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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
9,484 classificações
1,419 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 :)

Filtrar por:

851 — 875 de 1,411 Avaliações para o Data Visualization with Python

por Yu M C

9 de Dez de 2019

good

por Manea S I

14 de Set de 2019

nice

por Prabhu M

6 de Set de 2019

good

por Nay L

13 de Jul de 2019

good

por Aditya J

22 de Mai de 2019

None

por Piotr M

28 de Out de 2018

Nice

por John R

9 de Jul de 2020

o

k

por Muhammad T A

16 de Set de 2019

<3

por Ali C B

21 de Dez de 2020

.

por FAN Y

25 de Jul de 2019

I

por Manivannan D

20 de Fev de 2019

V

por banan A

11 de Jan de 2019

H

por Nima G M

9 de Nov de 2020

Before visualizing any data, one should gather and import those data to their computer directory, and this could not happen without the Pandas library. Importing the data could be done simply using the Pandas library, whose functions somewhat overlaps with the Matplotlib library.

Although in the last week, the author introduces the Folium library, which is a library to visualize Maps and other related things that could be shown on the Maps, like the population density of different cities in a country, the main focus of the course is on the Pandas library, which is, of course, need that lots of attention and time.

In summary, this course is especially helpful for those who want to become familiar with the Pandas library.

The author also gives a very short amount of time to show how seaborn could be used to plot the regression plots using seaborn.regplot function, which is also showing wise time management by the author since it does not need more amount of time to spend on.

por liam c

7 de Mai de 2021

The course and materials were very useful. However, there are a couple of things that I would like to flag up for possible improvement

There's are over reliance on the Jupyter Notebook and a lot of useful information that should have been in the videos was pushed into them

I know Dash is a large subject to cover but more information about the call back mechanism in Dash would have been useful - Fortunately I've used Dash, Matplotlib and Flask for a few years so it wasn't much of an issue for me.

Every video spent the first minute going over the data layout rather than focusing on information about a particular function (plot)

The biggest issue was the fact that I had to ask to be moved from an inactive session group, to an active one, to get access to the external tools and tests. This has impacted a large number of students and I have left a 'how to raise a support case' note in the discussion board for the group I was originally with

por Amy P

26 de Mai de 2019

Once again, quality hands-on labs were the highlight of this course (as has been the case throughout the IBM Data Science Certificate courses). The end-of-week quizzes were also a bit more difficult/involved, which was a good challenge. Still, I think there's room to increase the difficulty a bit further - after all, you can re-take the quizzes if at first you don't pass. I appreciated that the final project gave us the opportunity to apply a wide range of the skills that we learned.

That being said, I think there was quite a bit of fluff in the lectures. I would have preferred more content/exposure to other libraries rather than the redundant "data recaps" at the beginning of almost every video. I also would have appreciated more theory/recommendations for selecting the best visualization for a given application.

por Lena N

26 de Set de 2018

The best parts of the course were the labs and the final assignment. I spend a lot of time at the labs, paying extra attention to the details and often following the external links suggested by the instructor. I found the final assignment very interesting with good explanations step by step and I especially liked how the instructor were present at the discussion forums.

The weakest part of the course were the videos, I think I could have skipped them altogether. The information mentioned in them were elaborated much better at the labs. Also, for some reason, 1/3 of each video was exactly the same clip recalling the dataset. That felt a bit useless and loss of time! On the other hand, each video was a couple of minutes long so no big deal in the end.

por Erik A

30 de Jul de 2020

I have two minor issues. First, the final assignment called for a few things that were not directly discussed in the class. The class did recommend reading the documentation, and the needed information was available there. This is probably more realistic for a real world environment, where you won't know all the ins-and-outs of an API before using it, but a little warning at the top of the assignment would have been nice.

The second issue is that folium.choropleth() is now deprecated and produces a warning if you use it; the recommended alternative is to use the folium.Choropleth() object. Using the old method produces a warning, but works (for now). The labs and lecture should be updated to use the new API.

por Paul A

24 de Set de 2020

This course was a change of pace compared to the previous, absolutely stellar courses in the Applied Data Science specialization. The instructor is different and the methodology as well, the content was equally as digestible as the courses that preceded it, but at times the course had inconsistency on its quality. There was a lot repetition and it felt like padding at times. The difficulty and learning curve takes an abrupt spike on some of the assignments, but nothing you can't manage if you put in the work and leverage on the content of the previous courses.

por Jess M

27 de Fev de 2019

The videos are nice and clear, the visualizations are beautiful, and I'm sure that all of the libraries presented are extremely useful. But this course is not well-suited to students who have no prior background in Python before taking the Applied Data Science specialization. I look forward to coming back and maybe having a shot at understanding the code in the labs after I take a Python programming course. The long chunks of code presented here are mostly opaque if all you have are the previous courses in this specialization.

por Ajin

13 de Set de 2021

The course is amazing but the labs are really complicated as many of the things used in the lab are not been taught in the videos. It would be very helpful if after the labs a video explanation is given about each problem in the lab or the complicated ones. Even the peer graded assignment seemed little complicated because some was not taught. It was difficult to type out the code. Only this found as odd. Rest were absolutely amazing and teaching by IBM professionals. Thank you so much IBM and Coursera!

por Ruben G

28 de Nov de 2020

The content of the course is interesting, especially the last modules. However, there are some cons.

The content of the lectures (videos) is somehow redundant. Another "negative point" is that the final assignement is not 100% doable with the contents of the course. There are details that are not covered by the lectures.

It should be easier to complete the final assignment in our computer with a (local) notebook. It seems to me that the lecturer wanted us to use Jupyter

por Henry W

22 de Set de 2020

I Learned a lot in this course and the teaching assistants have been very helpful in the forums. This is very useful information that I learned and I highly suggest this course. The final assignment was quite a jump from the videos and labs and took a lot of work to figure out. The labs could have supported the final assignment better. Also, perhaps more work and examples in the labs would help to learn the material better. Thank you for the good learning.

por Azhan A

20 de Nov de 2019

The reason I'm giving it 4 stars is because the although the content was good, the labs were challenging but there are something which I found missing, for example, there should have been more information on libraries related to cholorpleth map. !wget was not working on my PC's jupyter notebook and looking it up on the internet was even harder because this extension or whatever it is big on its own. I don't know what to write to get the correct google search.

por Monali C

14 de Jun de 2020

It was a great learning experience with coursera.After Data Science course ,learning Data Visualization with Python was my next target to complete.I learned many basic and advance things about how to work with data using visualization.With every questionior and assignments it was interesting and challenging to learn from this course.Thank you coursera for this course it was really helpful to learn and know about data visualization more accurately.

por Joshua S

25 de Jul de 2021

Like every review I've written before: there was tons of good information in the videos/readings. the test/quizzes properly evaluated the information presented in the videos. and the labs reinforced the material presented from the videos through real world application. Just the final lab project is way more difficult than anything previously presented in the class and there is little to no help from the instructor, coursera, or anyone else.