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

4.5
étoiles
9,247 évaluations
1,372 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

AM
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!!!

SS
20 nov. 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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901 - 925 sur 1,356 Avis pour Data Visualization with Python

par Dalil A

15 déc. 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.

par Florent M

7 mai 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).

par Phenil B

17 avr. 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.

par Joshua M

31 mai 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.

par M.P.Jananee

31 déc. 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

par Tiffany W S

24 sept. 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.

par Darwin M

15 mars 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!

par Alexandre N

21 déc. 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.

par Siwarak L

7 nov. 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.

par Юдин В Д

22 janv. 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"

par Tirth J R

25 déc. 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.

par Mahvash N

15 mai 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.

par Manik H

8 juin 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.

par Miguel C V

5 juil. 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.

par Carsten K

13 mars 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.

par SAMIR B

6 mars 2020

The course was beautifully structured. I would like to request to add the conditions on which tiles Mapbox Bright works. At times the tiles dont work and we are not sure of the root cause.

par Shivam S

25 sept. 2019

Kindly update the final assessment of this course work since it is quite difficult to work with it, as the content related to the assessment cannot be found in the course videos. Thanks !

par Christopher I F

30 avr. 2021

I learnt an awful lot so I would give the course at least 4 stars. The opinions I got from the forums and the marking was that a lot of people really struggled and quite a few gave up.

par Henry C Y

24 mai 2020

Excellent course. The labs really challenge you because some of the material is not directly taught or the syntax differs slightly from what is taught so you have to hunt for answers.

par William P

27 oct. 2020

Great Course, would have liked to have labs/exercises that coincide with the video as he is presenting. Instead, it is designed to watch the video then go back and complete the labs.

par Abby M

8 oct. 2018

The course had a great examples and samples for common and uncommon visualizations. The course lacked the background to be able to import the geojson properly for the final though.

par Farah A

4 oct. 2019

Good course, but I found the final assignment hard to complete, spent quiet sometime researching to be able to complete it. Providing the correct solutions would be helpful

Thanks

par Jakhongir K

31 mai 2020

Overall really good. However, would be better if a few videos added about object-oriented visualization. Also some links and methods used should be updated to the latest ones.

par Michael J L

25 mars 2020

Best of the 5 IBM Data Science Courses I've taken so far. Some problems connecting with the labs, but you can bypass these by downloading the ipynb's from cognitiveclass.ai.

par Govardhana

30 juil. 2019

It was very nice and brief course but it could have been better. Some other topics must be included and some more exploration of different properties needed to be addressed