GREAT assignments, average-ish course instruction. Would recommend just for the assignments, great way to get your hands dirty with data manipulation work in python using pandas

Prior coding experience would definitely make this course easier to pick up. A lot of the learning i found isn't driven from the videos itself but from just constant googling.

The video of this course are good. Assessment questions and the expected format of data need to be clarified so that we really understand what is expected to pass the course.

This is good course but you should really have good knowledge of python before doing this course. even if this is introduction course still python basic knowledge is needed

The accent of the instructor was too fast, which made the content incomprehensible. The course unfolded very rapidly, giving little room for beginners to understand on spot

I think, that the structure of the lectures made it difficult to concentrate on the material, but the assignments were very good and I have learned a lot while doing them.

First three modules are great but in the last module (Week 4) Prof Brooks is rushing through many topics. Probably consider having lesser content with proper explanation.

The instructor doesn't explain that much, he could do better than that. It is an independent study. The only thing I enjoyed was the links and the articles, that was all.

Course has a great amount of information that is wonderful, but the instructional videos are less and less helpful as time goes on, and the autograder is the devil.

The course content was good but the assignments were way too tough.The assignments should have been a bit easier because i lost interest due to the tough questions.

The programming assignments were a little frustrating.

I feel a little more time should be spent on the theory behind pandas and how the library works conceptually.

I think the assignments waste too much of my time since I have no problems using proper programming skills, but have lots of problems catering to the auto grader.

Top free course about Data Science. But I think lectures must be more detailed and related to assignments. And assignments could be less ambiguous and more clear.

Some exercises of the assignments where ways to difficult compared to what learned during lectures: much more details should be provided about data manipulation

the course is really good but there are issues with autograder. Though they are addressed in forums you'll have to go through them and hence wasting your time.

You'll spend more time struggling with the jupyter notebook (assignment platform) than actually writing or learning code. The lectures are really good, though.

Great content. But some assignment questions are not that clear and might cost you more time than its worth. And feedback from mentor is not that responsive.

The course is well designed and assignments are complex. What I did not like about this course is that the assignments are not well explained with examples.

The main problem is with the auto grader. There are too many issues making it cumbersome to get the assignment submission right in one go. Please fix this.

Had to learn most of it by myself. Got discouraging at a certain point. Should have informed about the prerequisites.

Learn Numpy, Pandas before enrolling.

Some parts were quickly rushed through and poorly explained. However, they did explain the bare bones of pandas, which was the main reason for this course.

There is one critical technical problem lying in the assignment three and already caused hundreds of students' grade blank in the forum, including myself.

As a beginner I found it a bit of a brisk over the topic. There was a lack of basic questions. But in the end I was coping up and then the course ended.

too fast in explaining it was bit difficult to keep up with the explanation,small code example were taught but assignments questions was too difficult

Great course material, but the autograder system was frustrating to work with for assignments, and often made me less motivated to work on the course.