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Voltar para Data Visualization with Python

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

4.6
estrelas
7,078 classificações
908 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

SS

Nov 21, 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 :)

RS

Jan 08, 2020

This course gives very well knowledge about different types of visualization techniques and helps to start with visualization. Coursera provided an amazing course with an amazing instructor.

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701 — 725 de {totalReviews} Avaliações para o Data Visualization with Python

por JOSHY J

Oct 31, 2019

This course is a little disappointing for me. It is a 3 Week course and content you learn in this course are not even cover introductory sections. The Final Project is So hard, that it didn't cover the important sections. I don't suggest this course if you are really serious about Data Visualization.

por Kevin O

Apr 19, 2019

None of the labs data imports worked. The majority of the video content said to take the time to really learn the topics via the labs. The final assignment data sources worked, so at least that could be completed. Paid courses really need to have external dependencies reliably available or updated.

por Mark H

Feb 11, 2019

Good content to know. Fair but not great in terms of presentation. Many videos repeated how to prep the data frame so you end up watching the same 2 minutes several times. Also a lot of the things you had to know you had to figure out on your own versus finding it in the material presented.

por Giselle

May 25, 2020

I didn't completely understood the labs and where some lines of code came from. Also, I felt that we don't get enough directions to complete the final assignment, not even which notebook to use. This has been by far the most difficult course of this training in my opinion.

por Yanis B

Nov 25, 2018

Great course except of the final assignment being based on a deprecated or soon to be deprecated version of Folium Choropleth implementation. Please review that part as it could be very confusing to students that do not use cognitive class as their development environment.

por Sean M

Jan 20, 2020

Since students weren't able to submit code, this made it extremely difficult to answer the final project (which I couldn't figure out how to finish). Getting feed back on how to correctly code the answers is more important than showing a screenshot of the final product.

por Aditya D

Jan 12, 2020

Need more clarity and practice for this course. This course seems the toughest as it asks for memorizing artistic layer syntax which seems so difficult coupled with the humongous choropleth map!

A huge amount of practice is needed for this certificate even after labs!

por Collin G C

Jan 08, 2020

The information was valuable and generally well explained. The final was a massive failure; the classes and examples prepare us for maybe half of the questions, but all the questions depend on building off each other. The only way to pass is to Google for hours.

por Pablo D B

Jul 20, 2019

I had many issues when people marked my final assingment. Maybe the indications should be clarified. For example some people didn't gave me the points for not showing the dataframe with the rows in the same order, although all the rows were respectively correct.

por Eunice C

Jan 09, 2020

not too practical over the course, a lot of theory based which is great as well. But I personally not a big fan of the Watson studio as it's not user friendly. I have to go through a lot of layer on their site before getting to the studio or the notebook.

por Muhammad Y R

Jan 16, 2020

The Course Was Perfect And Was The Lab.The only thing that was so annoying was intructor just give a brief introduction and left the topic with lot of confusion.Lab was annoying to it was very hard to open and was giving so mcuh error

por Ashraf

Feb 10, 2020

The course would require revision to introduce the concepts in a simplified matter with different data sets. I also believe a lot of the detailed concepts are left for the course takers to explore to fully comprehend the material.

por Rohith P R

Apr 19, 2020

Need more concepts to be discussed for modifying charts using artist layers. 25% final assignment was based on artist layer, but the different options of artist layer are not explained like ax.spines 'top' .set_visible(false).

por Shan C

Nov 17, 2019

The data visualisation videos are repeating itself most of the time, but the final assignment is super hard, which many of the details were not mentioned in the courses materials - no clues to do the assignment at all..

por Adam J L J H

May 25, 2020

I think that more explanation about the syntax could be taught within the videos. As of now, most of the syntax is being taught within the hands-on lab practices which does not offer much explanation to it.

por Ashish D

Dec 22, 2019

Does the job of a good introduction.

Very limited and restrictive practice and assinments.

For a true learning experience one needs to do a lot of external research and work to show a measureable benifit.

por Pouyan K

Jun 23, 2019

The final exam is really vague and not organized. It would be a much better course if the instructor made exam in the JupyterLab like other courses. Also, the videos are not very comprehensive.

por Nikhil J

Apr 19, 2020

The content of the course is good. But, it was not gripping or engaging. Probably, because the instructors voice was inconsistent, modulations and variations. Overall, ok. But NOT satisfactory.

por Andrea E

Dec 19, 2019

PRO:

Content

CON

recurring technical issues (data on final assignment not available )

description of final assignment not clear / inconsistent to previous courses, no jupyter notebook provided

por Kailas K

Oct 14, 2019

The videos are very short compare to exercise covered. Assignment gives overview of how much deep the coding can go but video should be elaborating few aspects of layers of matplotlib.

por Dr S K

Oct 29, 2018

Again I cannot access the cognitive class ai and this has truly hindered my learning experience. I cannot open any jupyter notebooks nor can I submit any assignments, This is really bad

por Carol L

Jan 15, 2020

Me pareció super interesante el curso, pero los videos muy cortos dejando todo el material para el lab, y el final assigment con solicitudes que no fueron explicadas durante el curso.

por Jessica L P U

May 20, 2020

The assessments are a little silly- the quizzes trip you up on minor syntax instead of being concept-focused, and the final assignment used some skills that weren’t taught.

por Everett T

Jul 10, 2019

1) Quite a lot of contents of the final assignment are not covered in labs/videos

2) Huge portion of videos is redundancy and repitition

3) Labs cannot be exported to HTML

por asher b

Nov 27, 2018

Course was pretty good, except... The final project was too much of a stretch, had to google too much to figure stuff out that wasn't in the lectures or practice labs.