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A Crash Course in Causality:  Inferring Causal Effects from Observational Data

A Crash Course in Causality: Inferring Causal Effects from Observational Data

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8.9/10 (Our Score)
Product is rated as #51 in category Data Science

We have all heard the phrase “correlation does not equal causation.” What, then, does equal causation? This course aims to answer that question and more! Over a period of 5 weeks, you will learn how causal effects are defined, what assumptions about your data and models are necessary, and how to implement and interpret some popular statistical methods. Learners will have the opportunity to apply these methods to example data in R (free statistical software environment). At the end of the course, learners should be able to: 1. Define causal effects using potential outcomes 2. Describe the difference between association and causation 3. Express assumptions with causal graphs 4. Implement several types of causal inference methods (e.g. matching, instrumental variables, inverse probability of treatment weighting) 5. Identify which causal assumptions are necessary for each type of statistical method So join us…. and discover for yourself why modern statistical methods for estimating causal effects are indispensable in so many fields of study! The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth–oldest institution of higher education in the United States, and considers itself to …

Instructor Details

Dr. Roy is Professor and Chair of Biostatistics and Epidemiology at Rutgers University. He is Adjunct Professor at the University of Pennsylvania, and is Co-Director of the Center for Causal Inference at Penn. Dr. Roy received his PhD from the University of Michigan in 2000. Areas of Expertise: - Causal inference - Missing data - Bayesian methods - Pharmacoepidemiology Major Works: Kim C, Daniels MJ, Marcus BH, Roy JA. A framework for Bayesian nonparametric inference for causal effects of mediation. Biometrics. 2016 Aug 1. doi:10.1111/biom.12575. Roy J, Lum KJ, Daniels MJ. A Bayesian nonparametric approach to marginal structural models for point treatments and a continuous or survival outcome. Biostatistics. 2017 Jan;18(1):32-47.

Specification: A Crash Course in Causality: Inferring Causal Effects from Observational Data

Duration 27 hours
Year 2017
Level Intermediate
Certificate Yes
Quizzes Yes

96 reviews for A Crash Course in Causality: Inferring Causal Effects from Observational Data

4.4 out of 5
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  1. Avatar

    FKG

    The material is great. Just wished the professor was more active in the discussion forum. Have not showed up in the forum for weeks. At least there should be a TA or something.

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  2. Avatar

    Mark F

    I really enjoyed this course, the pace could be more even in parts. Sometimes the pace could be more even and some more books/reference material for further study would be nice.

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  3. Avatar

    Pichaya T

    Excellent courses. I gain my expectations.

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  4. Avatar

    Vikram R

    Great course for getting your hands dirty with some real causal methods.

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  5. Avatar

    Miguel B

    Excellent course! The lectures are very clear and easy to follow, and Professor Roy is really good at explaining the concepts in a simple way. The assignments in R are helpful for grasping the theoretical concepts. I would specially recommend this course to data scientist, who might be interested in complementing their predictive analytics skills with the the necessary ones to tackle questions about causality.

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  6. Avatar

    Rudy M P

    I learned the basics of causality inference and want even more now!

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  7. Avatar

    Miguel B

    Excellent course! The lectures are very clear and easy to follow, and Professor Roy is really good at explaining the concepts in a simple way. The assignments in R are helpful for grasping the theoretical concepts. I would specially recommend this course to data scientist, who might be interested in complementing their predictive analytics skills with the the necessary ones to tackle questions about causality.

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  8. Avatar

    Rudy M P

    I learned the basics of causality inference and want even more now!

    Helpful(0) Unhelpful(0)You have already voted this
  9. Avatar

    Vlad V

    One of the best courses in Coursera, Professor with lots of experience in a backpack show how to tackle very complex problem of causal inference. This is a topic every data analyst should know doesn’t matter which industry you work or learn.

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  10. Avatar

    Vlad V

    One of the best courses in Coursera, Professor with lots of experience in a backpack show how to tackle very complex problem of causal inference. This is a topic every data analyst should know doesn’t matter which industry you work or learn.

    Helpful(0) Unhelpful(0)You have already voted this
  11. Avatar

    Ignacio S R

    The course is ok, but not having access to the slides is very annoying

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  12. Avatar

    Ignacio S R

    The course is ok, but not having access to the slides is very annoying

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  13. Avatar

    Manuel A V S

    I have an economics background and during my undergraduate studies I took several statistics and econometric courses. The contents delivered in this course complemented my knowledge very well from another point of view. I would definitely enjoy a more advanced course dealing with other methods. The only aspect I would improve is providing the slides for further study. Other courses in Coursera do this and, honestly, I often consult the slides.

