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Voltar para Data Visualization with Python

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

10,265 classificações

Sobre o curso

"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....

Melhores avaliações


27 de nov de 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 de ago de 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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1201 — 1225 de 1,553 Avaliações para o Data Visualization with Python

por Manikandan S e

4 de mai de 2020

Very good course.

por Sergey Z

25 de abr de 2020

Very small course

por Raj K

9 de jul de 2018

Great course :)

por Mohammed A A A

29 de mai de 2022

greate cource

por tanmoy p

16 de dez de 2020

good content.

por Ernesto C M P

15 de jan de 2022

good course

por Nandivada P E

11 de jun de 2020

nice course

por Shailesh Y

13 de ago de 2022


por nico

18 de nov de 2020

Very nice!

por Alex A

14 de out de 2020

Great Job!

por Omer. K

14 de set de 2021


por Marcin

21 de jul de 2020

Too easy

por Jacob K J

12 de ago de 2019

good job

por Venkata T

29 de jun de 2020



12 de jun de 2020



27 de mai de 2020


por Vishal A

20 de abr de 2020


por KVD S

28 de fev de 2020


por Veronica S

28 de abr de 2019


por Franco M V

16 de mai de 2020


por Louis J

30 de jan de 2020

I have mixed feeling about this course. I think the purpose of this course (visualizing data) and the different ways of doing it is really motivating and awesome, specially when you realize all the things you can do (types of charts , maps etc...). This is actually awesome!

However, on the down sides:

-Each video repeats the steps on how the database used in each course has been "cleaned". I agree with the feedback from other people, reminding us one or two times is fine, but in each video... This is too much!

-I would have liked more practical exercises, specially to plot multiple linear regression models (and polynomial of different degrees, in particular), to display on a chart, and to make predictions. That would be great !

-Labs: they are of unequal difficulty: some are relatively easy to complete, some require more thinking/research and time, while some have no question at all or very little. Maybe it would be useful to re-organize the labs ?...

-Week 3: as everyone mentions, the "artist layer" method is only briefly covered in one of the lab. It would have be really useful to spend more time on it, and on all the things we do with it. Like others, I spent lot of time searching online, and it took me a full afternoon to complete that part of the final assignment !

To summarize: it's a very important and interesting course, but video lessons should be re-recorded with deleting all parts repeating the initial database processing, and adding more topics such as artist layers, etc. Also, maybe split each lab in 2 since there are few labs in this course, but if we follow them correctly, it requires quite few hours to spend on each lab (at least for "beginners" like us starting learning about this topic).

Thank You !

por Farrukh N A

1 de jul de 2020

I hold a degree in computer sciences with majors in Software Engineering so please take this review of the course seriously.

Unfortunately, this is the only course where it seems the teacher never had any outline as to what he needs to teach and how.

1) He has made the video lectures useless as he declared himself that the videos will be short but you have to 'read' lines and lines of lectures to get a grasp of the visualizations he will teach. I think he don't know if it was that easy for a person to get knowledge then he would have just read text books and would have gotten the degree as according to him there wouldn't be any need to educational institutions.

2) Many times, he introduces many 'advanced' functions of Python which was not taught in the previous course which was about Data Analysis by Python. I don't have any problem in learning new things everyday but using multiple advanced functions in a 'beginner' course makes it tough for student to grasp what he was trying to teach.

3) There are far better and easier ways to do many things but it seems he deliberately uses long, tedious and advances methods for plotting various graphs and makes things confusing again and again.

4) Lastly, he himself gives advanced quizzes for the stuff which were not even taught extensively and it makes hard to even pass them.

por Neil C

10 de mai de 2020

The rating of 3 is because there are some excellent points to this course and some issues. First, no doubting the Instructor knows his stuff and he has a good style, but for EVERY lesson to repeatedly go over the details of the data set used (and you can tell this is one clip pasted in every lesson) is mind numbing. Cover the data set once and then simply say "We will use our Canadian Immigration Data set, refer back to it if you have question" . Then use this time to go into a bit more detail on the graph mechanics. Secondly, there is no lab environment for the final assignment (as was provided in precious courses of the Data Science module). This overly complicates the assingment beyond the material being tested (I was bangin my head as to why I could not get a graph working until I realized it was the lack of an environmnet variable, not my code, that was causing the issue.

por Manuela G

19 de nov de 2018

The course itself was good.

Unfortunatly it was not clear at the beginning, that the "Data Analysis Module" is a pre-requisite. After struggling with the lab of week 3, I found out and took the Data Analysis Module. I tried the lab again - meanwhile the first part has changed - the file was not in the same structure. So, the code I wrote before was worthless. Took a while to figure this out.

Then in CC Lab the "conda install" did not run - neither in the lesson, nor in the lab - therefore I spent many hours struggling to find this out - didn't know, if it was my coding.

It would be good, to improve those "organisational problems". That's why I only gave 3 of 5 stars. It did cost me a lot of time.

The content and lessons and exercises and the lab itself is very good and interesting. Also the amount and speed, very good to handle besides a full-time job (if everything works ;-) ).

por Luisa V

1 de jun de 2020

The course is very informative with step by step explanations. However, there are too little teaching staff to answer all the students questions. As well, throughout the lab quite a few things were unclear (i.e. a certain map is not available for free users, a certain tiles doesn't work with maps, something must be downloaded/imported despite saying it must not). These things could have been mentioned in the lab instead of having to look through many students questions on the same issue up to two years ago. The importing/downloading parts of the code were also very slow on the notebook and it often had to restart often due to this. The final assignment discussion page often crashed and froze too but all the other discussion pages worked very well (no crashing or freezing, fast loading times).