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

I think there there is too much time given to the esoteric of what makes plots pretty rather than the nuts and bolts of how to do it and the limitations of using Pandas and Matplotlib for real world data

I found the lectures interesting and thorough yet short and to the point.

The course gives the background to information visualization that is a key in any engineering, scientific, and data visualization tasks. Then it is followed by the essential visualizations in the area (scatterplots, lineplots, boxplots, heatmaps, etc.) and the libraries that visualize and support the visualizations (matlibplot, panda, numpy, seaborn). As for the target audience, people from computer science, mathematics, physics and engineers will feel in the course comfortable. It is not only presented in an easy to understand way, starting with concept and going into depth, but also detail are given in case one is interested to advance and strengthen their skills. With 10% of effort you'll be able to reach 90% of knowledge/skill/result. The impressive thing is that the creators of the course also offers way for you to spend remaining 90% of your effort to deep dive and advance in your skills. For this course, you may expect the highest standards with respect to the course material (videos, presentations, resources), structure of the course, presentation style, the assignments. Well done indeed.

The course has been delayed in starting. They are evidently making some changes to it. You should consider taking another course if this one still says "starting soon."