I think we need to have more interactions into the lectures, also the material inside the course is not enough most of the course i do it searching and copy and paste the code from the online materials

The instructors did not explain functions well enough, is like they were always in hurry to finish and go to the next lecture. I end up reviewing a lot of internet materials to finish the assessments.

Lectures spend a lot of time on watching a person talk to a camera. Projects are pretty good, though auto-grader is a pain to debug. TA & Moderators are excellent and so is community taking course.

Good overall and I liked the instructor. However the assignments are extremely difficult, especially Week 4 and there are not a lot of online resources made available. Definitely not for a beginner!

Really a struggle to navigate around the discussion forums. The autograder is also a huge challenge. If you can make the actual tests that it runs available up-front would save a lot of time.

The course schedule is tight. I feel like a little bit hard for non-cs major learners. The good thing is you could still upload your homework even after the deadline before the last day of course.

The course offers very little guidance. Nevertheless, I learned a lot but it's really not that well structured. The course also makes you do homework on something that is not covered in the class.

i like the course content. but the assignments need improvement as i wasted lot of time due to unclear instructions. also if the professor can compile more content into slides that will be great.

It’s very fast paced. Personally I would prefer to spend more time on each topic particularly since it deals with the basics of data science and is very important to understand each topic clearly

Skills acquired when finishing this first course are very useful and applicable. However, lectures and assignments are almost unrelated. This course is nothing for people who are new to python.

The coursework validation could use some work to be more concise with error messages but it's OK as long as you work with it.

Content is good and seems to give a decent coverage to the basics.

Assignments often only accept certain solutions and go beyond what was taught in the class. Otherwise the course is pretty good, but you will spend hours after hours stuck in the assignments.

Great course, but the programming assignments take too long time and are more than python only assignments, researching about geography or where a team belongs to, that takes a lot of time.

This course relies almost exclusively on self learning of the details of pandas. It would be greatly improved by examples of how to use pandas to solve problems similar to the assignments.

I learned a lot. But be aware that programming skills are a requirement for this course and that you will have to research the web (stackoverflow, pandas documentation) on your own a lot.

Good course i.g! But it is quite annoying, that the auto grader (python 3.5 ?) does not behave like the online coursera notebook (python 3.6.2), which leads to errors at the evaluation.

Course material is good, covers the right topics to get started with python and pandas. Assignments and especially the grading process require a bit more patience than I was expecting.

I enjoyed the course, but I think the exercises could be improved a bit. Especially in the last two ones could have better explanations and examples of what's expected from the answer.

You will learn a lot, by yourself to solve the assignment.

Which could be see as a good way to learn

Time to do each assignment is clearly under estimated. You can multiply by 2 easily

Too much self-learning taking into account that this is supposed to be a course, could make example projects for better understanding instead of jumping right away to the assignment.

The course was fine, but the last assignment was too hard for me. And I think that for Introduction to data science - the first course in the series it shouldn't be so complicated.

Amazing course for an introduction to the pandas library and its main data structures Series and DataFrame.

Improvements could be made to the hypothesis testing section of the course.

Great explanation. But the speed of tutor is quite fast, so one needs to rewatch again and again. And for better understanding one has to practice questions from external resources.

I think i could be better if in a single module we checkout just a single dataframe and try to extract and transform the most data as possible insted do it with severals of them.

You should break assignment into smaller substeps. You should also provide more comments like 'your dataframe size is incorrect or starting from which line you result has error'.