Ratings and Reviews for Introduction to Data Science in Python

Thanks!

The course was really great. Thank you! Sometimes precisely what the questions were asking weren't clear (This may have been resolved by a notebook upgrade but I did not realise this until it was too late) and I did have some issues with the autograder. Otherwise would be five stars.

Really handy and useful materials. However, if we can share our codes online after receiving the certificate will be really helpful. Cause although I finished the course, I still find some of my code is repetitive and not pandorable, and I would like to learn from other talents. Thanks Coursera and University of Michigan.

Autograder is hard to understand and has no feedback. Could improve the feedback mechanism, maybe with peer review. Thanks for the course!

I learned A LOT during this course. I was even able to apply some of this knowledge at work after week 2 (and I do not have a technical job - I do this on my own time). It did feel a little complicated at some times. Some more detailed explanations in the assignments could help. We don't always know what the autograder expects...

A course which has great assignments. However, the video itself is a bit boring. Most of the time, my motivation to learn this course is just doing its assignments. At the same time, the assignments are somewhat difficult for those who are not familiar with Python, but for me it's just OK. What I want to make complaints about the assignments is that sometimes the Autograder is so rigid that I have to try one question over and over again until the Autograder "feels happy", and for me, sometimes the gap between "correct answer" and "incorrect answer" isn't so large... And finally, thank you, teacher Christopher Brooks! You are ateacher full of passion, and I actually learnt a lot from you and your course.

Lectures were interesting and well put together, however the assignments and the knowledge required for the assignments were not covered in the lecture material. While I can appreciate that every course will require some elements of self-learning and exploration, this felt a step too far. My sense is that if you have some experience in the actual topics covered by the course, and are looking to verify your knowledge with a certificate, you will be fine. However if you are hoping to actually learn about the topics, you are going to have to work very hard. I'm hoping that the coverage of course material to assignment requirements is a lot better in the subsequent courses in this specialization.

This course covers basics of pandas dataframes. So useful for amateur/advanced programmers who want to start learning data science. The assignments are very good and help students learn how to pre-process and use data retrieved from web.

The class was a helpful intro to pandas. But it was not as much a class as it was a series of homework assignments and the student painstakingly looking things up on stackoverflow. In the end, i am positive I got the correct answers using a horrible coding method and will never see the correct solutions. There should be a little bit more handholding in order for the student to learn the concepts. Otherwise, I might just throw a class up on coursera, give the link to docs.python.org, tell the students to read it and then they will be experts at python.

A hands on course on the basic tools needed to process data from experiments, web data, etc. The final assignment demands everything learned througout the course and it's a perfect example for what one would face on a daily basis.