Comentários e feedback de alunos de Data Visualization with Python da instituição IBM

Very useful and good explanation. The topics could have been subdivided more so the each tools could have been explained orally rather than working fully in the lab session

Video lectures are compact. To really get to know the matplotlib, a lot of work needs to be done during hands-on lab and self study. But it is a good introductory course.

Data Visualization plays a vital role in ML. This course helps in understanding various visualization tools and plots. Nice course to know about matplotlib, folium, etc.

A fairly good introduction. The scripts can be a bit advanced for those who are new to Python. It's best to have the documentation open on a different tab at all times.

This course has very good topics on Data Visualization, I must appreciate the exercises in lab and the final assessment which really helps you work on real-time data.

Un curso muy completo y con ejemplos prácticos. El proyecto final me permitió investigar mas sobre las opciones y atributos de las librerías para construir gráficas.

Excellent ! Although most of plots that I have learnt before, the map plot with folium is very attractive to me and I have got so much new things. Thanks professor !

I love final assignment, that's too hard for me at the beginning, but it's turns out to be very easy when I figured out. I was overthinking for the condition. lol

Let's you know the methods and techniques that you can work on real-time scenarios. Final assignment will make you feel great letting you to work from scratch.

Very well designed course. Clearly explains each module how to do it and then lab exercises gives us pretty good hands-on experience on the concepts we learn.

Very good course on understanding scripting layers and artist layers, as well as going over all basic graphs and advanced graphs. It was definitely rewarding!

It's an excellent data visualization course with Python, which is supported by external tools promoting knowledge and practice of what is seen in the course.

It's an excellent data visualization course with Python, which is supported by external tools promoting knowledge and practice of what is seen in the course.

This course was presented in a way that challenged me more than other courses in this program. I was very happy to have been challenged to think critically.

The assignments carry some general templates for data visualization. Downloading jupyter notebooks of them helps me when i visualise some othe data. Thanks

Among all the other courses in IBM Data Science, I liked how this course emphasized on the practicals while giving a good idea in the videos. Thank you Sir

Lab materials are really good.. and the assignments in the course need additional research than the learning available in the course which is really good..

Really like it, the maps are not working in MS Edge, and took me a lot of time to figure out, those thinks would be great to be announced in the training.

the content is new and interesting to me personally, however some sample codes are now deprecated so you'll have to read the doc from PyPI of the package

I had a good idea of basic statistical plots, but this course actually shows you how to make them attractive and effective for presentations and reports.

Lots of in-depth labs. However, final assignment required some techniques that were not covered at all, so the difficulty was much higher than expected.

A very good course! The Jupyter Notebooks are structured perfectly to follow the steps and action without difficulties. Had a great learning experience!

Thanks for the well-explained and comprehensible introduction to Data Visualization with Python. The best thing about this course was the lab sessions!

Good Course to understand the topics of data visualization and dashboard creation using Python libraries such as Matplotlib, Seaborn, bokeh and Plotly

The course is designed very well and each topic is explained in easy to understand manner. Also the labs are very well designed to clear the concepts.