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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
9,586 classificações
1,434 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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926 — 950 de 1,427 Avaliações para o Data Visualization with Python

por Jacqui T

29 de Mar de 2020

Labs are very interesting. Would suggest including more data wrangling techniques (to better align with the final assignment), and removing Mapbox Bright references. On the whole, this was a far more interesting module than I had expected.

por PATEL D K

3 de Mai de 2020

The Course helped me to clear my doubts and made my concepts of Data Visualization more strong.

The Ungraded assignments helped me to apply the concepts in practice. The quizzes were easy and I think there should be more questions in quiz.

por Matthew A

28 de Mai de 2019

OK overall - but I wish there were more and smaller hands-on exercises. Also, waiting to load 3rd party libraries in exercises is quite slow (3-5 mins for choropleth, for example) - it would be nice if these could be pre-loaded somehow.

por Paul R K

16 de Ago de 2019

Good intro to matplotlib, visualization of dataframes. Some of the more advance content, e.g. choropleth maps, relies on older versions of some of the python packages (folium) so the examples need to be updated for the newer versions.

por tal h

14 de Jun de 2019

the course is great, however, I think matplotlib's structure should have been explained in greater detail, this would help the student to accelerate the understanding of the library's documentation and implement his visualizing needs.

por Luis A A

13 de Set de 2021

Great module to learn about the most common different types of plots we could generate with Python coding. I would suggest to deepen more in Matplotlib's Pyplot scenarios, including tick, label, legenda nd filling options.

por Leonardo J C

25 de Mai de 2020

I enjoyed the course to the fullest. My only complaint is regarding question number 2 in the final assignment. The bar chart that we were requested to create and display is not shown in the videos or labs how to create it.

por Reşat C B

7 de Jun de 2020

Generally good content with great lab additions except for Folium. Folium 0.5.0 is outdated (it is 0.11.0) now and the choropleth method is deprecated. Also, the final assignment threshold label differs between versions.

por Kenneth C H K

8 de Jan de 2020

Course content is good. But there're some replication for each video about "recap of the data". The final assignment is quite difficult because I need to find some codes from the internet to meet some task requirements.

por Lingyan F

16 de Jul de 2020

After learning, I still feel a bit confused. I think it would be better if there is a comprehensive summary, such as: what graphics use which imports, and the comparison between the coding required by each graphic

por Abdouraman B D

15 de Dez de 2020

Very tough course, needed to really dive into books about folium and etc...for the final peer to peer grade exam

but thats fine, sometimes in data science you need to really look and search to find solutions.

por Florent M

7 de Mai de 2019

Cours intéressant et évaluation pertinente. Il est cependant plus optimal de s'appuyer sur des ressources externes pour avoir accès à des mémos sur Pandas et Matplotlib (il y a de très bons sites là-dessus).

por Phenil B

17 de Abr de 2019

Videos were short and could have explained the lab work better. Also, the Data was discussed in every single video which was annoying and I always skipped 30 seconds in every video.

The course itself is nice.

por Joshua M

31 de Mai de 2020

Course material did not prepare you well for the final assignment, the final assignment was too difficult and didn't have enough clear instruction. Overall, the course material was very interesting though.

por M.P.Jananee

31 de Dez de 2019

Course was interesting. Few more sample exercises on the features of map, artist layer could have been useful. Since these are more visualizing concepts which requires more practice and thinking. THANK YOU

por Tiffany W S

24 de Set de 2018

This course and the following course "Data Analysis with Python" should be switched. It's mentioned that "Data Analysis with Python" should be completed before this one but they are in the reverse order.

por Darwin M

15 de Mar de 2020

Good course, some of the lab assignments did not load properly so it was difficult to practice... (week 2 & 3). Assignment was good after using Jupyter Notebooks as the scripting interface. Thank you!

por Alexandre N

21 de Dez de 2020

This course is asking for more details. It could be extended to one or two more weeks in order to provide broader understand and examples of how to make good use of visualization tools and resources.

por Siwarak L

7 de Nov de 2019

The final assignment requires self-research (not included in the course material) to fully complete the required items. The course shall cover all that the assignment requires, at least touch a bit.

por Юдин В Д

22 de Jan de 2020

In each video we transform dataset and it take more 1 minute for each video. Will be good if in video will be some quick quiz as in "Data Analysis with Python" and "Python for Data Science and AI"

por Tirth J R

25 de Dez de 2020

The Course Was Good. It would have been better if some lab sections were covered in labs. As we all know understanding a code then reading might help the students grasp better faster and deeper.

por Mahvash N

15 de Mai de 2019

More in class projects similar to final assignment where we can challenge our knowledge as we are all remote and it takes time to communicate through the available coursera forums.

Thank you.

por Manik H

8 de Jun de 2020

The labs were good but the issue was the extremely rushed up videos. A lot of concepts, especially the artist layer was not covered will in the videos, which made me give this course 4 stars.

por Miguel C V

5 de Jul de 2020

I learned solid bases on different data visualization tools, it was an overall good course. The one thing I think could be better is to provide more exercises to work with the Artist Layer.

por Carsten K

13 de Mar de 2020

Good coverage of different plots. Videos are somewhat repetitive regarding the dataset (most of them could be about 20% shorter due to this). Labs (in Jupyter Notebooks) are great practice.