A good introduction to python and data science. The questions were just about the right level of difficulty. My main criticism is that the online videos were pretty short and not going into a lot of detail, whereas with the questions you had to do a lot of extra research to figure out how to solve them. More interaction with the enrolled students during the course and having more in-depth videos would make the course a lot better.

The course is good if you are carrying even a little experience with python and data science. The teaching methodology is not that impressive but it can make key points clear. Assignments are really good which can be the best part of the course undoubtedly. Though once enrolled, you will yourself going through the discussion forums a lot because not everything is provided for the assignments. Self-exploring is highly encouraged.

The material intended to be taught by this course is really good. What is missing is additional video tutorials to support the learner. I had to resort to youtube video by codebasics and other people so I could put together the required knowledge for this course. It urges the learner to do individual learning which is good, but there needs be more direction and support with educational material presented in a meaningful manner.

The assignment questions need a thorough understanding of the concepts which requires elaborate explanations with more examples. I felt that the standard of the examples were too low as compared to the standard of the assignment questions. I would not recommend this course to any beginner of Python language. The discussion forums on the other hand are inactive and I haven't received any quick response to my questions posted.

Overall I learned a lot, but the relation between course material and effort to pass the assignments is not good. For example for week 4 there is 23 minutes course material (videos) and I needed roughly 15 - 20 hours to pass the assignment. In week three it was not much better.

The videos are only describing rough principles. For the assignments you have to search for a lot of other sources in the internet.

In my humble opinion, the Python ramp-up in week 1 is not sufficient to effectively complete weeks 2-4. This course necessitates a bit more practice in Python. The lectures are cut-and-dry, and I recommend frequently referencing them when completing the assignments. I spent about 1.5x the listed time-to-complete on most assignments. On the flip side, I gained a lot of knowledge by putting forth full effort.

Honestly, it was a good crash course into data science in python. My 3/5 star rating comes from the fact that I think their could be more content / examples shown in the videos. The videos were a good start into the assignments, but I had to spend hours reading on the internet to really understand enough to complete the course.

I liked what I saw in the videos, just wish there was a little more substance.

There are good explanations about Numpy and Pandas, but the assignments are unnecessarily difficult and you will require to look up more functions and methods (that were not previously explained) to finish the course. (I consider that this is an inefficient way of learning)

Also, this is not an introductory course to data science in Python, it tries to cover a lot of topics with Pandas and Numpy.

Course lectures were good, tho at times a little too rapid. The python text appears and disappears too fast to digest, I did a lot of pausing.

The early exercises were good, but later ones were finicky. I would prefer more intermediate steps to confirm we're on the right track. In particular the last (huge) exercise was frustrating, just being told I've got it wrong with no feedback on why.

I'd give this 5 stars but the auto grader is atrocious. Wasted too much time trying to debug instead of trying to learn, and the instructions were never clear, like you could warn me that I need to place all my work inside the function so the auto grader wouldnt freak out, or that I need to delete the raise error once I finish the question

Oh well. I learned a lot, but the assignments were hell

The content is rich and useful, but the assignment in week 3 was excrutiating: it was too long with pointless, confusing questions. I really considered quitting the course though I already practiced pandas heavily in the past. Please do something about it. The assignment in week 4 was much more profitable. Not necessarily easier, but it had meaningful questions and a concrete goal to achieve.

the programing assignment were challenging, which is good as it resamples real world problems. However, the lectures were really lacking in terms of content and the student is left wondering around in stackoverflow finding ways to solve the problems. If this was the intention of the course, then you did great, however, for me, I wanted more content and a lot more explaniation in the videos.

The course material is shallow and there's a huge jump between the lectures and the assignment. I'm able to finish the course only because I learned python and pandas before. The assignment questions are sometimes too vague, and grading system doesn't show why the answer is wrong. It would thus be very helpful to have a option for showing the correct answers after one finished the course.

This course requires a lot of self learning from students, it would have been great if there were more video lectures. I found this one a little bit difficult for me because it required a lot work by my side. The course is okay i will say. It gives a general idea of what this field is all about. I really loved the articles this course provided , they were interesting and informative.

Para os amigos brasileiros, a semana 3 e 4 é bem difíceis. O curso aborda demais o Pandas, no entanto pra mim só alguns pontos foram úteis, pois não mexo tanto com data frame. Mas é sempre bom saber que existe. O professor é maneiro dá bastante exemplo, porém muitos exemplos não casam com algumas partes das atividades, as vezes você precisa ver a documentação e tals. Mas faz parte.

A decent introduction to data analysis using python, particularly introducing the pandas framework. The material can be a bit uneven and disjointed, and the assignments sometimes leave you guessing what is actually required, but overall this was a useful intro to the topic areas. If you're prepared to supplement the course material with your own research you'll get a lot out of it.

The assignment difficulty is much, much greater than the rather basic instruction provided in the lectures. This results in a lot of google searches to figure things out. I feel I could have received an equivalent level of education on my own, by reading books and doing free exercises online. I don't feel there was sufficient value added by the course over independent study.

It took an extremely long time to complete these assignments. In addition, I think the teaching could be improved. With the fast speaking and coding during the lectures, often it requires reviewing multiple times. And, it is never very clear what is going on in some of the lecture applications. This style of teaching is not my preferred method, but it is only my opinion.

PRO: The lectures and content are good. CON: The version of pandas the grader uses is quote old, and is older than the version used in the assignment notebooks, meaning some code that runs ok when you test it crashes in the grader, *with no useful error message*. This caused a lot of hassle and wasted time for me, but hopefully they've fixed it for the new course.

The course per se deserves 5 stars, however the "grader" (=the program which checks you programming) is a pain in the a**. I once submitted a float but it wanted a float 64 ... well yea ...

The Tips in the discussion forum are great - however they could be highlighted better (e.g. extra post).

I especially loved the discussion prompts. I thought them very important.

Although material and assignments provide a good way to learn Python, the estimated time is understated especially for beginners. The challenge is not only what the assignment is asking but dealing with the autograder and making sure responses are syntactically exact. It's easy to spend hours on one question so make sure to make good use of the discussion board.

Lectures should be more in depth especially when going over the concepts in python. They should show at least couple of ways to solve problem under discussion to help drive home the discussion point. Assignment questions were not constructed properly and were very confusion at times. Having a correct answer (not the solution) would help in debugging the issue.

A very interesting and challenging course that would benefit from replacement of the somewhat disturbing living background of the videos, a slower-paced delivery of the lessons, the proper identification of the key functions and methods that are required for the assignments, and replacement Kudos to Yusuf without whom I would not have complete the course!

Really good problem sets and discussion forums. Unlike some other courses, this one doesn't provide much in the way of useful videos. Essentially, you get problem sets and have to search pandas documentation or StackOverflow for help, or look in the discussion forums. Still very useful in learning pandas, but the "classroom" part is not worthwhile.

It was a good introduction to Python for those who are familiar with programming basics, however, the assignments were quite ambiguous at times and did not involve much material from the actual course lectures. Nevertheless, the discussion board helped along with the TA providing helpful hints, guidelines and test code for solving the problems.