Ratings and Reviews for Introduction to Data Science in Python

Great instruction and challenging problems. This was enjoyable.

It seems to me self-learning is more important than watching the videos. Every time I used a lot of time in finishing the programming assignments. Suggestions: give the standard answer of each assignment so that we can improve the coding skill. (yes its difficult in not showing to the ones who has not finished the assignment.But to those who wants to learn it is important. Thanks for the guiding)

wonderful

I really liked the Assignments given. They are a good way to learn and understand.

This was a amazing course related to data science. Most of the topics were covered in this course and the level is quite high.

I would not recommend this course at all. This is for a number of reasons. The lectures are not really lectures, they are more of a narration of someone else writing code on screen, the intructor just whizzes through what's happening without giving any proper explanation (I cannot stress this enough). The limited explanation provided is just on what's happening on the screen rather than why we're doing it this way compared to any other way. There is also not enough guidance given in the lectures but told to just figure it out and go post on Stack Overflow. Anyone familiar with Stack Overflow should know, they *really* do not like beginners posting repetitive questions - so I find that advice from the instructor really odd. The courses makes use of Numpy, but gives zero explanation on what Numpy is and why we use it. It just dives into it by using Numpy arrays and expects you to either magically understand it or go learn what/why Numpy, from someone else. Speaking about assignments, a lot of the excercises require you to do something which hasn't been covered in the sessions at all. I understand giving a challene in assignments, but I would much rather prefer those challenges be related to things taught or from resources given / pointed to. But, unfortunately, you have to figure a lot out on your own and the videos are of no help. It also doesn't help that the assignment feedback is very lacking. The grader also does not tell you what answer it expects, so you have no way of knowing how far off your answer is. This is further not helped by the out-dated version of Pandas running (0.19.2). It has a 4 year old version. I tried to do the assignments locally, but then coming onto Coursera to find the methods I've used aren't supported. This causes further frustation with the "go learn on your own" approach, as every resource you'll find will be using methods/functions from the latest versions. You then have to spend hours more finding legacy methods for what you're trying to do (which, in practice, will be useless as you will always be working on updated packages) In my opinion, this course is not worth the money. I would highly recommend you trial its contents before deciding whether to pay for it or not.

The course content of Intro to Data Science in Python offered by Uni of Michigan is extremely useful and well-organised. It is quite handy to the beginner

I would say this course is kind of a crash course on pandas. If you are looking to learn pandas from basics and want to explore each possibility of different methods and attributes of pandas object and classes, this is not for you. But, if you already know a bit of pandas and want to build on that, I definitely recommend this course. The course instructor speaks very fast and sometimes it's kinda hard to follow along with video and notebook exercise. The assignments are a bit challenging and requires double the time mentioned in the course if you are not fluent with pandas. I would look to see some built in interactive practice tool within the course rather than separate notebook files. I wish you good luck with the course.

great support also in the forums

Excellent course, with good material & explanations by the staff. However, giving more guidance on what is expected from each answer could save us some time while doing the assignments