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Avis et commentaires pour d'étudiants pour Data Visualization with Python par IBM

8,519 évaluations
1,187 avis

À propos du cours

"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data. One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions. The main goal of this Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

Meilleurs avis

27 nov. 2018

The course with the IBM Lab is a very good way to learn and practice. The tools we've learned in this module can supply a good material to enrich all data work that need to be presented in a nice way.

13 août 2020

Great course, one of the best course to get hands-on learning for Data Visualization with Python. Particularly the lap exercise, it will make you think on every line of code you write. Excellent!!!

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251 - 275 sur 1,172 Avis pour Data Visualization with Python

par JUAN J T R

26 juin 2020

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.

par Bryce Y

3 févr. 2020

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.

par Keerthi K A M

7 août 2020

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

par Jeevan K J

18 mai 2020

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

par Vijayalakshmi K

27 juil. 2019

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..

par Heraclio R

4 nov. 2018

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.

par Hieu D T

17 oct. 2020

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

par Karl J

23 févr. 2020

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.

par Carlos N J

13 janv. 2020

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.

par Juliet M J

27 oct. 2019

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

par Kuber B

7 août 2020

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.

par prakriti p

23 mars 2020

I liked the assignment presented by the course. I learned from solving the problems. The constant error with the lab problems discouraged me at times.

par Gregor H

10 oct. 2018

The tutorials are brilliant and very useful! Make sure to complete them and you will get an extremely beneficial intro to several visualisation tools.

par Bakari D

27 juil. 2019

The project was well done. To be successful you have to complete the labs. The lab materials are a really good balance between practical and theory.

par José E S V

8 août 2020

Realmente un curso muy practico para aprender sobre todas las herramientas y librerías que ofrece Python para la visualización de datos.


par Venkat N N

30 nov. 2020

Very good entry point into data visualization using Python. Found associated labs and assignments to be very helpful in reinforcing the concepts.


11 oct. 2019

The course is made in very simple language, anyone can learn from this course. The most amazing part of the course is Lab. Love you IBM & COURSERA

par lara l

30 juin 2020

the teacher of this course has made great designs and offered rich resources to students. I personally like his teaching style a lot. thank you!

par Familusi O A

16 avr. 2020

Amazing challenge for enthusiastic learner, i would definitely reference the course materials several times more just for its depth. Thank you.

par Sachin K K

29 mai 2020

The course is brief and to the point and is providing you with great practical work to get a hands-on practice to make you ready for the world.

par Ravindranath R

20 déc. 2019

Very clearly explained and lab is excellent. Like the style of providing description of datasets used in each lab. Thanks a lot to instructor.

par Nhan T N

15 mars 2019

Nice course. It is short video, but well-composed ones. I love labs, it focuses on key points of visualization. I learned a lot here. Thanks!

par Krishna K S

4 août 2020

Thanks for IBM for providing these courses and the content of the material is good for who coming from different domain can also do easily.

par Devvrat M

28 déc. 2019

Detailed explanation in the lab section on how to implement each visualization tool to better understand its use case in various scenarios.

par Eden P

19 févr. 2020

Great course. Demonstrated some great techniques on representing data in an informative way. Will definitely use the learnings in future.