Ratings and Reviews for Introduction to Data Science in Python

I like the course very much. It was fun to learn and to do the exercises. There were some rough edges in the assignments but I'm sure these will be straightened out in time.

The content and assignments are certainly useful and relevant. However, the lectures are too short and do not help much with doing the assignment. As a beginner, I relied heavily on google and the discussion forum to get through the assignment. And I am not sure if i can actually tackle similar problems again without referring back to the pre-mentioned resources.

Excellent! A little harder for new students in python but very interesting!

More concise coding tutorials and less "search on your own on the internet" needed. It is great to get to know the online community and the course needs more coding example directly relat to exams.

Wow, this course was intense but worth it!

A great introductory class to data science with challenging assignments to build a solid understanding of pandas and numpy .

It is useful, but there are some notable flaws. My biggest problems were with the clarity of the assignment questions (some were unacceptably vague) and the feedback that the autograder gives. Fortunately, fellow classmates on the forums are extremely helpful in figuring this all out.

Excellent class. Needs a little work to make sure assignments a little more clear, but with a bit of work from the student, it's a great learning experience.

The jupyter notebook made this a horrid experience. Plus Coursera really doesn't want you to bother them with your silly questions, relying on peer-forums. If you scroll through the week's discussion forums, many student posts go ignored. You can't drop the course past the second (I guess) week so the system will keep on keeping on long after you've given up on trying to figure out the janky notebook thing. Will not return to Coursera for any reason. Breathtakingly bad experience.

Very knowledgeable professors, but very little explanation or actual 'teaching'. Graded assignments require a lot of self-education.