the language is quite difficult to understand and the the course neede more detailed lectures

I have taken my Pandas skills to a new level as a result of this course.

The materials and assignments are quite difficult for a beginner.

Great course. learned a lot from it

Assignment 3, question 1: The autograder would mark this answer correct even when the data in the DataFrame was wrong. I discovered this after I answered the question, was told it was correct, but I produced wrong answers for subsequent questions that depended on the first one. Messages from fellow students in the forum helped me track down the problem.

Assn. 3, question 2: This was worded very awkwardly and the Venn diagram seemed to contradict the question rather than clarify it.

Assn. 4, question 1 ("get_list_of_university_towns"): The function template provided has a long comment block that seemed to be complete instructions for what the function should do. However, there are two other different versions of the instructions for this assignment in the Coursera course resources section and Google Drive. If the function template includes instructions in the comments, they should be complete. Otherwise, don't show them at all and let the student get the instructions from the other document. Also, the course's "Resources" section doesn't seem like the correct place for these instructions. They should be under the "Instructions" tab of the assignment submission page.

The instructor, teaching staff, mentors, etc. are almost completely unhelpful or extremely slow to answer questions. With regards to my forum postings for assn. 3, a staff member replied only recently, about two weeks after I asked the question. Since then, I've completed that assignment and the one following it!

The course videos are difficult to watch. Whenever Mr. Brooks shows how some code works in Jupyter Notebook, he uses a full-screen view of his browser. On my laptop with a 15-inch screen, his font is a little too small to read easily. I need to concentrate so much more on deciphering the screen that I can't easily keep up with what he is saying. Sometimes I wanted to view the course video on my phone or mobile device. At those times, it was impossible to read the screen being shown. I recommend these alternate ways of showing the code:

Use slides. Students usually don't need to see the instructor typing in real-time. Show a slide with the code and the result.

Use a large font. If showing real-time input and results is important for a specific question, use a large font or zoom in the display as much as possible.

There were some small mistakes made in the videos and assignments that make me think all the materials need some proofreading and updates.

Overall, I'm glad I took the course. I wish several things were better, though. I'm looking forward to the next course of the specialization (data visualization), which is the one I was most interested in taking. I took this course because I would need it for the final certificate and I wanted to be sure I didn't miss any information that would be helpful in the second course. I thought maybe the first course wouldn't be interesting to me, since I have many years of Python programming experience. However, I was pleased to find that the course covered a lot of pandas features and some of the mathematics and statistics techniques that I haven't used in many years, so those contributed to making the course challenging. I would prefer to have done without the additional challenges related to autograder technical shortcomings, though.

I think all the assignments in this course are interesting and well designed. I learned more from doing the assignments than watching the videos. Yes, it took me a lot of time searching and reading stack overflow and other similar resources, but I did learn from them.

Most of my frustration was in fact coming from their outdated Autotrader - for those who plan to do the assignments on local Jupyter Notebook, you'll run into some confusion and frustration with their Autograder as their Pandas are not as updated as your Pandas. This means that even though your code can run perfectly correct on your local, it doesn't mean it would do the same with the Autograde after you uploaded for grading. I spent tons of time, not on debugging exactly, but on figuring out why my code won't just execute after submission. I guess my advice to avoid similar frustration would be just writing assignments in the Jupyter Notebook on Coursera.

As for the video lectures, I agree that they could and should be made better in terms of pedagogy. I'm sure the professor and the teaching assistance are absolutely knowledgable on the subject, but their teaching style is way too stiff. Basically they were just reading off a prepared script, which was not colloquial at all, and they rush through it. I don't think coding skills can be taught in the way of lectures as if delivering a TV speech. Honestly, lots of free youtube videos are better at online teaching than this course.

This is an intermediate level course in python, but entitling it as 'Introduction to Data Science in Python' kinda devalued how much of strength people have to spend on finishing it.

But all in all, I did learn a lot from completing this course, thanks to the well-designed assignments. I would recommend this course to those who wouldn't mind spending more time doing their own thinking and research.

Pros:

1: The content of the course is really good. A lot of important staffs of Numpy and Pandas were given.

2: Even though the homeworks were a little bit difficult, I could practice what I learnt during the video through the homework. This helped me better memorize and grasp the knowledge.

3: The TAs in the forum were really nice and helpful. They tried their best to answer every question raised by the students. They even summarized the algrithoms to solve the homeworks and pointed out the bugs of the system. I definitely would like to give the TAs a star.

Cons:

1, There are a few bugs in the autograder system. I had to adjust my right codes to go around the bugs of the autograder. This is a little bit ridiculous. I wrote right code with correct answer but I could not pass the autograder bucause the autograder had bugs! Obviously, these bugs had been raised by other learners for quite a long time. However, it seems the Prof.'s team didn't listen to the voice of the customers. They should improve the autograder to give the learners better experience because we paid to learn.

2 Some of the problems of the homeworks were not very clear.

3. The teaching style of the Professor is not my taste. I felt like he was just reading the content of a text book. A lot of new things popped up during the course without any explanation. The structure of this course was not well organized.

