Loved the course! This course teaches you details about matplotlib and enables you to produce beautiful and accurate graphs.. Assignments are challanging, and helps to build a solid foundation.

I feel that this course is to take money from people who are not educated enough to realize they are mostly offered snake oil. It was very disappointing how little effort the course staff put into this course. The whole first week the professor was rambling about some design authorities spitting out names like Tufte and Cairo and asserting how important it was to mind the design features. One might argue about the importance of this, but there was not a single item of actual practical application over all the first week. Then in the second week finally came some material on matplotlib, also horrendously presented. Professor Brooks showed it the way that made one of the best plotting tools in the world look revolting. Speaking factually, the information was scarce and consisted largely of using matplotlib in the convoluted way with the practices nobody actually uses. And again, most of the actual learning was left to the user in the form of Professor Brooks encouraging the learner to read documentation and ask questions on stackexchange. I can do this and I do this a lot in my work but having paid money for this course, I did not do it for a dismissal like this. Yet I decided to stick with the course out of sunken cost implications (after all, I paid $50 and spent some time in the specialization). Today it is three days to the next subscription charge and I realize I do not have enough motivation neither to hand in the last two assignments (which I am capable of) nor to give away another 50 dollars just to discover that the machine learning course is none the better.

A fundamental issue after this course is that it still takes me hours to prepare an appealing data visualization using what I learned here whereas with Excel it takes me minutes to draw and pretty a graph. So the course doesn't fulfill the practicality criterion yet.

very much disappointed.so much less content than the first one and it is not self-contained. A lot of things left unexplained and kind of assumed that you knew a lot about python already. I literally took another course in python before finishing up this one.

Badest learning experience ever. What do you learn in the course itself? - you can use matplotlib - there are different chart types in matplotlib and subplots (and you see the basic code therefore) - a visual should be beautiful etc (a whole week of 4 is spend on this topic!)

How bad the course is does the teacher say himself at the beginning. He is saying something like: "For the assignments you will have to search a lot in the internet and ask question how to solve it at different sources".

??? What is then the sense of this course? Of course it is ok to look something up in the internet, but in this case you have to look up 99 % of the necessary information. The sense of a course is to learn it primary INSIDE the course.

In the videos he is only scratching the topics in a very fast way. Mostly he is not explaining anything of the code he writes (ok, in week 3 with the course updates he sometimes explain parts of the code). Especially in external readings it is forgotten that not everybody is a native English speaker (Too complex and way to long explanations).

So you have somehow to break the coursera rules. For the assignments it is a must to search in the internet for existing solutions and adapt your code accordingly or you ask somewhere how you can solve it and copy this code. You learn primary via trial&error and copy + paste + perhaps understand code from other sources.

You also have no script etc of this course beside some pages of Jupiter notebook with less information.

Beside the assignments you have no exercises, which are somehow rated. Sometimes the teacher says you can try to change something. But that is then not using existing knowledge out of the course, but searching in the internet...

Week 1 about beauty etc. is overkill. Way to much information about a visual level, that you will never reach with this course.

The assignments are rated by other learners. So you have to spend additional time for rating the work of others. And then you even have to rate the beauty etc of the visual...

I would never pay for such a course. The only advantage is, that you have assignments. If you do not need them you can simply use directly the internet for learning. With or without this course you have to search in the Internet how you can get a certain result with matplotlib.

Paying for a brief showcase of "what is possible" and then getting told to look up needed information elsewhere is not my understanding of good teaching. Also lessons are absolutely not useful for assignments. No recommendation.

Good course to learned matplotlib and other Graphs libraries, but the course goes further than Python and also encourages the studies to create more meaningful and beautiful Graphic views.

Ideally, would be 2 1/2 stars if that was possible. Again, like Course 1 in the series, the time required is VERY underestimated, especially since the course is little more than a series of exercises that require extensive external research to learn how to complete. The instructor seems more interested in this subject matter than the first course, but the discussions are such high-level overview, much pouring through Stack Overflow is needed just to learn the topics. The best pieces, as in Course 1, are the extra reading that one might never otherwise be pointed towards, but other than those, a $10 web course that simply gave exercises and pointed to Google searches and Stack Overflow to learn the detailed material would accomplish 80+% of what this course does. And many find the assignments confusing which adds time or results in the wrong work product (some of that I believe is especially true for non-native language speakers) - lots of comments to that effect in the forums. Students grade each others' work product, and it is clear from doing so there are many interpretations of the exercises.

And, some students doing the evaluation of others are clearly not qualified to do so - if one does not really understand basic Python or statistics, they should not be indicating the calculations are wrong... And with three reviews required - it seems the grader uses the lowest grade of the three. If 2 reviewers give full marks, and another gives a 0, the 0 is what is recorded. This is especially annoying in tandem with the lack of value in the instruction - just getting some assignments from off the web and forcing yourself to do them would be far more satisfying.

I don't see continuing with the Michigan courses beyond this point - there are better options.

It's a poorly managed course. The videos, though informative, are extremely short and only provide one use case for a function. The rest is "left to the student to hunt around in the documentation". I wouldn't have taken the course if all I had to do was read the documentation.

