It would be nice if Coursera could update the Python environment used for the exercises and assignments to something recent. The version they're using (0.19) is fairly old. Every single assignment that I had running against 0.24 had to be altered in some way to work for 0.19.

Course is very good but the Assesments are VERY time consuming. You have to cleanup the data by your own (e.g. rename football teams by hand, what is really painfull for someone comming not from USA)

The assigments' questions were not always clear, but the real issue were the reports from the automatic checks on the answers one submits: puzzling, sto say the least. The rest of the course is OK.

This course was really challenging, I had to look for information per hours, besides I wanna thank the forum debate. I gave 3 stars because they could improve the teaching techniques.

Good course overall, but more material is required to be learned outside of this class for the required assignments than what is actually taught in the class by a very wide margin

Very limited gaining of knowledge based on course materials, most of the effort is self-learning, internet searching, and lots of readings. Inefficient.

Lots of useful content, and a promising structure. But, the overall level of polish was distractingly low, especially in assignments (unclear & buggy)

I don't think I've learned much along the course. I had to pick a few concepts here and there, but I don't think that the way in which those are explained would stick.

Also, the course seems rushed: I'm not sure what the end game of these courses is, but I think it's an incredible wasted opportunity when it comes to MOOCs, as there could be more lengthy videos and more and better ungraded exercises (something that in this particular course do not exist) and much, much better explained assignments (I guess adding there the info from the forums by the teaching stuff would not hurt).

For being a course of intermediate level, the videos and explanations are too short; there are even places where things are left totally unexplained.

Even if it's supposed (and even encouraged) that the students seek information on their own, the lack of context in some places makes it rather difficult. this is specialy more so with the questions that are interwined in the videos, as normally in order to answer them corretly you have to go out and find the related info (something that totally disrupts watching the videos).

finally, the assignments are a wreckage; some of the questions are incredible difficult to understand, if not out right impossible. The fact that there's a lot of information added to the forums by the etaching stuff, up to the point that the more complicated questions are easily answered with that same infromation, proves this.

I do think there are examples of courses in Coursera: I recently completed "Mathematics for Machine Learning: Linear Algebra" and even thought I don't think it's not without its issues, I find it a much more challenging, entertaining and fun course, that covers in a good way its subject.

I have to commend the people from the teaching stuff that are in the forums, thought, as it's the only course in which I found people from the teaching area activelly participating, and helping the students.

In my opinion not really a course. You get simple hints in the videos what can be done with dataframes and co and 90 % has to be find by yourself in the internet. Very often the teacher says after running a code "as we can see...", but you can see it only if you run the code in parallel, because the teacher does not show the relevant result. For the assignment 3 you have to search a lot in the internet and use trial&error to get the correct result. The notebooks are not very useful for looking up later and you have no slides to download or similar.

The questions in assignment 3 are very sloppy and inaccurate written. Check the forum contributions before starting to avoid a lot of mistakes due to possible misunderstandings.

The speed is very fast (even at 75 %) and all topics are only touched upon briefly. The only advantages compared to Youtube videos are that you have assignments. There should be a lot more exercises in between instead of having after hours of videos only a difficult assignment.

I had done "Python for Everybody" from Charles Severance which I had found excellent, with the instructor being passionate and the pace being just about right. I had assumed it would be similar for "Introduction to Data Science in Python", but that wasn't case. The delivery of the course is at a very very fast pace, you don't even have time to stop and absorb the functions and methods that you are supposed to learn. The instructor and the research assistant will list the functions and methods one after the other without pausing. The assignment is then extremely hard with no resemblance to the material in the course (I couldn't do it even after having reviewed the videos). After holding on for the first 2 weeks (it's a very useful topic after all), I gave up and decided to learn from the "learning the Pandas library book", which is a very good summary of the main Pandas functions and methods (and which was recommended by Dr Christopher Brooks), and I was able to follow it very easily.

This course is not very well structured. A lot of the things that are on the assignments/quizzes are relegated to readings in the books and never discussed in the videos. The book readings are overwhelming for a week worth and require at least 2 times more to finish than what is suggested in the course. That is assuming you want to run the code in the book and not just do a hacky job of just reading it and not understanding the code.

The instructor is fine and does well enough but the structure of this course needs to be reevaluated and the time allotment needs to be made by someone actually doing those readings/assignments and not just an idealized number that they expect unreasonably from their students.

There are better courses to start with your data science journey and this isn't the one to go to, in my opinion.

Really appreciate this course. Got me started in Python, Pandas, and Jupyter. First week felt like magic. I am giving it a low score because the assignment questions were so ambiguous that it required constant resubmits an scouring the forums. The ratio of learning of course content to required Stack Overflow internet research was way off balance.

I learned a lot but was extremely frustrated and burned a lot of time it what I felt was all the wrong places.

Still grateful for this opportunity. I think the questions can be better explained and tightened up.

