The most often questions about Data Science Bootcamp are related to the complexity and intensity of the program.
The answer to these questions lies in a block on the Bootcamp website entitled “No bullshit approach”. In other words, the program looks as it is, not to be easy, but to give a result.
And efficient results already arrived. We marked August with the completion of the student’s final projects from Group 1, and of course, the start of Group 4. But, we will close September even more triumphantly, because we have officially the first employment of the student from the Data Science Bootcamp!
Meet Nikola Nastev who recently signed his first professional contract with the Slovak company i.ERP working in the field of AI-powered Business Predictions.
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Brainster: Nikola, in one year, from a student at the Data Science Bootcamp you became a Junior Data Scientist at i.ERP. Congrats on your new job! How will you describe the whole process from your start on September 1, 2019, and finishing it with employment in an international company?
Nikola: Thanks for the kind words! The process for me started with the application for the Data Science Bootcamp. Even it was the first institution of this type of education in our country, one of the reasons for enrolling in the Bootcamp was the positive recommendations for Brainster that I received first hand. The other reason was the networking. To start a career in any digital skill, you first need to be surrounded by professionals in the field, colleagues, instructors, and finally, companies. That was crucial for me.
After the interview with the coordinators of the Bootcamp, I got great expectations. In the end, I have to confirm that they are completely fulfilled. The manner of the lectures and their pace is really intense, but the mentors were always there to help us to overcome even the most difficult challenges. I am especially pleased with the online way of working where I would single out the recording of lectures as the biggest benefit.
Brainster: It is known that the program of the Bootcamp is difficult and intensive. Did you really expect such fast progress in Data Science, considering that in addition to the new job, you already have several projects in your portfolio?
Nikola: If someone told me in the first class that after a year I will be employed in an international company, I would not believe him. But from this perspective, with all the effort I put into the lectures and the projects, honestly – I’m not surprised. On the contrary, even this is a completely expected outcome.
Here again, I would like to return to the Bootcamp’s instructors who flawlessly and maximally transferred their knowledge to us. But in the end, everything is in the student’s hands. It required a maximum commitment. My system was based on setting realistic goals throughout the program. What surprised me was the obvious progress, from module to module. When I look back on the whole program, I’m proud of everything I have achieved in just one year.
Brainster: i.ERP is a Bratislava company that develops software platforms for Ai Powered Business Predictions and works for clients such as Coca-Cola and Wurth. How did you first get this opportunity to enter the competition for employment in a company of this calibre?
Nikola: After completing the final projects, I was contacted by the management of the Bootcamp. They offered me the chance to have an interview with i.ERP. I know Brainster is working on many partnerships companies that can provide career opportunities for students at this Bootcamp, but I did not expect to be the first one. That’s why I’m so grateful to Brainster and the chance that I got because without them I would not be in the position that I am today.
Brainster: Nikola, you are a FINKI student with a background in programming that I believe helped you learn Python. From that perspective, how much harder or easier is it to master Python than other programming languages?
Nikola: The most attractive feature of Python, especially for beginners, is its syntax, high abstraction level, and a huge number of libraries. Without any prior programming knowledge, it is very easy to start programming effectively in Python, without worrying about all the inner workings and everything that goes on in the background. For people who are familiar with programming, or are already programmers, and have never written a single line of Python code, it will be very easy to master. As I said, the same goes for beginners. The “problem” will not be the programming language that will be used. It will be the mindset itself and the completely different kinds of problems that you will be faced every day. Therefore, I claim that anyone good at math, statistics or calculus will do well in Python programming.
Brainster: What exactly is the scope of your responsibilities at your new job? What exactly are you going to work on?
Nikola: I will work on various projects, for which it will need solutions to be built from Step 1 to a ready-made algorithm that meets the client’s requirements. The whole process from analyzing the obtained data, reprocessing according to the insights obtained from the analysis and then building an appropriate Machine Learning algorithm. The program I passed at the Bootcamp will be directly applicable to my new job.
Brainster: Working in real production comes with a lot of specifics and challenges. How much do you think that working on real projects at the Bootcamp will help you to deal with these challenges in the future?
Nikola: I think the most valuable part of the Bootcamp is the workshops that take place every Saturday. I even think they are a little underestimated. Although even these are not specific projects, we have been working on subcategories or parts from one project. This helped us to review and practice the content learned that week. Of course, these exercises are just preparation for the final project in the end. So when the final projects came, I felt ready for the problems that I might face. After dividing the problem into appropriate categories and tasks, we have already passed all those tasks in the workshops. What remained for us was to combine them into one complete project.
Brainster: In Macedonia, there still seems to be some scepticism about Data Science job opportunities. But in your case, it proves the opposite. In your opinion, what is the reason for this perception that there is not much work for Data Scientists?
Nikola: I think the scepticism about Data Science is because there is not enough staff. Until some time ago, the companies themselves did not venture to invest in these positions. But lately, according to Western trends, I see more and more demand for this kind of job opportunity. I would add that Data Science is still in its early stages as a discipline in Macedonia. It creates confusion among companies and potential staff. I’ve seen a lot of job advertisements looking for a Data Scientist, but they are basically looking for a Data Analyst. With the growing staff and the demand for Data Scientists, companies are starting to invest and have nicely defined positions.
Brainster: Let’s take another brief look at the program. The Machine Learning (ML) module has already been adopted as the most difficult. How much does it cost to “be dead tired of learning” in the last 6 months at the Bootcamp?
Nikola: Looking at this point where I am now after the “dead tired of learning” period, I would say that it definitely paid off :). However, ML is a huge field to study. Even I have finished, many more hours are waiting for me to be learning.
Brainster: Nikola, before we finish this conversation, once again, we wish you success and productivity in your new job. Finally, what would you recommend to anyone considering starting training in Data Science and the career opportunities that it offers?
Nikola: If you have an analytical mind and you want new challenges, I would highly recommend this Bootcamp. You will learn a lot of interesting things. You could further apply in a bunch of different areas, from medicine to the financial sector and in between, even in everyday life. Data Science is a field that will offer you a choice, to focus more analytically or more programmatically. Besides, one often overlooked benefit is that as a Data Scientist you can analyze your own habits, such as costs.
If you have ever thought about a future-proof career in Data Science, have a look at our remote Bootcamps.