started working at Yandex while I was still studying. Initially, I joined a team that was developing "Drive"—a car-sharing service with many opportunities for implementing machine learning. Later, I switched to autonomous vehicles and now work on computer vision. In this sense, I never questioned the relevance of the subjects taught at MSAI—I always saw their practical significance in what I am doing or planning to do. Even now, all these things that I acquired there prove useful for me daily, despite our program being very intense and the subjects diverse. The most telling moment, I think, is that I work in my profession using what I know well. I was never told, "Forget everything you learned at university"—instead, I understand that I know everything necessary and feel confident professionally.

What would you like to improve looking back at your student experience after graduation?
I disliked that it was very tough to combine work and study. Who would like that? I would have preferred it to be the same but easy! But no, I was almost deprived of any free time because on one hand, I was mastering the basics, which I sometimes lacked, and on the other, I was digging deeper, wanting to reach things that would give me the maximum understanding of the field.

What advice would you give yourself if you were just starting the program?
None! Overall, I am very pleased with myself because I really spent a lot of time and effort mastering the program. The only thing I might say to myself is: "You will often feel uncomfortable because you don't know something, and that's okay. It will be worth it."

Graduate of MSAI (2023) working in Infosys Limited which is the second-largest Indian IT company that provides business consulting, information technology and outsourcing services. Currently Bharani is searching for a PhD program in Computer Science in universities across the world to continue mastering machine learning.

Why did you make a decision to enter MSAI and develop new skills there?
Actually, since the pandemic I had a lot of free time because traveling was a completely closed option for me and I didn’t have to work in the Infosys office in Chennai. And I thought: “Okay, why not use this spare time in a fruitful manner, why not study something?”. That’s why I started looking for some online courses and programs.


At the beginning I didn’t have the aim to get a master's degree in Computer Science but slowly I started learning some basics in data science and machine learning and understood that it was worth studying on a full time basis. MSAI caught my attention on Mastersportal and I decided to enter MSAI basically because of three things.

• The first reason is the MIPT brand, it has a great name in the global academic environment. Even now after graduation it helps me with my PhD application because everyone understands that the master program in MIPT is not a joke.
• The second one is the MSAI curriculum that I really liked. It was quite structured and flexible in comparison with other programs and courses.

And the last one is the affordable cost of the program. I just saved some money from my work and invested it in education because it is the greatest investment that you can ever make. Education is something that nobody can take away from you.

How was studying on MSAI for you?
First of all, I was never an alien in the program. Although I don't know Russian, the professors have made sure that they always communicated in English when I was in the webinar room.
Concerning studies, I had to take some additional courses in basic math and programming in Python before MSAI because they are essential for mastering machine learning. However, those courses were not enough because MIPT has a high standard of knowledge which is, on the one hand, great for students but, on the other hand, could be quite difficult. It was not easy for me too but professors were really helpful, so I could always ask any doubts, get a response and a helping hand. Besides, there were a bunch of different projects and assignments that helped to understand even more and go deep in the field.

What else did you like about the program or among things related to it?
The fact that the curriculum is structured so that at the beginning students could get acquainted with basics of machine learning, software development with Python and optimization in the first year and only then have a deep dive into applications of deep learning, computer vision, NLP and so on. So, after three semesters of the program students can feel that they come out with much knowledge of computer science and it enables them to make an informed decision about their thesis topic. So, I think it’s really appreciable that you don’t jump from subject to subject, but gradually go deeper into each one.

Besides, I liked the possibility of taking some more courses in order to master something on an advanced level. It wasn’t compulsory for everyone, in my case, for example, I took only digital signal processing (DSP) as an elective and this course was included in my diploma.

And one more cool thing is the fact that we got some bonus lectures because of dynamic changes in the IT industry. In the third semester, for example, we had three more lectures because it was time when Chat GPT came out. Just in order to know that we were not missing the news our professor gave us some extra classes dedicated to large language models (LLM). It was not a part of the curriculum and he could have told us “okay, learn it yourselves if you want”, but he did not. It was really appreciable!