Kursteilnehmer-Bewertung und -Feedback für Introduction to Data Science in Python von University of Michigan

The course is interesting, but the grading system needs to improve substantially. The grader bugs considerably, and the questions are often not well defined, which requires a lot of unnecessary trial and error to understand what exactly the question was about. Finally, complete the assignments took way long that what it is suggested.

It is an interesting course that shows you part of the extent of the things that you can do with the Pandas library within python. However don't expect to be able to code everything by scratch, instead expect to be able to google the answers for your coding questions and be able to adapt those to your particular coding objectives.

The assignments are great and challenging.

Lectures leave a you bit short or not fully equipped to take on segments of the assignments, that I understand and accept however I feel it they should hit at least what else do you need to go out and learn yourself in order to complete the assignment.

Oh and the grading system, eish.

Good and necessary introduction to Python. But especially Assignement 3 regarding cleaning the data should be improved. It´s good to know how to clean the data but it´s confusing when Q1 is apparently correct but actually it´s not. Mabye it would be better that Q2 - Q13 based on a new dataframe which is correctly by all means.

The lectures do not contain enough material to prepare you for the programming assignments. Programming assignments are challenging but the problems are not clearly stated, most of your work will consist in finding answers in Stackoverflow instead of looking for the answers in lectures or programming assignment instructions.

the instructor guides students to pandas, not bad. the assignments are not difficult, but are poorly designed---it's hard to get the goals of functions, and one may not get them done without searching internet. just don't know what a function is supposed to return, and there's no enough explanation on the assignments.

The Assignments are very good. But the video lectures are terrible. they offer no or very little Explanation what so ever of the notebook being displayed on the screen. The TA just reads the notebook instead of diving into what the functions are doing. The subtitles overlap with what people are writing in the journal.

This course was over all okay. My primary complaints are that I felt that the class moved too quickly and relied too heavily on students to teach themselves through the Pandas documentation. The Pandas documentation is really only so-so and it would have been nice to have more guidance through the course materials.

the weekly assignments are so challenging.But the instructions are not clear enough.for each question,one has to adventure through the discussion forum to find what the question expects.Thank you for the discussion forum because there are enough good people to explain and ask questions in each and every dimension.

Though I very much appreciate Dr. Brooks' traits when video lecturing: relaxed, informative, and often lucid-- I worry that students with little to no computer science background will struggle greatly with assignments. That is to say, there is a disparage between the videos and the expectations of the assignments.

Contents are great and very relative. Exam is fair and reasonable. However students have to deal with an autograder for the scores and the autograder is not up to par for this course. The amount of time that you spend on learning during the course is only a fraction of time you spend to get through the autograder.

The assignments have bugs that become more and more present after browsing the discussion board so extensively. I think that it would be really helpful to eliminate any bugs in the grader, so that when you get a solution marked as correct, you can actually count on later problems building on a correct solution.

The course doesn't feel complete, the information and techniques used for assignments can be found completely online through documentation and instead this is merely an exercise for doing basic analysis through documentation rather than an explanation of python through data science (which is what I anticipated)

This course is a very nice course, though it wasn't close to being thorough, but it helped me to develop self learning skills and endurance in tackling problems. it also helped me to have a pattern of study for data science, providing me with assignments which tasked me and helped me in learning so much more

The lectures are too simple. The assignments are difficult. You constantly need to google how-to to be able to complete the assignments because the code/functions are not covered by the lectures. But if you overcome that, the assignments challenge you in a way that you will learn good things about Python.

I have learned many things in this course, but this is more related to the searches that I have done outside Coursera to find information and tools to solve the assignments. There is a great disparity between what is shown in the videos and what must be done in the tests, which also are poorly organized.

Interesting assignments but definitely not the best video lectures - very short and not enough explanation, can as well read a documentation on my own.

Overall is not a bad course, but either change the name from 'Introduction' to 'Intermediate'-ish or create a more comprehensive set of lectures.

Thanks!

The auto-grader system does not provide any useful information for understanding why my answer is wrong. Many questions are not clear enough to understand what they mean, we need to adopt trial-and-error approach to find the correct answer. Finally I aborted on the second course of this specialization.

The assignments contain questions which are beyond the scope of what is taught. Assignmwnt 3 was very useful specially from Data analysis point of view. Assignment 4 was lil difficult. In my opinion, more lectures on how to code specially for tough problems like those in assignments should be added.

I think there could have been more thorough video instruction / preparation for some of the harder assignments. It would have been more helpful if the auto grader could give more detail as to what was wrong with the output rather than trying to find someone who had the same problem on the forum.

The knowledge you get in the lectures do not match the level of the assigments. You use way more time googling and trying to solve technical problems than actually learning Python. I wish the lectures included more examples, specially things you can later use in the assigments. And more theory.

The course has a high level which is fine. The bad part is that most the knowledge you require to complete the assignments is not available in the content of the videos and you have to spend quite some time on internet. It took me way more time than the hours they say to complete the course.

The course is well explained. The grading mechanism is insufficient... in some exercises I arrived at the same result but somehow the answer would be graded as incorrect; and I could never find the formatting differences.

Also, I come from the R world, and I find Pandas extremely unintuitive.

hard and you will pull your hair, but I guess that is their point. It would take them forever to teach you each functionality in Pandas, but the real way to learn is to go and explore. It is the most difficult way though. Expect to spend hours on this, but the reward at the end is worth it.

Assignments are challenging and assignments must be related with the content not out of content of the videos.But in assignment they aren't related with those content of video but out of content of the teaching videos . So, it will be better if you improve the assignments. Thank you !!