I meet the prerequisites, but I can’t understand your course. Why?
Where are the slides? Why are you saying I should take hand-written notes?
Ok, but really, where can I get the course slides?
Should you code along?
How do I practice what I learned in your course?
Why do you keep saying “all data is the same”?
What does “in-depth” mean?
“What if I’m forgetful? Can you remind me?”
Why does “how to succeed in this course” exist?
What does “appendix” mean? Why is the “appendix” / “FAQ” section so long?
Why do I have to learn about what I’m coding before I write the code?
Why didn’t you answer my question on the Q&A?
How to read course titles, for beginners (e.g. “Why doesn’t your Bayesian Machine Learning course cover everything about Bayesian Machine Learning?”)
Why do you need math for machine learning and deep learning?
Isn’t implementing machine learning algorithms reinventing the wheel?
Your course title was misleading, why?
Should you study the theory behind machine learning?
How do I debug the code if I get an error?
What’s the difference between your courses and your consulting service?
What’s with all those single-letter variable names in ML code?