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  14. Avatar

    Manuel A V S

    I have an economics background and during my undergraduate studies I took several statistics and econometric courses. The contents delivered in this course complemented my knowledge very well from another point of view. I would definitely enjoy a more advanced course dealing with other methods. The only aspect I would improve is providing the slides for further study. Other courses in Coursera do this and, honestly, I often consult the slides.

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  15. Avatar

    Andrew

    This course is really fantastic for all levels. Very thorough explanations and helpful illustrations. Many thanks for putting this together!

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  16. Avatar

    Andrew

    This course is really fantastic for all levels. Very thorough explanations and helpful illustrations. Many thanks for putting this together!

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  17. Avatar

    Arka B

    gives thorough basic intro to causal inference

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  18. Avatar

    Arka B

    gives thorough basic intro to causal inference

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  19. Avatar

    Akash G

    Amazing Course! Really Helpful. I would love to have a similar full duration course 😀

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  20. Avatar

    Akash G

    Amazing Course! Really Helpful. I would love to have a similar full duration course 😀

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  21. Avatar

    Patrick W D

    Excellent course. Could use a small restructuring, as I had to go through the material more than once, but otherwise, very good material and presentation.

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  22. Avatar

    Patrick W D

    Excellent course. Could use a small restructuring, as I had to go through the material more than once, but otherwise, very good material and presentation.

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  23. Avatar

    Chris C

    Could use a bit more guidance on the projects, but overall a helpful course. Gets straight to the point.

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  24. Avatar

    clancy b

    no nonsense, in depth and practical

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  25. Avatar

    Chris C

    Could use a bit more guidance on the projects, but overall a helpful course. Gets straight to the point.

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  26. Avatar

    clancy b

    no nonsense, in depth and practical

    Helpful(0) Unhelpful(0)You have already voted this
  27. Avatar

    Bob K

    Well taught, easy to follow but potentially very important techniques

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  28. Avatar

    Bob K

    Well taught, easy to follow but potentially very important techniques

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  29. Avatar

    Manuel F

    Interesting introductory course about causality. Good “compilation” in just 5 weeks. Thanks!

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  30. Avatar

    Manuel F

    Interesting introductory course about causality. Good “compilation” in just 5 weeks. Thanks!

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  31. Avatar

    Wei F

    This course is quite useful for me to get quick understanding of the causality and causal inference in epidemiologic studies. Thanks to Prof. Roy.

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  32. Avatar

    Wei F

    This course is quite useful for me to get quick understanding of the causality and causal inference in epidemiologic studies. Thanks to Prof. Roy.

    Helpful(1) Unhelpful(0)You have already voted this
  33. Avatar

    Mateusz K

    I enjoyed the course and learned basics of causal inference. What I missed was more exercises with R in order to gain more practical understanding of the material. In particular, it would be great to have exercises where you get some dataset and your task is to calculate given causal effect and you need to come up with an approach and to execute it. This would mimic more closely problems that you encounter in practice.

    Helpful(2) Unhelpful(0)You have already voted this
  34. Avatar

    Mateusz K

    I enjoyed the course and learned basics of causal inference. What I missed was more exercises with R in order to gain more practical understanding of the material. In particular, it would be great to have exercises where you get some dataset and your task is to calculate given causal effect and you need to come up with an approach and to execute it. This would mimic more closely problems that you encounter in practice.

    Helpful(2) Unhelpful(0)You have already voted this
  35. Avatar

    Michael N

    Content was useful for understanding causal inference in a variety of situations. Presentation was sometimes slow even on double speed. Lectures were generally structured from abstract to concrete, which was much harder to follow than if it were presented in english first and then made abstract (Mayer, 2009).

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  36. Avatar

    Michael N

    Content was useful for understanding causal inference in a variety of situations. Presentation was sometimes slow even on double speed. Lectures were generally structured from abstract to concrete, which was much harder to follow than if it were presented in english first and then made abstract (Mayer, 2009).

    Helpful(0) Unhelpful(0)You have already voted this
  37. Avatar

    Alejandro A P

    very good content. Story line is highly concise. However, Lecturer could be more stream lined the the way of explaining. He sure is a skilled guy, however.

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  38. Avatar

    Alejandro A P

    very good content. Story line is highly concise. However, Lecturer could be more stream lined the the way of explaining. He sure is a skilled guy, however.

