The course began well, with a focus on the elements that make for good visual presentations. When it came to applying Python and Pandas to attain those design goals, however, I found the course lectures to be superficial and mostly unhelpful. I ended up having to teach myself the basics of merging dataframes, generating interactive charts, and applying Matplotlib. Even now I don't feel that I have a good handle on the concepts. The lectures could benefit from the use of more graphics, ironically, and not just have a talking head or code sections. For example, should we use the backend to generate Matplotlib plots or the plt.plot function? There was too little guidance on these points, forcing me to invest in my own separate reading materials just to try to figure out how to make things work.

It does teach you matplotlib in a way but really misses the whole figure, axes, axis differentiation. I had to read a lot that was not a part of this course. Some things are outdated and the assignments are good (the last one was superb!), but they really are not suited for a beginner. The first one was trivial (no coding), second was great but had bad instructions and third exercise was too difficult. You don't learn half of it during the short vids and then they expect you to pull of something like that.

I would not recommend this course and would regret buying it if I didn't get it for free. However, it does the job and teaches you matplotlib basics.

Programming can be a slog when the right materials are not available or the documentation is sparse. It is for this reason that I choose to take and pay for a course instead of muddling around the documentation alone and pulling my hair out. This course does not remedy that issue. I find the professor likeable and he cares about his subject but I have to say it directly and bluntly: the videos are examples of teaching issues with incomplete treatment of basics before moving onto complexities. There is more than a little word salad to get through in the videos which are more and more frustrating as you re-watch them expecting you might have missed important info needed to complete the assignments. It is frequently the case that you have to dedicate far more time to background research in order to complete exercises than the time commitments quoted here. This course could be so much better with some rethinking on how to emphasise and present key concepts so that we are enabled to start from a solid base instead of wandering half-lost as soon as we begin coding. Maybe a collab with professor Severance could remedy.

Too little of expounding and too much of searching the net by oneself. Too few examples. It is a self-learning but what's the Course for then?

Plus the assignments. I didn't like the peer evaluation idea, just as evaluating the others, because I don't have time for this and that's not what I came for.

First - what's the motivation of random viewers to fairly and thoroughly evaluate my work? Plus it's hard to finish the course quicker for this reason, because one has to wait a couple of days to get a grade. That's the reason I resigned from waiting for the assignments evaluations for next weeks assignments and in consequence for the certificate.

The construction of this course is fine, but content is really bad. Instructor could not give detailed introduction in matplotlib. So basically you need to learn everything by yourself. On the other hand, there is huge gap between course and assignment. I would say that you should have at least intermediate level of matplotlib before you take this course, which strongly against the principal of this course. I suggest instructor giving a more general idea first and gradually providing more specific application and harder examples.

Compared to the first course in this series, I found this one not so challenging. The final project was very loose (I understand that the instructors wanted to give the feel of a real research). The first assignment was very superficial. As much as Cairo's principles are important, I feel devoting an entire assignment to that is justified. The second and third were relatively straight-forward, but that was perhaps the saving grace.

Wish the course spent time in dwelling on complex visualizations.

From the previous course I know what was coming.

And it was tuffer than Tufte...

I'm not that confident with the structure of the course. I would prefer more mini tests on checking the knowledge of the singe plotting commands and then heading to the assignment of each week.

I think that the challenge would be less frustrating when beeing more skilled with the tools in your plotting toolbox.

Too little teaching and too much googling. The questions are poorly defined and you end up using Stacker and the discussion forums to really understand what they are asking. I put the time in and got the answers but would have liked them to explain whats going on a bit more rather and give a bit of guidance. Also very expensive, compared to other Pandas and Matplotlib courses.

It taught some visualization that is not use very often and sometimes I feel I couldn't catch up the knowledge, so if you are a beginner, skip this class first.

It was too fast. The jump from basic to advance was too quick

too little explanation of the code

The content is very limited

This course is anbalagous to taking a creative writing course, but all lessons are on vocabulary and grammar. Once again the lectures are unhelpful. The discussion forum in this course does not provide much help (unlike the first course in the sequence). I suppose they are applying the graduate school mentality to teaching: you want to learn it, figure it out. I myself am definitely not at that level right now.

The assignments are challenging, and you will learn from them, but you won't learn deeply. It seems all very superficial. Just look things up to get them done. Type in any question you have and a solution will certainly appear on SO. Why not give students the tools necessary to solve challenging problems on their own (like in Python for Everybody and Python 3 Programming)?

Professor Brooks is clearly passionate about programming and is very accomplished/intelligent. Unfortunately the teaching in this course is of low quality.

The explanations are horrible. You either see the profesor talking which is difficult to grasp when you don't really see the code. Once you see the code it goes too fast with hardly no explanation. I understand the point to encourage students to learn how to get extra information online, but this is just too much. 95% of the knowledge I'm getting is not from the course. Waste of time and money.

Another course where the lectures are basic with madeup, easy examples and the assignments are real world, messy with poor direction and unclear end results. You have to use the forums to understand the desired outcome and then spend your time on Stack Overflow to solve. Why then even pay for a course?

Awful course. What a waste of time! No proper explanation of the different functions used. Half the time, I'm confused. This is the pattern that Prof. Brooks follows. I'm done. I'm not enrolling in any more courses offered by him.

Lectures are not detailed enough and speaks too fast, assignments too difficult. If I have to do my own study 90% of the time why do I need to pay tuition?

There are some rubbish assignments in this course which involve searching the web for badly made info graphics.

Well to be honest youtube videos are quite informative than this. Opting out from this course.

I feel like this course is bad. Since it basically tell us to search google for everything.

Too few lectures with detailed explanations of the functionality of matplotlib.

A course where you practice your googling capabilities. It could be improved.

Peer review is not good.

This course offers a nice introduction to plotting with matplotlib (and a bit of seaborn).

Much depends on you. The videos give you general instructions, but you should also search proactive for more detailed information on your own and learn by doing the assignments. To enjoy the course as much as I did, you should be familiar with the material of the first course of the specialization (especially with pandas and data wrangling).

I really liked the peer-reviewed assignments. There are a lot of fellow learners, thus you never have to wait more than a couple of hours (or maybe a day) to receive feedback and a grade. The assignments meet different skill levels and let you decide how much effort you want to put in. You could do them in 20-60 minutes or you can really dive deep into it and learn a lot while solving provided questions and your own questions as well. It’s up to you.

You are going to learn by doing, less then getting a deep lecture of Matplotlib. Yes you will learn it quickly, but the lecture videos are only about 15-30 minutes a week, while the projects will take you a few hours to complete (With the last two taking significantly more time if you want them to). I was a little disappointed that I didn't get I 100% clear picture on how to use Matplotlib and Seaborn, but I do feel like I gained comfort, so it was worth taking!