To utilize contemporary data-intensive solutions in your company or organization means to change its mindset, full stop. The epoch has changed. It is a change of modus operandi: those who change the way they think about their products and services will be those who will adapt to the new data-intensive environments. We offer a range of courses and workshops meant to empower you so that you can join us in this new conceptual framework.


[a 24 weeks in-depth Introduction to Data Science in R course]


This is a thorough, intensive, 24 weeks introductory course in R for Data Science. NOTE: This is not a self-paced course. People tend to lose their motivation too often in self-paced courses, typically as soon as they encounter problems that are difficult to solve by browsing the Internet alone. We do not do that in DataKolektiv. You will be working directly with Goran S. Milovanović, owner of DataKolektiv, expert Data Scientist, and full-stack R developer who provides analytics services for some of the most complex, big datasets in the World with more than 20 years of experience in Data Science and Analytics. And no, one cannot learn Data Science by investing 2 -3 hours of work weekly. The weekly workload here is: 3h of tuition, 1h labs, 1:1 sessions with the lecturer upon request monthly, and a minimum of 4h of individual work. Send your notification of interest to: goran.milovanovic@datakolektiv.com

This 24 weeks course has three objectives:

  1. Learn R programming, data visualizations, and reporting from R;
  2. Understand the fundamental concepts of Data Science starting from the elementary introduction to Probability and Statistics;
  3. Learn how to deliver more powerful models that solve real-world problems from R (like Generalized Linear Models and Random Forest).

This course provides a comprehensive introduction to Data Science in the programming language R for those who want to get a grasp on the contemporary data magic and its application but have no technical background in coding, computer science, or statistics. This is a practical course which provides a minimal but explicable and useful theoretical foundation for those who want to enter Data Science from a non-technical perspective and still become able to work efficiently in its highly technical context.

PREREQUISITES: You can use a computer and know how to search the Internet for information. This course is planned and ideally suited for

• Those with a non-technical background who are interested to start a career in IT/Digital: Product, HR, Marketing, Communications
• Non-tech employees in the IT industry (administration, marketing, HR etc)
• Students and scholars in social sciences, arts, and humanities
• Researches with a background in qualitative methods who wish to learn about quantitative analysis
• Developer and Software Engineers in other areas who wish to enter Data Science and Analytics

We will support you in anything that needs to be done during the course in any of the following operative systems: Windows, Linux Ubuntu/Debian, and macOS. If any of the projects that you would like to develop during the course need rely on heavy computations and/or memory use, we will provide the technical infrastructure to you and teach you how to manage it (up to 64Gb of RAM, half TB (that would be 500 GB) of disk usage, and up to 24 AMD cores for computation).

24 weeks of intensive learning and fun: understand the fundamental concepts and then translate your understanding into a useful R code.



Note. This workshop is always customized with respect to the nature and the needs of a particular business, team, or organization.
A mother of a demo and a definite intro. This is a technically non-intensive workshop designed for the non-technical part of your crew that needs to incorporate the contemporary data-oriented thinking and awareness into its everyday operations. Understand what data structures are, how they are produced and managed, and how do we utilize them to make business and organizational decisions. What do Data Scientists do to help improve business decisions and operations? How to communicate with techies without learning a word of any foreign (i.e. programming) language? How to recognize what aspects of a product or a project can be improved by utilizing data-intensive solutions?



Already an R developer, but there’s just that one thing that you still need in your arsenal to become awesome? Very good. Oh, not an R programmer at all, but there’s that one package that you need to understand and you still need help to fight through the basic structure of the language? We can help.
While we are a bit more enthusiastic about training full-scale R developers for Data Science, we can sometimes jump in the middle of your problem and try to help you find a way out. Only had you’ve done your homework!