Good intro to Bayesian Statistics. Covers the basic concepts. Workload is reasonable and quizzes/exercises are helpful. Could include more exercises and additional backgroung/future reading materials.
An excellent course with some good hands on exercises in both R and excel. Not for the faint of heart mathematically speaking, assumes a competent understanding of statistics and probability going in
創建者 Alessandra T•
We still don't understand how Bayes differs to Frequentist... A worked example comparing the two at the end would have been nice.
創建者 Ken M•
It would have been great if more graphs had been provided, for easier visualization of the e.g. distributions, or concepts.
It would be better to add more explain about those equations and connect the math stuffs with the real world samples
創建者 Max H•
It would be much better if there was a more sufficient introduction to the various distributions used in the course.
創建者 Victor D•
Very informative as an introduction to concepts, but nowhere near the deep dive I'm now interested in taking.
Good course!!... Additional examples of real life explained and done in R or excel will make it great
創建者 Andres F P A•
A lot of formulas and not that much interpretation. It is a good start in Bayesian concepts.
創建者 Binu M D•
Too much theoretical than practical applications. No need to give both R and Excel videos.
創建者 A A•
Would have liked more problem solving and real-world application examples.
The workload is manageable however the homework is somewhat challenging.
創建者 Hassan S•
Not well organized.
No sufficient materials, references, etc.
創建者 sokunsatya s•
Overall, it's Ok. but the explanation is too short and incomplete.
創建者 aref h•
better to come up with more examples and more mathematical details
創建者 Rajesh k•
This course could be taught in better understanding way
創建者 Tawan S•
For some derivations, the explanations are too sparse.
thank you my teacher
創建者 Damir M•
A bit too short.
創建者 Marjan H•
I expected better teaching quality. The instructor is undoubtedly one of the bests in his area, but I personally did not like his teaching in this course. I felt he knows a lot of interesting concepts but intentionally does not teach them. The whole course was like somebody was reading from a textbook without adding any comments for students to actually grasp the concepts. In general I liked the course but I expected to learn much more from it.
創建者 Patrick K W•
It's alright because it gives you an overview of what is covered in a Bayesian Stats class, but the material is presented quite poorly and I had to do a lot of second hand reading to answer the questions. It is not particularly enlightening even and the formulas are presented without proper grounding, context, and intuition. I can recommend this only for dedicated self-studiers who already have some sort of grounding in Bayesian reasoning.
創建者 Vinod M•
Week 4 explanations are just theoretical where professor is literally not giving any intuition and rushing through the concepts with equations which did not make any sense to me. Till week 3 I could kind follow. I did this course with the intend of giving a based for Machine Learning study and I am an thoroughly disappointed the way it ended up.
創建者 Dennis R•
Good content. However, way of presentation is not very engaging. Presenter's voice very monotonous and free of any engagement. In my opinion, scribbling formulas to the board does not make a helpful learning experience.
A pretty standard "college-like" course with many definitions and derivations that do not help with conceptual understanding of the material. There are better tutorial/explanation videos on YouTube.
創建者 Bole K•
Lecturer just writes formulas without trying to explain background concepts. It is like reading a book of statistics. No way that most of the students will understand it.
創建者 Jorge P•
Some matters were just given formulas and there was a lack of practice. The course should cover less materials or be longer to be effective in teaching.
創建者 Brett B•
Disappointing. Hard to follow, as concepts are not fully explained or linked. Steps in equations are often skipped without notice.