The assignments are fine, they are pretty tedious at times, but it is this kind of situations that forces me to self taught myself. Something really bad about this course is the lectures. They assume we know everything, I wouldn't be able to follow if i haven't done python in data analysis before, g, so they go fast and doesn't explain how everything/every function works. But if they assume we know everything, there is no need for the lecture videos. Just give us the assignments and just ask us to look at stackoverflow. The videos are 90% useless.

This is not really a course. 2h of lectures in total. I have been in longer one-day university lectures. You have to attend other courses in order to be able to complete the assignments because 90% of what they ask is not in the lectures. This is a compilation of exercises, not a course.

On the other hand, the assignments and exercises are OK, that's why I gave it 2 stars.

the course speed is very highand assuming high level of knoweldg

Not sure whether this course is trying to reach data science or Python, but it does a poor job at both.

The class is a light-speed tour through NumPy and Pandas, definitely not for the neophyte Python developer (which I am not). There's 30-40 mins of lecture each week that's basically lightly narrated typing into a Jupyter notebook with only the slightest bit of additional explanation about what the instructor is doing, although the material covered is substantial. There's lot of important details that are glossed over -- forcing the student to pause the lecture and do offline research to understand what just happened.

Similarly, the assignments address and cover beyond the material covered, but the instruction is scarcely sufficient to understand the concepts required to complete them, so lots of Stack Overview and other research is required. And the automated grader, as expected, is completely literal so for complex problems, not much help in validating whether you're on the right track. Assignments take many multiples of the estimated time.

And because even for paying students (such as myself), you never get access to an answer key even after the assignment is due, you have no idea how closely your solution conformed to best practices, even if you arrived at the right answer. For coding, this makes all of the difference, particularly with large datasets that could consume considerable computing resources if not done correctly. I'm told this is because of potential cheating by learners.

How would I change this course? Simple: 3x more lecture material to actually explain what's going on, or down-scope the class so that the existing lecture time becomes adequate for the material.

I recently completed this course on Coursera, and I must say it was quite a disappointing experience. The course material itself was not comprehensive enough, leaving me struggling to grasp the concepts and understand the topics properly. However, what made matters worse were the challenging assignments. The assignments seemed to be disproportionately difficult compared to the provided course material. It felt like there was a significant gap between what was taught and what was expected from the assignments. This left me feeling frustrated and ill-equipped to complete the tasks successfully. I understand that courses should be challenging to facilitate learning and growth. However, there should be a balance between providing comprehensive materials and ensuring the assignments align with the knowledge acquired during the course. This course fell short in that regard. In conclusion, while the course had potential, the mismatch between the course material and the difficulty level of the assignments, coupled with limited support, made it a frustrating learning experience. I hope that the course creators take this feedback into consideration and make the necessary improvements for future learners. he is just a Radio! you can listen to him ! but wont learn from him

I dropped this course. The complexity of the assignments is absurd and the autograder does not give much information about what is supposed to be wrong. Many people have problems with the assigments because the forum is packed with posts about all sorts of difficulties. I managed to complete all the assignments but the last one. In the last one I wasted so much time that I came to realize that there was not point in wasting any more time with this assignment and this course. If the remaining of the specialization is like this, it is going to be a nightmare. I will choose another data analysis course in Coursera, sinze there are a few available.

I find it outrageous that in Week 4 instead of practicing python and statistics I have to spend a lot of time learning very US and sport-specific information which is absolutely useless and I am never going to need it. The same is valid I believe for the rest of the world. The coursera platform was not intended exclusively for US and Canada students? Or for people who do not have full-time jobs and a family in addition to the need to learn python?

Unfortunately, I won't complete the specialization because of this course and I will look for the content elsewhere, because of the following reasons:

1- The videos are not informative and short

2- Assignments only use like 10 to 15% only of the given info from the video

3- No slides, hints or tricks are given to help you in the assignment

4- The lecturer needs real life examples and visualization aid to support his teaching method

Not really an introduction course. The lectures are moving very fast, without really explaining the material. The assignments are much more complicated than the material learned during the lecture. Almost not related at all. I had to learn everything from google. Not for beginners!!! This course will take all your free time and will to live...

very badly designed course, no material support. Assignment required outcome where not covered in the lectures. what do you expect students to learn from outside sources. Very very bad. Waste of money, I am disappointed this course.

Links don't work. Very little information provided, It confuses more than enlighten.

too fast .... needed to pause the video constantly

It's a really good course for those who start working with data, but I must warn you that for those who has a beginner level in programming that can be a tough one. I really like the approach when you are given the basics and algorithms but you have to investigate the topic yourself to solve tasks - it's the most effective way to learn something. However I understand why some people may not like it.

I would like to mention the forum support - all the questions are solved very-very quickly, thanks a lot to the teachers!

The thing I didn't really like was the last assignment - 4 Qs out of 5 are the same... So if you manage to solve Q1 - others just require some boring data preparation, I understand that it happes in real life, but why here, it only takes time and annoys you?

I would recommend this course for those who has already worked with Python and knows all the basic classes and structures. If not - it's better to take some introductory course (it will be useful anyway, better to start with the fundamentals) .

PS: I really don't understand the comments here of people wh0 complain that they had to go to stackoverflow or read documentation - that's what you do when you code