    Helpful(0) Unhelpful(0)You have already voted this
  39. Avatar

    Christopher R

    I thought this was a good overview and I’m glad I took the course, but I would have preferred more hands on programming assignments.

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  40. Avatar

    Christopher R

    I thought this was a good overview and I’m glad I took the course, but I would have preferred more hands on programming assignments.

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  41. Avatar

    HEF

    The content is relaxing and easy to understand, yet extremely useful in real life when you are conducting experiments. The well designed quiz each week only takes a little time, but could help you to diagnose problems and remember the key points. I really love this course.

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  42. Avatar

    HEF

    The content is relaxing and easy to understand, yet extremely useful in real life when you are conducting experiments. The well designed quiz each week only takes a little time, but could help you to diagnose problems and remember the key points. I really love this course.

    Helpful(0) Unhelpful(0)You have already voted this
  43. Avatar

    Naiqiao H

    The course is very useful for beginners. The materials are clear and easy to understand.

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  44. Avatar

    Naiqiao H

    The course is very useful for beginners. The materials are clear and easy to understand.

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  45. Avatar

    Wayne L

    Very easy to follow examples and great coverage for such an important topic! The delivery sometimes get repetitive and I wish we talked more about how the uncertainties are derived.

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  46. Avatar

    Wayne L

    Very easy to follow examples and great coverage for such an important topic! The delivery sometimes get repetitive and I wish we talked more about how the uncertainties are derived.

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  47. Avatar

    Cameron F

    Good course on the over view of Causality. Not too technical, but not too light and fluffy.

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  48. Avatar

    Cameron F

    Good course on the over view of Causality. Not too technical, but not too light and fluffy.

    Helpful(0) Unhelpful(0)You have already voted this
  49. Avatar

    Xisco B

    Very interesting studies.

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  50. Avatar

    Xisco B

    Very interesting studies.

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  51. Avatar

    Leihua Y

    Over all, this course is extremely helpful for students who are interested in causal inference of observational data. It provides a rather comprehensive list of methods and techniques that we could use to disentangle causal effects, provided with ample supply of exercises and tests. Highly recommended! Will definitely take other courses on similar topics with the same instructor.

    Helpful(0) Unhelpful(0)You have already voted this
  52. Avatar

    Leihua Y

    Over all, this course is extremely helpful for students who are interested in causal inference of observational data. It provides a rather comprehensive list of methods and techniques that we could use to disentangle causal effects, provided with ample supply of exercises and tests. Highly recommended! Will definitely take other courses on similar topics with the same instructor.

    Helpful(0) Unhelpful(0)You have already voted this
  53. Avatar

    Vikram M

    Good introductory course. I wish there were more quizzes (at least another 2 more), testing our knowledge of various formulae for computing IPTW (inverse probability of treatment weights), ITT (intent to treat) and at least one more lab in R

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  54. Avatar

    Francisco P

    Hard to understand

    Helpful(0) Unhelpful(0)You have already voted this
  55. Avatar

    Vikram M

    Good introductory course. I wish there were more quizzes (at least another 2 more), testing our knowledge of various formulae for computing IPTW (inverse probability of treatment weights), ITT (intent to treat) and at least one more lab in R

    Helpful(0) Unhelpful(0)You have already voted this
  56. Avatar

    Francisco P

    Hard to understand

    Helpful(0) Unhelpful(0)You have already voted this
  57. Avatar

    Ruixuan Z

    Some of the materials are bit academical and away from industry, however, I found most of the materials relevant and practical.

    Helpful(0) Unhelpful(0)You have already voted this
  58. Avatar

    Ruixuan Z

    Some of the materials are bit academical and away from industry, however, I found most of the materials relevant and practical.

    Helpful(0) Unhelpful(0)You have already voted this
  59. Avatar

    Michael S

    Awesome!!! Looking forward to the next one!!!

    Helpful(0) Unhelpful(0)You have already voted this
  60. Avatar

    Michael S

    Awesome!!! Looking forward to the next one!!!

    Helpful(0) Unhelpful(0)You have already voted this
  61. Avatar

    olufemi B o

    The course itremendoulsy straightened my knowledge of causal evaluation

    Helpful(0) Unhelpful(0)You have already voted this
  62. Avatar

    olufemi B o

    The course itremendoulsy straightened my knowledge of causal evaluation

    Helpful(0) Unhelpful(0)You have already voted this
  63. Avatar

    Ted L

    Well structured to provide solid understanding of fundamentals, good intuition, and a basic view of applying the covered material.

