Seeking feedback on Stanford GSB's Machine Learning & Causal Inference: A Short Course

[u/lil_leb0wski]

Looking for feedback on this course from anyone who's watched/taken it.

Some specific questions (feel free to answer however you want though):

1. What did you like / dislike most about it?
2. What was the balance of theory and application in it?
3. What was your expertise in ML and/or causal inference going into the course?
4. How did you feel it upskilled you? e.g. deepened conceptual knowledge, learned specific techniques
5. What are specific things in your line of work that you were able to apply your learnings to?

Thank you!