Too slow grading and a very inefficient process.

Not very well done

really bad!

NOT GOOD

Overall, the course is great and definitely deserves 5-star rating.

However, it starts quite slow and in my opinion first few lectures discuss irrelevant topics, like minimalism of presentation. The problem is that a person can't grasp them without experience...

For example, several videos discuss idea of Edward Tufte. I understand that CS and mathematical statistics are the background of the instructor, but really, Tufte had only repeated well-known basics. Indeed, it was Leonardo da Vinci who first said that "simplicity is the ultimate sophistication". He was followed by Antoine de Saint Exupéry with "It seems that perfection is attained not when there is nothing more to add, but when there is nothing more to remove" and the KISS principle of Kelly Johnson of Lockheed Martin Skunk Works.

Perhaps, for the authors of the course software engineering is closer: https://wiki.archlinux.org/index.php/Arch_Linux#Principles ...

I found the course very rewarding, and I was surprised how easy it is to make nice looking graphs in python. Extra points to teachers for putting substantial emphasis on good design and aesthetics.

You can pass the course without making any animations or interactive graphics; however, I found those assignments most rewarding so I recommend you give them a try.

Workload-wise, this course took me about double the amount indicated on the course website, but it would have taken considerably less time if I had set the bar lower for myself.

As with Course 1 of this specialisation, the lectures only give an introduction to the topics and you'll have to look up matplotlib documentation and answers from stackoverflow to complete the assignments. I found this course less challenging than the first one (but still challenging enough for sure!).

Perfect, insightful, deep, challenging! I love the way prof. Christofer Brooks teach Data Science. Interactive IPython notebooks enables creativity to implement lecture notes right in the browser during watching lections.

I enrolled to "Applied Plotting, Charting & Data Representation in Python" course right after finishing the first "Python for Data Science" module. This is one of the best experiencies I got during my online education.

There are a very active forum discussions on this course, people and course staff are helpful.

Next, I want to enroll next courses of the Specialization.

Also I would like to say "Thank you" to course team and Coursera for the financial aid opportunity.

This course helped me understand the basics of Data Visualization unlike any other internet resourses.

It starts with one module completely dedicated to the theory behind data visualization and how to present data in a genuinely insightful manner and then delves into matplotlib and eventually seaborn to implement the same.

I enjoyed Dr. Brook's teaching and the exercises. With a solid pedagogy, challenging exercises (the last one is especially fun and gives you a feel for the subject) and insightful lectures it's a great course for people looking to gain knowledge about basics of python data visualization.

I really enjoyed this course. As a python novice I had to spend lots of times in googling commands for arguments, options, examples. Well I see many peoples are only relying on course materials but the considering this course as a motivator. I often felt frustrations and pressure, but not tried to be defeated by myself. Hope you guys find your own way to get it done. I still see lots of thing to learn, but I am not worried. This is only the beginning. Course is not a magic pill, it just gives a start point. As a start point, this is really nice cource to take.

This is an excellent course on visualization in Python. The videos are brief and covers just the right amount of information. Reading resources and assignments are carefully chosen and perfectly complements what we've learned in the lectures. Assignments, most of the time, require us to read the matplotlib documentation but is easily understandable once gone through the lectures. Assignments are not very easy/simple, but completing it with real data and help from documentation, stack overflow and discussion forums is deeply satisfying.

This was an interesting course. The professor was excellent and the practical exercises, in particular, were beneficial in learning the material. My only complaint would be that a lot more time in the exercises was spent formatting and manipulating Pandas dataframes than applying the matplotlib libraries to produce charts and graphs of the data. I would have preferred to spend more time experimenting and using the graphics libraries and less on trying to manipulate data to get it into formats acceptable for grading.