    Helpful(0) Unhelpful(0)You have already voted this
  64. Avatar

    Ted L

    Well structured to provide solid understanding of fundamentals, good intuition, and a basic view of applying the covered material.

    Helpful(0) Unhelpful(0)You have already voted this
  65. Avatar

    Benjamin R

    I work in the field of Marketing, in a company that is actively exploring Causal Inference methods to estimate the impact of ads on the purchase behaviour. This course provided me with a solid understanding through illustrations and examples. This has changed my perception that experiments are the only answer to tease out a causal effect. Thank you Jason.

    Helpful(0) Unhelpful(0)You have already voted this
  66. Avatar

    Benjamin R

    I work in the field of Marketing, in a company that is actively exploring Causal Inference methods to estimate the impact of ads on the purchase behaviour. This course provided me with a solid understanding through illustrations and examples. This has changed my perception that experiments are the only answer to tease out a causal effect. Thank you Jason.

    Helpful(0) Unhelpful(0)You have already voted this
  67. Avatar

    Stephen M D

    After reading Pearl’s book, Causal Inference in Statistics, I found this course really put some meat on the bones, reviewing the basics and demonstrating, in a very clear and easy to understand way, how to conduct the analyses and make causal inferences. The examples in R were reasonably easy to follow and reproduce even for someone who has not used R (me).

    Helpful(0) Unhelpful(0)You have already voted this
  68. Avatar

    Stephen M D

    After reading Pearl’s book, Causal Inference in Statistics, I found this course really put some meat on the bones, reviewing the basics and demonstrating, in a very clear and easy to understand way, how to conduct the analyses and make causal inferences. The examples in R were reasonably easy to follow and reproduce even for someone who has not used R (me).

    Helpful(0) Unhelpful(0)You have already voted this
  69. Avatar

    Luca A

    A clear and straight to the point introduction to causality. I’m really enjoying the course!

    Helpful(0) Unhelpful(0)You have already voted this
  70. Avatar

    Luca A

    A clear and straight to the point introduction to causality. I’m really enjoying the course!

    Helpful(0) Unhelpful(0)You have already voted this
  71. Avatar

    Eva Y G

    Can not download slides which make the source material very inaccessible

    Helpful(0) Unhelpful(0)You have already voted this
  72. Avatar

    Eva Y G

    Can not download slides which make the source material very inaccessible

    Helpful(0) Unhelpful(0)You have already voted this
  73. Avatar

    Juan M C B

    Great

    Helpful(0) Unhelpful(0)You have already voted this
  74. Avatar

    Juan M C B

    Great

    Helpful(0) Unhelpful(0)You have already voted this
  75. Avatar

    Marriane M

    Very practical for beginners in causal inference

    Helpful(0) Unhelpful(0)You have already voted this
  76. Avatar

    Marriane M

    Very practical for beginners in causal inference

    Helpful(0) Unhelpful(0)You have already voted this
  77. Avatar

    Marko B

    Clear course most of the time and a very interesting subject. The teacher covers the concepts from many angles: conceptual understanding, math, examples and R code. I like how there is little “fluff”, you learn a lot for the time given and I don’t feel any of the concepts covered are unnecessary or esoteric. The only negative is that the course could’ve benefited from more practical assignments. There are 2 R code assignments: could’ve been more. I was thinking about giving it a 5 or 4 stars and decided on 4 in case a non perfect score actually makes the instructor improve the course.

    Helpful(0) Unhelpful(0)You have already voted this
  78. Avatar

    Marko B

    Clear course most of the time and a very interesting subject. The teacher covers the concepts from many angles: conceptual understanding, math, examples and R code. I like how there is little “fluff”, you learn a lot for the time given and I don’t feel any of the concepts covered are unnecessary or esoteric. The only negative is that the course could’ve benefited from more practical assignments. There are 2 R code assignments: could’ve been more. I was thinking about giving it a 5 or 4 stars and decided on 4 in case a non perfect score actually makes the instructor improve the course.

    Helpful(0) Unhelpful(0)You have already voted this
  79. Avatar

    Alfred B

    Overall a great course. Better than other courses on causal inference on coursera. However, some of the topics (e.g. within the IPTW and IV methodologies ) were presented in a sort of general manner (intuitive). Which is obviously not a fault of the instructor and is due to the strong research nature of these topics. Personally, I can’t think of presenting, for instance, 2SLS or insights on IPTW in more detail within a crash course. Perhaps, increasing the number of weeks to 6 or 7 in order to include more detail on, e.g. 2SLS would be a good idea. What definitely helped to make up for those missed details is the practical examples parts with R. Keep up the good job!

