The only real way of utilizing contemporary data-intensive solutions for any organization is to move them at the core of its operations. It is a change of modus operandi: those who change the way they think about their products and operations will be those who adapt to the new data-intensive environment. We offer a range of courses and workshops meant to empower you so that you can join us in a new conceptual framework from which we proceed together as an alliance towards your vision.

[NEW] Introduction to Data Science: Non-Technical Background
[R course]

Please send your notification of interest to: goran.milovanovic@datakolektiv.com

Review course material: DATA SCIENCE SESSIONS VOL.0 2020/21

Learn the rules like a pro, so you can break them like an artist
– a quote attributed to Pablo Picasso

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

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

Introduction to Data Management

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?

Advanced and High Performance R

Note. This course can be customized having in mind any specific needs and the level of the trainees’ previous knowledge.
For R programmers who are about to enter the realm of highly efficient, super-complicated, awesome R development. Prerequisite: a very good understanding of the topics covered in our Introduction to Data Science in R course. Learn how to parallelize the execution R code, efficiently process big datasets in-memory, interact with databases and APIs, the packages that you need to transform your toy ML solutions models to real monsters, and many more frightening things. No off-the-shelf solutions, the real thing, real datasets, real infrastructures.
Ten weeks, high-intensity training, real, only real, and nothing but a real Data Science experience.

Advanced Data Structures and Visualizations in R

Beyond data wrangling: from graphs to dataframes and back, JSON, XML, RDF, RDF/XML, XPATH, all imaginable serializations, parsing API responses and transferring to R structures suitable for analysis and visualization, enter databases, exit databases, do data.table, advanced object structures, design patterns, formatting data for advanced visualizations, scrape from websites, and many more.
Handle your data like a pro up to the level where yours is whatever is online and whatever unknown file extension it might have.
Six to ten weeks, depending upon the course customization. Highly intensive.

Front-end in R for Data Science

Design Shiny Dashboards, flexdashboards, and interactive Rmarkdown reports. Learn the most advanced interactive visualizations present in the R ecosystem. A systematic intro to reporting and reactive design for Data Science is provided along the way. A touch of aesthetics on top of your heavy AI/ML machinery.
Ten weeks. Very difficult.

Custom R Training

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!