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 !!

The course material was not enough. The assignment questions were good but in order to solve those questions I had to find a lot of things from stack-overflow and the python documentation . This was mentioned there but I still think the material was less according to the assignments.

The Course content is good but the instructor is not so good because while he is explaining something he tries to do all of it verbally and in a very short way. Only those people will be able to understand those who know something regarding this field prior.

The assignments are good.

The course itself is not so bad. But tasks are frustrating! Solving them gives some value but they are mixed with tons of meaningless problems. Some tasks are not clear and autograder gives little information. But I need to say that I learnt more about Python and Pandas library.

I personally feel that this course should had been divided into a 8 week course instead of 4 and material should be added on that ,

eg: the problems asked in the exercise

The exercises are way too difficult and require the use of many functions not taught in the video lectures

Classes moved very fast, especially in the video materials. Functions were introduced briefly without time to digest. While I ultimately did learn the topics through my own research, I feel the class would have been much more beneficial with slower, more indepth explanations.

A lot of question in assignment are not clear. I saw that in forum a lot of people have the same problem as me. The assignment Week 3 is to long, It took so far more than 6 hours for me to complete it. A lot of materials are not in video, we have to read them by ourselves.

Los ejercicios son muy dificiles y hay que hacer mucho reaserch en los foros para lograr llegar al resultado. Las pruebas son diagramadas de tal forma que a veces es dificil llegar por errores pavos al minimo resultado esperable para aprobar los assignments (ej run_ttest)

Content was well paced and well presented but the auto grading submissions took a long time to get used to and were very stressful. The recommended time to complete the assessments was also very optimistic, most assessments took me easily double the time suggested.

A bit surprised by the low volume of teaching material, and the energy required for completing each assignment.

But a posteriori, it forced me to really engage in the learning. I will probably remember more this way, than if I had listened to dozens of video...

I found some assignment questions quite unclear. This, together with the grader sometimes marking answers as correct even though they were wrong, forced me to spend many hours trying to find the underlying problem to incorrectly answered questions down the line.