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Voltar para Data Visualization with Python

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

4.5
estrelas
9,493 classificações
1,420 avaliações

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

AM
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!!!

SS
20 de Nov de 2019

It's a really great course with proper hands on time and the assignments are great too. i got enough opportunity to explore the things which were taught in the course. Really Satisfied. Thanks :)

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1101 — 1125 de 1,412 Avaliações para o Data Visualization with Python

por NANA K M

9 de Mai de 2020

Une qualite exceptionnelle

por SEKHARAMANTRI V K

22 de Jun de 2020

Few things are direct.

por Senyo A

15 de Abr de 2021

Great job thank you!

por Akash M

22 de Jan de 2020

NICE MENTORED COURSE

por Svetlana O S

12 de Jan de 2021

a lot of new skills

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 tanmoy p

16 de Dez de 2020

good content.

por Nandivada P E

11 de Jun de 2020

nice course

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

excellent

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

Good

por SRINIVASULU B

12 de Jun de 2020

GOOD

por DEVARAMPATI M S A

27 de Mai de 2020

good

por Sai V A

20 de Abr de 2020

good

por KVD S

28 de Fev de 2020

good

por Veronica A S

28 de Abr de 2019

Good

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.