The third assignment is extremely poorly worded. It's not a difficult assignment, but it took me 2 hrs to figure out what the hell the question actually meant. It's like someone from grade 7 wrote the instructions for the question.

Week 4 doesn't really provide any new information, but introduces a completely new package when the first three weeks didn't even conclude Matplotlib correctly.

I personally struggled a lot through the course. I thought the video lecture did not go into enough depth on how to manipulate matplotlib (eg. ax objects and ticks markers are still not clear) and even in general, the explanations were lacking.I feel the pace was a bit too fast as well and the topics were not in sync. Even after completion, I am nowhere confident in my matplotlib abilities.

The Assignments should not be peer-graded, as there's no uniformity to the evaluation process, rather the instructors can share their thoughts on the candidates plots.

Not the best course I've had. Video are too short and superficial. Assessment are based on personal research and often not well explained. Teaching material is quite poor, python libraries version in jupyter notebook online environment is old and it is quite difficult to find something in the forums because of this (and you need to do it because thay do not introduce enought concept about what you'll need for assessments). At the end, a really poor content course.

Didn't like peer grading as it introduces delays in grade and peers don't have competency to judge my work.

Also, the course should be more focused on technical matters. I really would love on the completion of the course to be guru in matplotlib (or some other plot utility) and know by hand all the tricks and methods the data can be plotted.

I really dislike the peer-graded assignments

Too much of the course is unstructured

I dislike being assigned a region and topic for the final project

I would prefer to dive less into interactivity and focus more on practicing essential plotting skills over and over again.

The only advantage are the assignments and the certificate. But there are better alternatives for information and learning matierals for pandas or matplotlib on youtube or so one. But this course isnt 50 bucks worth it.

Course coordinators don't monitor the forums enough, so obtaining help from them is next to impossible. Aside from that good course, would be nicer if it focused on more modern plotting frameworks (Plotly, etc...)

instructor advice is primarily to 'use stack overflow'.

I registered to the whole specialization mainly to take the first three courses. I got stuck in the second (this one about data visualisation) because a file I need for assignment in week 2 is missing. There are many complaints in the forum from those affected (the file is supposed to contain weather data around your location, and it seems to affect some of us in Europe). I jumped to course 3.

I'm very happy with courses 1 and 3, but this one is extremely bad, with poor material, confusing data and wrong instructions. On top of that, there is no one in the forums to answer questions or fix the errors. I finished courses 1 and 2 (those are great, really) and I will drop this specialisation right now leaving this course unfinished.

A better use of your time is watching youtube videos on MatPlotLIb and practicing charting with w3reasource exercises. The strength of this class is independent learning (reading library documentation and StackOverflow), which you can do without the class.

Very helpful to understand what it takes to make a scientific and sensible visual. Recommended for someone who is interested in learning data visualization and does not have a background.

Great course, great instructor! I think for me the more difficult was lack of simple practice tasks during course - it will much improve to understand material. Regards, and thanks!

Pretty good course! The only reason I didn't give 5/5 is because the 3rd assignment required you to know quite a lot about custom colours and how to change the colours based on values. This was not covered in the lectures and was a high pain point for me. I understand that there is a level of finding the information yourself in this course but this really did take me a very long time as the matplotlib documents are quite dense.

It would have been better if lectures were of more length and covered relatively harder problems. Support of course staff on forums is very poor. These things can be improved.

Too many peer reviewed assignments.

I have taken several courses on Coursera, including Data Science with R, Statistics etc. The first course on this Specialization (Pandas) was ok, I'll rate that 4 stars.

However, this course seems like a downgrade. Lectures are either too shallow or too deep. Too shallow as in there are only several short videos on Matplotlib that are very introductory and doesn't show much. Too deep as in Professor Brooks went dove deep into the architecture of Matplotlib, which I think could have been simplified and delivered in a better way.

The assignment for Week 2 and 3 are ok - but I'm starting to hate how vague the instructions are and everyone turns to the forums to figure it out. Assignment Week 4 is a disappointment, as the allocated topic is almost impossible to draw up information on and in the end everyone just pick their own 2 dataasets, which is another challenge. I feel a better way would be offer several sets of data to choose from.

this course is not entirely bad, I just feel that i didn't learn as much and what I learn comes from googling Stack Overflow or other websites while doingthe assignments. Thus I feel that this course is not really worth its price, other than gaining a certificate and advancing the Specialisation.

A good course that could be better.

I think that this course provided a reasonable introduction to Matplotlib, but the lectures need to go a bit deeper and provide more examples. The course left too much of the work to the student. [For your reference, I have a PhD in Mathematics, taught for several years at a highly selective undergraduate college, and have extensive experience in industry as a Matlab and SAS user.] The homework assignments were substantial, and I enjoyed doing the final assignment which required merging two or more datasets using Pandas and then Matplotlib to plot relationships. The course website provides estimates of the number of hours required to complete the assignments, but these were gross underestimates because so much about Matplotlib was left to the student. I would have preferred a bit more lecture time, more examples, and a few side tutorials on using Jupyter and notebooks (how to download and upload), especially since we were grading the code of our fellow students.