The first group of the Academy of Data Science is advancing at a high pace.
The key factor in shaping the experience of the Bootcamp is our team of instructors, composed of top experts from several industries. We shift the focus to the “teachers”. We had a nice chat with Blagoj Kostovski (SQL, Data Warehouse), a Data Science Instructor at Brainster Vienna. He is a Tech Lead at Seavus with over 15 years of experience in data design and implementation and administration in MS SQL Server.
Find out about Blagoj’s impressions from the Bootcamp so far and what awaits us next.
Brainster: We have just finished the SQL / Data Warehouse modules. Blagoj, given the further schedule, how important is it to master SQL solidly, at the beginning of the Bootcamp?
Blagoj: Every Data Scientist must have a detailed knowledge of the data, that he works with. SQL as a language offers the ability to analyze a dataset, its meaning, structure, and interrelationship.
With the help of SQL, we can easily process and format the data and easily identify the missing data. And further, through filtering, aggregation, and sorting, we get a detailed picture of their distribution and organization.
Relational databases and data warehouses are the most common data source we use in Data Science projects. So SQL is one of the basic languages that every Data Scientist should learn.
Brainster: Blagoj, how satisfied are you with the students’ learning of your modules?
Blagoj: The group has progressed beyond all expectations. Many students have already many years of experience working with business applications. In their daily work, they often use Excel for data processing.
Although SQL as a language was something new for them, students in a relatively short period mastered the basic principles of working with this technology. We start to build a new database related to banking, a business model that was already known to them. By building this database, students learned the principles of data creation, processing, and analysis.
We worked with publicly available databases. Students could apply the acquired knowledge to a more complex domain, and extract relevant information on which they will base future business decisions. The data prepared in this way is a good basis for what students will do on the Power BI module.
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Brainster: Wide application, high demand, and high wages are just some of the benefits of Data Science. Is the situation in our country different compared to the United States? What do you think about the Data Science scene in our country?
Blagoj: I believe that with incapacity and ability we do not lag behind the more developed countries.
If we look holistically, the problem in our country is the application of Data Science and the lack of sufficient projects in this area. Those companies that have caught up with the transformation are already building BI and Data Science teams in-house. They do not rely on the expertise of foreign companies. Thus, as we produce quality staff in Data Science, the number of projects and companies that will incorporate will increase proportionally.
Brainster: What is the career key in Data Science? What are the basic predispositions in your opinion?
Blagoj: Priority, analytical thinking. It’s not bad any previous experience in data working. I would especially emphasize the desire to solve problems and perseverance. After proper and quality training, I think it is necessary to work on real projects where the acquired knowledge can be applied.
Brainster: What do you think will be a challenge for the students during the Bootcamp?
Blagoj: The duration of the Bootcamp, and the required focus in the entire period of 8 months. We did not create the program to be easy but to be effective. We have covered everything we think a modern Data Scientist should know. From here, it can be said that learning several different areas and the need for students to adapt to the material is an additional challenge.
Brainster: What is your message to all candidates for the next Bootcamp of Data Science and in general all interested in a career in this profession?
Blagoj: Full commitment to learning in the future and develop a mindset for lifelong learning because the work in Data Science is never finished. And of course, a vision of how they should apply the acquired knowledge after graduating from the Bootcamp.
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