ONLINE COURSE

Causal Inference for Data Science and Analytics

Foundations, Assumptions and Applications

15 weeks

COURSE DURATION

35

Videos

15

EXERCISES

15

QUIZZES

8h

VIDEO DURATION

3-5h per week

REQUIRED TIME TO COMPLETE

COURSE OVERVIEW

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.

WHY IS CAUSAL INFERENCE USEFUL?

Causal inference provides a 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.

WHAT IS THE FOCUS OF THE COURSE?

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 causal relationships.

WHO IS THE COURSE FOR?

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 analysis of causal relationships (Week 2).

ABOUT COURSE MATERIAL

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

ABOUT INSTRUCTOR

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.

ABOUT THE FLOW oF tHE cOURSE

This online course covers material of five academic weeks of in-person lessons. Due to an online implementation of the course and the deep-learning teaching approach that we use, it takes about 5 months to complete this course.

The Learn&Apply module consists of extra material, so those enroled to Learn&Apply module should add another month of time to complete this course.

The course consists of video lessons, exercises and quizzes. For each week’s curriculum you will need about 3 weeks to complete. An assistance from the instructor is available for all the exercises. The Learn&Apply module includes also online consultation hours with the instructor.

Upon successful completion of all the course activities, you receive a course certificate.

Who should take advantage of the Learn&Apply module?
This module is useful for those who want to apply the knowledge with their own project. This module offers extra material in terms of exercises and assignments linked to your project. The purpose of this extra material is to engage you in working on your project alongside the course. With more exercises and assignments you receive also more assistance from the instructor.
 

COURSE OUTLINE

By the end of this course you will develop the reasoning that is required in causal inference to design studies, analyse causal relationships and perform impact evaluations with experimental or observational data.

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, 3 exercises and 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, 3 exercises and 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, 3 exercises and 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, 3 exercises and 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, 3 exercises and 3 quizzes to complete.

COMMON QUESTIONS

You can access the course material for 12 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 material of the second week, and you will get full refund. The cancellation needs to be done in writing by emailing to admin@tarastats.com, the latest 30 days after enrolment.

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 to the Learn&Apply module of the course. 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 a maximum three extra consultation hours at 125€ per hour. If you are enroled in the Learn Independently module you can also purchase a maximum three extra consultation hours at 125€ per hour. If additional consultations with the instructor are still needed, further options are available.

What people say

Join us to learn about the hottest topic in today´s data world!

Are you ready to enrol?

This course runs three times per year. The current edition – Spring 2022 started on 3rd of March. The enrolment is open until the end of March 2022. Join us in learning how to analyse causal relationships in a scientifically objective way.

Learn & Apply

with your own project
1235
  • 35 Lessons, 15 Exercises, 15 Quizzes
  • Regular feedback from the course instructor
  • Feedback Space for Exercises and Quizzes
  • 3 Assignments related to your own project
  • 5 Exercises (additional) related to your own project
  • Feedback Space for Assignments and additional Exercises
  • 3 Online Consultation hours with the course instructor
  • COURSE CERTIFICATE

Approximate amount of time needed to complete the course in part-time study mode is about 6 months.

Learn Independently

with guided assistance
395
  • 35 Lessons, 15 Exercises, 15 Quizzes
  • Regular Feedback from the course instructor
  • Feedback Space for Exercises and Quizzes
  • COURSE CERTIFICATE

Approximate amount of time needed to complete the course in part-time study mode is 4-5 months.

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

stay tuned!

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