U-M and Coursera together brought a great and very interesting course. Great that the learners get exposed to various aspects of DS, be it the concepts , trends etc. A great platform for participants to learn together and experiment. Course introduces what is relevant in the industry and provide multiple opportunities to apply the learning. On top that it is laced with interesting challenges, not a cake-walk -:)

My sincere thanks to U-M, Coursera, teaching staff and all who made this happen

Great Course. The best part about it is that you are forced to dig deep into various resources and work hard on your assignments, which helps you to apply everything you will learn from the lectures. Extremely practical and totally hands-on. Looking foward to the remaining courses in the specialization. I feel so much more confident about not only creating amazing visualizations but also about acquiring datasets and preparing them, which we learnt in the previous course.

I continue to like the way the Prof. Brooks explains the different topics, the selection of the topics themselves and the scientific articles are very enriching. I was previously an HCI researcher and it was a pleasant surprise to find such great art Thanks for sharing them! It was defenetly a challenge for me, learning it all and doing the assignments. At the end, I'm proud, I've learned a lot and l'll definitely share what I've learn so far. Thank you!

The best course, that i would recommend for if anyone wants to cover a lot of basics in the field of Data visualization, The course assignments and emphasis on self learning, and making us familiar with many top websites like stack overflow and geeks for geeks to ask and clarify our doubts.

I recommend the beginners doing this course to document each of their assignment and make a repository in Github that would add a good value to your profile.

I was skeptic about this course since I am beginner to applied plotting and charting. After watching all videos, i felt overall course is intermediate level and well organized. I went through online search to understand all details mentioned in video, moreover I gained knowledge by looking at the assignment and solving myself with the help of stack overflow. I wanted to learn something new, and it did.

Thank you so much, Christopher Brooks !

This course is amazing! The assignments are really challenging and force you to work hard. It could be longer, with more information about Seaborn but it's okay. In the final project you are free to choose what chart you want to create and what data you want to use. The peer-reviews are fast. The most interesting thing in this course is to learn how to create dynamic charts with interactivity.

I​t shows exactly what is expected, it is similar to a master's class. The teacher explains the main concept and some methods to solve specific problems, but there are much more to learn. Therefore, look at this course as a guided course, more you search, better you become; Thus, it gives you hints, makes you think in a different perspective and allows you to understand what you have to do.

This course is extraordinary. The faculty initially explains you the basics and then requires you to do some digging from the documentation and on the forums, but it was all worth it. I couldn't have asked for a better faculty than Mr. Brooks for this course. His explanations of the concepts is perfect and to-the-point. I thoroughly enjoyed doing the programming assignments in this course.

In addition to giving practical guidance in plotting and charting, the professors also give a simple but comprehensive explanation of the structure and functioning of the matplotlib.pyplot module, even though it doesn't require you to understand the deeper structure when you use the function, it certainly doesn't hurt you for learning more, especially when you want to be an expert in this.

I found this module to be the most enjoyable of all the Data Science courses offered by UMich. The method of instruction isn't only aimed at plotting data in various charts but it also focuses on the subjective part of visualization. I had fun doing the assignments, especially the 3rd and 4th week assignments, and I could say that I have improved a lot with my visualization skills. 10/10

This course is excellent because it teaches not only how to create customized visualizations using matploltlib in Python, but also what principles one should follow to create an excellent visual. The assignments are designed in a way that you get to enforce those principles on the visualization you create - making them memorable throughout your Data Viz career.

To all of you who have done the first course under this specialisation - you have GOT to do this! Its simply amazing, and will mostly deal with the practical side of things. You will learn skills to be able to clean, analyze and plot data beautifully on your own! I'm a student of grade 12, studying under the CBSE curriculum. If I can do it, SO CAN YOU!

Taking up this course is a great way to understand how visualization libraries are organized in python. Instead of just stating down functions, the instructor has actually gone through the trouble of explaining the whole underlying architecture of how data is stored and rendered from back-end. Great work! And thank you for organizing a superb course.

There are so many components to plotting that I didn't take into consideration, and this is after having gone through a Master's program in statistics. I have taken many of the simple things into mind each time I create a visualization at my job. Thus far, I have found the first two courses in this series invaluable and highly recommend it!