Valentina Đorđević

Valentina Djordjevic is a huge Data Science enthusiast. Graduating from the Faculty of Organizational Sciences, she faced the challenge of packing her (then irreconcilable) interests into a unique career path-cutting machine. Still, she is a real "fox" when it comes to her areas of interest, so we have no doubt that this has given her good signposts. Valentina finds motivation in challenging projects and in working with equally enthusiastic team members. She believes that working on the Data Science challenges helps her to continually grow, examine (her) boundaries, and develop her imagination. Still, she has not yet determined whether the fact that she has never solved the same problem in exactly the same way is a good or bad thing. She hopes her colleagues, or maybe someone in the community, will help her finally come up with the correct answer.
Applied business

My team, my motivation

Monday, 10:00am. I am entering the office where the regular weekly Leadership Community (LC) team meeting is held. As usual, we start the meeting by checking in. The first time we did the check in,

Applied business

Agile and Data Science as a perfect match?

As I got familiar with the agile manifesto methodology a few months ago – agile values and principles, the most interesting thing for me was to think about its application within Data Science projects. The

Applied business

Data Science in Marketing

In the previous posts, we got introduced with Data Science and some of the most famous use cases from the industry leaders. In our future posts, we will talk about the applications in specific industries.

Applied business

Machine learning in Business

“A field of study that gives computers the ability to learn without being explicitly programmed”. That is how Arthur Samuel defined machine learning by the end of the 1950s. As one of the pioneers in

Applied business

Data Science in Business

In my previous post, I have tried to explain the evolutionary process of Data Science. Since it is a broad discipline, in regards to the context of the defined problem, Data Science may include several

Applied business

Data Science & co.

Unless you have spent the last ten years trapped into the deep cave surrounded by nothing else but darkness – the chances are you have heard of Data Science. You may have even tried to

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