par Cora M•
20 nov. 2021
My rating applies to the first week, as I'm dropping after my experience with the first assignment. This is not a commentary on Prof. Dougherty, who seems like a teacher I'd really like to have in an in-person setting. It refers instead to the Gilliamesque homework submission and grading system. Before you join the class, be prepared:
All homework is submitted in an ipynb using an R kernel, and homework is autograded. The grader gives zero feedback regarding what was incorrect, not to mention why or what the correct answer is. All you get is the number of cells that didn't pass; when you reload the assignment, there is no indication of what was wrong.
As a math nerd troll, however, it's magnificent—the grading mechanism itself is a probability problem that provides one with hours of fun. By which I mean frustration.
I joined this class as a refresher, because I love probability. I'm dropping this course before that changes.
par Mattia G•
18 déc. 2021
peer review assignments are useless
par Essam S•
11 oct. 2021
The instructor is very good, more examples need to be added, there are mistakes in the evaluation
par Ke M•
15 nov. 2021
Sorry, but I can't learn R by myself. I know how to do all the calculations, just don't know how to put it in the R language.
par Tim S•
5 sept. 2021
This was a very good course. The material was well thought/planned out such that the readings, lectures, and homeworks built off each other in a constructive manner, which reinforced the material. I highly recommend taking this course as an introduction to probability.
par Jun I•
13 oct. 2021
Great course which covers from fundamental probability theory with good examples for better understandings.
par Ping Q•
22 janv. 2022
Very logical arrangement, proper speech rate, crystal clear!
par P A•
17 janv. 2022
Great intro and very well presented by the prof
par Michelle W•
30 avr. 2022
The professor's instruction is clear and concise, but I wish there were more videos to expand on topics not discussed. The auto-graded assignments are painful since there is no feedback on which problem was wrong (hint: only do one problem at a time and submit to grader. it is painfully slow but this way you know how you did on each question). This course assumes you have basic familiarity with R and can do basic differentiation & integration. I would not recommend this as a first course in probability - this course is best for those who have had some exposure to probability already (E.g., undergraduate level course).
par Nathan H•
23 mars 2022
It's pretty basic material, but that's not a bad thing. I had no trouble with the content.
It took a month, or something like that, for Coursera to let do the peer grading that's required by the course.
par Paul R P•
18 avr. 2022
Need to brush up integral calculus for thios course. Something I haven't looked at for 40 years.
par Mauricio F•
20 juil. 2021
It was a great course. Good combination between theory and practice.
par 상은 김•
5 oct. 2021
Helpful to understand data sciences basic thories
par Daniel C•
3 févr. 2022
Exactly the probability course I was looking for
par Hidetake T•
30 mars 2022
Good course with sufficient amount of practice.
par Claudia G D•
3 mars 2022
The course is very good.
par Kyle A•
21 févr. 2022
par Matthew E•
8 mai 2022
Lots of fun
par Kevin H•
14 mai 2022
Not enough participants for peer review, not quite enough time spent on curriculum