Ratings and Reviews for Introduction to Data Science in Python

I like the content covered in the lectures. That's very useful for me to clean data parsed from webpages. There is one thing I hope the course can improved, which probably has been mentioned in the forum for many times: the auto-grader is not flexible that it doesn't grant any points to answers that is slightly different from the submitted form (e.g. upper/lower cases, white space, etc.) and we have a hard time figuring out what exactly the auto-grader is accepting. I would suggest modifying the auto-grader such that it allows flexibility in answer acceptance, or breaking down questions into smaller parts (more partial credits) and give more precise/detailed description on the format of answer expected.

Really good course BUT be prepared for a very fast pace of the lectures. I'd placed in the "advance beginner" or "intermediate low" level, therefore, you need to have previous knowledge of Python. As in College, lectures and assignments are somewhat related, but you will spend some additional time investigating by yourself to get the appropriate responses. Again, just like College where Lectures are level 2-3 but assignments are level 7-8 (out of 10).

I thank so much professor Brooks and the team of the cours.

Awsome course with good balance betweern Challange,Reasearch and Progression.

Although the tests can be a bit fiddly, this is a great course if you already have a bit of background with Python and/or data cleaning. Lecture and tutorial videos are lean and information-dense.

This course was excellent. This course deviates from many garbage MOOC who only work with quiz and can not provide a real python coding challenge experience. Assignements are really tough. But my sense of progress is real.(I have struggled to identify such feel in many pytyhon MOOC). Jupyter base for everythjng is a fantatsic format(it even allows coding mobility betwwen my station at work and my home station through the coding on jupyter in the cloud) . My feedback nevertheless will point to some aspect in my experience and where I think you can improve. Succeeding the assignement does not mean that we identified the most elegant way to apply all the knowledge of the course(lambdas,list comprehension, grouping..., apply) in our coding. Breaking that barrier is not easy for me unless we are forced at it and so my looping mind is often applied in assignments. A real correction with the answer need to be provided(this is what the real classroom would do, we managed to get to the answer but we could still learn more with an assisted correction just like what the real classroom would do.I understand that you are worry that the model will end up as copy paste on a webpage and will kill your value. You could maybe consider this add_on for paid customers only and only provide it in picture way which can only be paper print and not so easily converted to webpage format.Or you need to find an alegant way to randomize the assignment coding test at each coursera session, which in that case would not bring any forgery issue and you could provide the correction at the end of the course(or after each assigment completed). Videos are a bit too fast on concepts sometimes. You could split the assigment in two formats: format where simple principle of the course are first resolved on jupyter notebook (just like the videos case but with more exercices) and complex dataframe case as second assignment .(but please reduce the amounts of case to only 1 or 2, not 3) You could reduce dataframe case.(I've spend easily 40 hours on assigment here, assigment time is too heavy from my workload as a full time scientist. This needs some carefull tuning. Overall Great Job

Really awesome course. It is a kind of do it yourself course.The assignments are tough to crack. I think a little bit of programming experience is neccessary. The lectures themselves only give the basic knowledge. The assignments make you do research on the relevant topics. The autograder is pretty bad, it gives false negatives a lot of times, but that i believe is Coursera's drawback and they are working on it.

Very challenging course. And I thought I knew Python. I learned much, much more about Pandas, idioms, lambdas, regex, etc. I will be able to be more productive at work with all this. Thanks.

Excellent course, I learned a lot especially through the assignments. Missing a fifth star because of a lot of issues with the notebooks autograding, and sometimes imprecise instructions in the assignments. Still I look forward to working on the next pandas courses!

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.