Causal Academy is a platform focused entirely on education in causal inference. It is an initiative by CausAI, founded by Jamilla Cooiman, which has been dedicated to causal inference education since early 2024.
The platform was created to address a gap within the data industry: a lack of causal inference skills among data professionals.
Jamilla experienced this gap herself during her academic training in econometric and data science. Within both her BSc and MSc programmes, there was limited focus on explicit causal analysis techniques. This often created a disconnect between the modelling approaches she was trained in and the types of questions that are most relevant in applied business data science.
Over time, it became clear that this issue was not personal, but widespread. Many data scientists, analysts, and similar professionals have limited formal training in causal inference.
This gap arises for at least two reasons.
First, many educational programmes emphasize correlation-based modelling approaches, while causal inference receives more limited attention.
Second, causal inference material can be dense and fragmented, making it time-consuming to navigate independently for professionals working in business environments.
Both of these issues can be addressed through structured educational material in causal inference. Jamilla decided to contribute to closing this gap, with the aim of improving how data science is approached in practice.
To date, this has resulted in the development of more than 40 hours of course material and has reached over 1,500 learners globally through online education and in-company training. Causal Academy serves as the unified platform where these educational materials and trainings are brought together.
If you would like to learn more about the founder, you can connect with Jamilla Cooiman on LinkedIn here: