Develop foundational knowledge to analyse data in a scientifically objective way and unlock the full value that data holds.


Causal Inference for Data Science and Analytics Foundations, assumptions and applications

Because most questions of interest are causal in their nature, it is important for data scientists and data analysts to develop understanding about the key causal inference concepts. This is a foundational data science and analytics course.

Statistical Thinking for Data Science and AnalyticsA foundation for a scientifically objective data analysis

Statistical thinking is the key skill to analyse data in a scientifically objective way. The course takes you through the key statistical and non-statistical concepts to develop statistical thinking. This is a foundational data science and analytics course.

Causal Inference with Observational Data for Impact EvaluationsData requirements, methods and techniques

Most of today's data is observational. This course is a continuation of the course on causal inference, focusing on applications and thus the art of satisfying assumptions without which causal inference is a mission impossible.

Causal inference is the method of choice for impact evaluations, policy evaluations, evaluations of marketing interventions, clinical trials… It is the foundation for a design and analysis of experiments.

About our online courses

The courses are designed by following philosophy of experiential learning. The focus is to provide data practitioners (data analysts, data scientists, …) with foundations to design studies and analyse data in a scientifically objective way. We provide practical advice and scientific references for further learning.

About course material

Different parts of the material have been previously used for lectures, seminars and workshops at scientific conferences, business seminars and universities, such as University of Helsinki, Sigmund Freud University, Uppsala University and Tsinghua University.


Dr. Ana Kolar holds a PhD in Statistics with expertise in Causal inference and she is the creator of a new approach for developing statistical thinking skills. Ana is able to introduce complex topics in a simple manner and she is dedicated to an experiential educational and learning approach. She holds a postgraduate qualification in tertiary teaching and learning and has over 15 years of international professional experience in the fields of academia, statistics and research. Read more about Ana here.

We warmly invite data scientists and data analysts whether in industry, research or development agency, to learn with our online courses.