    Helpful(0) Unhelpful(0)You have already voted this
  80. Avatar

    Alfred B

    Overall a great course. Better than other courses on causal inference on coursera. However, some of the topics (e.g. within the IPTW and IV methodologies ) were presented in a sort of general manner (intuitive). Which is obviously not a fault of the instructor and is due to the strong research nature of these topics. Personally, I can’t think of presenting, for instance, 2SLS or insights on IPTW in more detail within a crash course. Perhaps, increasing the number of weeks to 6 or 7 in order to include more detail on, e.g. 2SLS would be a good idea. What definitely helped to make up for those missed details is the practical examples parts with R. Keep up the good job!

    Helpful(0) Unhelpful(0)You have already voted this
  81. Avatar

    Jiacong L

    I learned so much from Dr. Roy by watching his great lectures. Thank you!

    Helpful(0) Unhelpful(0)You have already voted this
  82. Avatar

    Jiacong L

    I learned so much from Dr. Roy by watching his great lectures. Thank you!

    Helpful(0) Unhelpful(0)You have already voted this
  83. Avatar

    Andrew L

    Clear deliver of engaging content. Very disappointed the course lacked an IV program or some capstone to evaluate learning. Why would you complete the course with a quiz compared to a practical assignment. I also do not understand why the slides are not available.

    Helpful(0) Unhelpful(0)You have already voted this
  84. Avatar

    Andrew L

    Clear deliver of engaging content. Very disappointed the course lacked an IV program or some capstone to evaluate learning. Why would you complete the course with a quiz compared to a practical assignment. I also do not understand why the slides are not available.

    Helpful(0) Unhelpful(0)You have already voted this
  85. Avatar

    KATONA N P

    Taking this course was a great help for me in my work. I was familiar with most of the matching methods but learning about other preprocessing methods and approaches really widened my view on how to decide what is the best way to do causal analysis on observational data. Thank you for using examples also from the field of social sciences. All in all, thank you for making this course!

    Helpful(0) Unhelpful(0)You have already voted this
  86. Avatar

    KATONA N P

    Taking this course was a great help for me in my work. I was familiar with most of the matching methods but learning about other preprocessing methods and approaches really widened my view on how to decide what is the best way to do causal analysis on observational data. Thank you for using examples also from the field of social sciences. All in all, thank you for making this course!

    Helpful(0) Unhelpful(0)You have already voted this
  87. Avatar

    Aniket G

    Superb crash course for quickly getting up to speed!

    Helpful(0) Unhelpful(0)You have already voted this
  88. Avatar

    Aniket G

    Superb crash course for quickly getting up to speed!

    Helpful(0) Unhelpful(0)You have already voted this
  89. Avatar

    Yahia E G

    Great course. I have learned a lot. I just wish to have more programming exercises to cement our knowledge.

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  90. Avatar

    Yahia E G

    Great course. I have learned a lot. I just wish to have more programming exercises to cement our knowledge.

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  91. Avatar

    Mario M

    Great introduction. Immediately used new knowledge in current job (marketing data scientist). Recommended course to co workers.

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  92. Avatar

    Mario M

    Great introduction. Immediately used new knowledge in current job (marketing data scientist). Recommended course to co workers.

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  93. Avatar

    Ayush T

    It’s really the easiest way to approach Causality someone who is not from a pure Statistics background. The approach here is different from Judea Pearl’s book and I think it’s justified because this course was not only for computer science students. This course has changed my perspective on how to work with data.

    Helpful(0) Unhelpful(0)You have already voted this
  94. Avatar

    Ayush T

    It’s really the easiest way to approach Causality someone who is not from a pure Statistics background. The approach here is different from Judea Pearl’s book and I think it’s justified because this course was not only for computer science students. This course has changed my perspective on how to work with data.

    Helpful(1) Unhelpful(0)You have already voted this
  95. Avatar

    Gautam B

    Great intro and overview of the details of Causal Inference methods

    Helpful(0) Unhelpful(0)You have already voted this
  96. Avatar

    Alessandro C

    Very clear, it give good intuition also for technical points.

    Helpful(0) Unhelpful(0)You have already voted this

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    A Crash Course in Causality:  Inferring Causal Effects from Observational Data
    A Crash Course in Causality: Inferring Causal Effects from Observational Data

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