The basic skill on how to get data from the csv files and excel files. Cleaning and manupulating and making dataframes are taught in the course. I am giving a comparitvely low score because there are multiple things i didnt like:

The professeor and the tutor in the video lectures are too boring. Straight forward they keep on taking and playing a video in which the codes are written at lightning fast speeds.

It becomes hard to keep up with learning as it goes super fast. They just keep on talking before a letting a person digest the syntax of code.

The assignments were super difficult for a beginner like me and the questions wording omgggg! The questions aren't framed well at all had to keep searching the discussion forums.

Not for the beginners course as it becomes too difficult to keep up with. Just keep searching forums in the clue of getting the syntax. Really i was not much impressed by the professor. They should definitely make it more interactive rather than super boring.

Assignments should be peer-reviewed. Spent most of my time trying to figure out why my code run successfully on Jupyter Notebook but not getting any grades on Coursera Grading system. Especially the Assignment 3 was a nightmare for me. Eventough I was getting the right outputs on Jupyter Notebook I had to spent several extra days to fit my code for the Coursera Grading System. Apart from that assignments are forcing learners to get more insight in python individually, which was great for me. If you're total beginner to Python there is very high chance that you may drop the course due to assignments.

The course was frustrating in the occasional lack of specificity in the assignments, which led to problems with the grader. I assume that these resulted in the replacement by a new course, which unfortunately does not begin until after I had already completed this. The lectures by Prof. Brooks sometimes covered the material quickly without developing the points step by step. The lectures by the assistant were very difficult to follow. The assignments were challenging and I have a sense of accomplishment having completed them all.

Concepts could have been taught with more explanation. I prefer learning from books. On trying this video course, it seems VERY tough & so time-consuming to learn. Elaborate explanations could have been provided.

Or at least if I could say, I already knew basic Python but learned Pandas for the first time. Advanced Pandas should be explained with more videos, more steps.

I needed to replay video parts countless times because of only higher level explanation in videos

Almost every course everyone complain about assignments being hard..... but this one is EXCEPTIONALLY hard. Last question of assignment 4 is compulsory to pass the course and trust me it will bring to you trauma and pain like you have never imagined before.

Otherwise the lecturer is actually pretty good, and the other assignments are great for learning!!! I really think they overkilled it with assignment 4 though

Generally, very good selection of content. The explanations are insufficient for passing the assignments tho, which means that most of the course work is self-study from the web. The buggy auto-grader sometime made the submission of the assignments quite a pain as one has to find a way to change the code in a way that still produces the right answer but doesn't blow up the auto-grader.

It started out great but the more difficult assignments like week3 and week4 could use better wording and better clarification on the expected submission answers. The problems could be more well defined based on expected answers. A lot more of my time was spent troubleshooting the errors of assignment submission than what was being asked to be solved in the assignment question.

Bad :

This course sucks, all the video sound like reading pandas documentation. And I have to google the related explanation all the time.

Good:

All assignments are pretty challenging. It is a great improvement for panda skills after passing these assignments. This is a Enriching-4-week course.

These stars all for the teaching assistant, they helped me a lot on the Forum.

The content and assignments are certainly useful and relevant. However, the lectures are too short and do not help much with doing the assignment. As a beginner, I relied heavily on google and the discussion forum to get through the assignment. And I am not sure if i can actually tackle similar problems again without referring back to the pre-mentioned resources.

Interesting course covering the main introduction topics to Data Science, however there is a too large gap between the theoretical (videos, Jupiter notebook examples, ...) lessons provided and the knowledge required to perform the assignment. The time to do individual research to perform the assignment is tremendous. This is not an easy course at all.

I didn't feel that the lecture material corresponded to the exercises. I spent all my time just looking at Stack Overflow. The exercises are also not clearly written, such that you spend time trying to adhere to solving for the solution as opposed to learning Python fundamentals.

The assignments require you to do a lot of additional searching online to find solutions to the problems given. That is what you will also do in "the real world" to resolve issues but when you pay for a course it would have been nice that the course can be used as a reference.

I learned things, yes. But I was here to try and learn what is already there in the books; I thought it would make me understand easily and in interesting ways. I was disappointed. There is no point in taking the course if it sends me back to the books. :(

I have to say this course took me much more time than I expected, because I spent too much time on understanding the programming assignments. Assignment 4 is not friendly to me, because I didn't know about sports in USA.

This is a pretty tuff course and the explanations and teachings are not up to the mark while assignments are good. To complete the course you have to take the help of youtube and web to fully understand the concept.

More concise coding tutorials and less "search on your own on the internet" needed. It is great to get to know the online community and the course needs more coding example directly relat to exams.

A lot of self directed learning, bordering on excessive. Sometimes it takes some investigation to figure out why the autograder did not pass you. Overall, I felt I learned a lot, much on my own.

This is a great overview for python, but the materials/videos/slides are very elementary compared to the sophistication of the homework. Required many more hours than the estimates.