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

The professor is going too fast and the concept isn't getting cleared. I wish he used some digital board to write atleast what is trying to say or write how the different functions in pandas,series,numpy works.

Although, the assignments were of high quality.

Although the course helped me learn about Data Science. the session taken and the assignment were different and had to understand the expectation in the output.

But overall it helped me understand how can we proceed with studying Data Science through Python

Lectures were OK. The pace moved really fast, and I thought the hardest part was that the directions for some of the questions weren't really clear (and I spent sometime trying to figure it out but gave up --- still passed though!!). Thanks for the course.

For the beginners, It's little bit hard to cope up with the submission according to the lectures. Lectures seems easy but when I go for submission, it seems much difficult and requires more study than the lectures which are not mentioned in the lectures.

this course is definitely not for beginners, I as a beginner had a hard time completing the assignments as I had to read most of the functions used from pandas documentation and it took me a lot of time. please introduce a more beginner-friendly course.

From my poitn of view more lessons are needed, achieving exercises require a deep search on stackoverflow and other courses. That shouldn´t be the goal of the course, I expected the lessons to give enough knowledge to fullfil the questions of the exams

Too much information to absorb within 4 weeks course, requires to spend lots of time offline in learning and researching the Python codes to resolve problems in the Assignments. WOud recommend for hte proficient programmers but not for the beginners .

The teaching process is too fast, especially the assistant teacher who appear at the end.

The assignment is 40% related to the course. And a little bit hard.

The first week assignment is related to the week two, but i did not study week two at that time

The explanation provided and the expertise needed to complete the assignments were way apart. People with great grip on python and having basic knowledge of pandas library will find this relatively easy. The assignments are challenging and hence good.

The instructor is nice and course content is very good. But with respect to what he explains, the coding is way too fast to catch up! Also, not all for beginners. One should have intermediate knowledge in python and at least beginner level in Pandas.

Good course but the assignment grader can be annoying as it is very sensitive to data types and data formatting. I get that this is one one of the constraints of auto graders but on a course that is centered around data it can become very frustrating

The course was easy to understand. The reason i'm giving 3 stars is more on the preparation of the entire set of courses. They kinda develop as the course goes. The other 4 courses of the specialization were not even ready after this course was done.

I spent over 150 pounds on this course which is suppose to be less than 40 and last for a month. I work and studied this course at the same time, I would advice to check your price policy because it is definitively not for those in full employment.

I found the assignments strangely difficult, and their difficulty wasn't sourced in the right place . For example, when solving assignments I never went back to see the lectures, but spent most of the time googling syntax, method signatures, etc.

I felt that the lectures could have been more helpful. There was a lot of talking without actually writing down and explaining the concepts. Even when there were demonstrations, he breezed through them without explaining what each part meant.

Looking for some more references for practicing lambda and list comprehension.Assignment auto grader is a pain, it does not give clarity on the answers submitted. Having some detailed explanation on the assignment and approach used will help.

The lectures dont include almost anything from the programming assignments, I had to look for everything on stack overflow. The explanations are great and I learned a lot on the assignments, they are just 2 different things most of the time.

The material is good, but the assignments are incredibly messy (perhaps that's what you're supposed to learn!): errors are never fixed, it's still using pandas 0.19 (this isn't even mentioned) and you can see the course is simply neglected.

Interesting perspectives on data from knowledgeable professionals, but lacked some hands on learning that I was expecting. Timelines to complete technical assignments were ridiculously shorter than the actual time it took to complete them.

The course was very intense as far as it is concerned with knowledge and skills but it was somewhat a little fast paced.Some of the topics in which more amount of time should have been invested was left aside as though it was a side topic.

In my opinion a basic knowledge of Python is not enough for this course. Furthermore, the video lecture doesn't really explain what is needed fo pass the assigments, the last one is even more terrible because required statistic knowledge.

Don't try this if you are not working with pandas for a while....

The course is actually overwhelming......it packs a lot if stuff without being clear about every item.....

Sometimes you just DON'T know what the speaker is talking about :(

the first , the second , and half of the tird week's content was pretty understandable , everything after should've been more detailed and simplified , the tasks were hard honestly speaking , there should have been more indications

I am not a huge fan of the way the lecturer delivers the course material as sometimes he doesn't explain why things work in a certain way but the assignments are a great way to learn pandas as they force you to search on your own.

The course and the assignments were great. Everything was fine until the auto-grader. Even after running a function and testing it on Coursera's jupyter lab, auto-grader kept throwing an exception. Please fix rectify this issue.