Causal Inference for Data Science and Analytics

Foundations, Assumptions and Applications











5-8 h per week



Because most questions are causal in their nature, it is important for data analysts and data scientists to become familiar with the foundations of cause and effect studies. Causal inference is a theoretical and methodological field of study that offers tools and  techniques to analyse causal relationships.


Causal inference provides the methodological foundation for impact evaluations, marketing interventions, and evidence-based policy developments, to name a few. Causal inference helps us in revealing subtle differences about which things work better and it provides foundational knowledge for the design and analysis of experiments.


The course provides an introduction to causal inference in terms of foundations, causal reasoning, scientific design and data analysis. The focus of this course is to develop understanding about the key concepts that influence the design and analysis of data when analysing in a causal effect way.


Those who like to solve real life problems by using tools that solve questions which are causal in their nature. The following groups are welcome:

1.Data scientists and analysts, regardless of whether you hold one of these roles by profession or in spirit.

2. Applied researchers in the social, behavioural and medical sciences.

2. Leaders and data entrepreneurs with keen interest in understanding the world of data-based decision-making.

No prior knowledge of statistics is required, although those who have some, will be able to review it when learning about the impact that statistical thinking has on causal effect studies (Week 2).


The course consists of videos, exercises and quizzes. Each week´s activities need to be completed in order to proceed with the next week classes. Upon successful completion of all the course activities, you receive a course certificate.


The material has been previously used for lectures, seminars and workshops at different venues, including University of Helsinki, Sigmund Freud University, Uppsala University and Tsinghua University.


Dr. Ana Kolar holds a PhD in Statistics with expertise in Causal Inference. Her PhD advisor and Causal Inference guru is one of the greatest applied statisticians of today – Dr. Donald B. Rubin, Emeritus Professor from Harvard University. Read more about Ana here.


This is a 5 weeks course. By the end of the course you develop the reasoning used in causal inference when designing studies and analysing data in a causal-effect fashion.

In the first week, we introduce the concept of causality as it is used in real life, philosophically and in data analysis. We explain the difference between physical and factual causes, and show the role that causal thinking has on the formulation of research questions, design and analysis of collected data.

7 videos of 12 minutes, 3 exercises, 3 quizzes to complete.

During the second week we learn about the scientific design in causal inference and about the importance of statistical thinking. We look at how crucial statistical thinking is for objective scientific designs and what are the ways to develop it.

7 videos of 12 minutes, 3 exercise, 3 quizzes to complete.

During the third week we look at the problem of bias and assumptions. We introduce different types of biases that can influence scientific design, analysis and conclusion making, and, we look at the impact that posing and justifying assumptions has on validity of obtained data insights.

7 videos of 12 minutes, 3 exercises, 3 quizzes to complete.

During the fourth week, we talk about a required knowledge to develop and implement an effective data collection strategy which guides an analysis of data in a causal-effect fashion. By introducing the required knowledge, we show common misconceptions about causal inference and causal effect studies.

7 videos of 12 minutes, 3 exercises, 3 quizzes to complete.

During our last, fifth week, we explain the difference between observational and experimental data, and show how to proceed with a causal-effect study when only observational data is available. We cover all the steps, from forming research questions, to posing assumptions and thinking of the ways to justify them.

We show how to think when designing such studies, as also how to think when analysing obtained data. We use real world examples from different impact evaluations that were used for further decision-making.

 7 videos of 12 minutes, 3 exercises, 3 quizzes to complete.


You can access the course material for at least 5 months from the day of enrolment. This access limitation is due to course material being regularly updated.

Yes, you can cancel the course anytime during your first week, or before accessing the material of the second week, and you will get full refund. The cancellation needs to be done in writing by emailing to, the latest 30 days after the course has started.

The Online Consultation Hour With The Instructor is available to clarify questions during your learning process. When you enrol for the course, you get access to an online consultation booking calendar where you select the time that suits you. To get the most out of this online consultation hour, we recommend that you send questions for which you need clarification  at least 72 hours before the consultation with the instructor. Details of where to send questions are provided once you enrol for the course.

ATTENTION! The Online Consultation Hour With The Instructor is complementary for those enroled as Early Bird and those enroled with the Learn&Apply bundle. Early Bird enrolment is offered three times per year. Check for the Early Bird offer below, or leave your email in the “Stay Tuned” section to be informed about the upcoming courses.

Is it possible to purchase consultation hours with the instructor during the course? Yes, but it is subject to availability. If your enrolment already includes a consultation hour with the instructor like with Early Bird and Lear&Apply enrolment, then you can purchase maximum three extra consultation hours at 85€ per 45 minutes. If you enrol as Learn Independently you can purchase your first three consultation hours at 95€ per 45 minutes.

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This course runs five times per year. Each edition of the course has a limited number of seats available. Below you can see the availability for the Autumn 2021 edition of the course.

Learn & apply with your own project

Online course + 3 online consultation hours with the instructor.

455 €



5 seats left

Online course with basic assistance from the instructor.

195 €

You will get access to the online course material 12 hours after enrolment. The prices include 24% VAT.

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