Ratings and Reviews for Applied Plotting, Charting & Data Representation in Python

This course needs a serious overhaul. Assignments are very unclear and only reviewed by other students, which questions the legitimacy of this course certificate. Lectures are shallow and clearly made by very unexperienced lecturers.

This course has given me deep understanding of data visualization

I liked this course, but I thought that it would be a little more advanced. I would have liked if it dived a little deeper in how to use visualizations to make decisions while analysing and cleaning data.

I liked this course. It was very practical. The reading material was very interesting and valuable. Project had some flaws in terms of formulation of questions but they really pushed me to search and look for help. That in my opinion was actually good and I think that after each of these courses there is still a lot we need to learn ourselves. The course materials was laid out pretty well. Sometimes I had a feeling that things were a bit rushed (like introducing seaborn at the very end) . There is a lot of software terminology involved in the beginning when explaining matplotlib notebook and it was hard to follow that part. My biggest complaint is the Coursera's online Jupyter notebook. I got very frustrated with it. Even if you save your work frequently it often happens that the connection does not work or isn't strong and after you close your assignment you edits are lost!!! My advice, download all necessary links and work in your own Jupiter notebook and then upload the assignment.

An excellent course with lots of knowledge about innovative principles for plotting. Can get a little heavy to follow.

I am confused how to rate this course... Let me introduce my personal Pros and Cons Pros: 1) I've learned A LOT. 2) Assignments are really interesting. 3) There is a Peers Grading system, which I personally like. 4) If you really dig into problem - there is a big chance you learn cool things. Cons: 1) The Professor explains only the very basic stuff. It's a bit disappointing because I finally was doing the assignments with external sources of information. It was not much usage in videos. 2) You have to spend tonnes of time on your own digging into possible solutions to learn how to do the assignments. But if you care only about passing it - don't worry it will take you maximum 1 hour as there are a lot of already done examples on many sites. 3) While grading the assignments you can see a lot of copies. Once I've found my own project copied. After that I decided to leave the code with advanced charts only for my personal usage and for assignments - the simple basic charts. To sum up - great source if you like exploring new things and digging into details on your own. It's like a tool that give you some direction and base to start. If you prefer to get information ready to use - it's not for you. I put 4 stars out of 5 as it was a great help for me but still almost all the information I had to find on other sources.

Dr Brooks, himself an eminent researcher in Data Science himself, has made a well-laid out plan towards the data science learning track. The theory behind each application is also explained appropriately for better understanding of each topic.

I learnt a lot from the course especially in the visualization and data analysis. The assignments are challenging but the things are covered in the courses and the recommended essays are quite useful. Hope the project can cover more dimensions of the visualization, and be more specific when giving the instructions on the assignments.

That coursera is wonderful thank for this course I understand the data representation in python with matplotlib, seaborn and pandas. It was very helpful for me.

Extremely useful, i've referred back to it several times.