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

4.5
étoiles
8,230 évaluations
1,128 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

Aug 14, 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

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 :)

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951 - 975 sur 1,113 Avis pour Data Visualization with Python

par Drew K

Aug 03, 2019

Disappointed with this module. The Labs would not execute and had issues. Throughout the course there is a request to advise of errors (including spelling errors) or problems in the modules or content. I don't understand how entire Labs cannot execute, due to the starting cells not running. I logged a few issues (that other participants encountered too, backing up my issues) and had responses after a few days saying there were "fixes", but you had to run x/y code ..... This still proved difficult. I think the fundamentals definitely need addressing (modules/labs that run). The videos (teaching) are very good however. Thank you.

par Annamaria M

May 26, 2020

The course material is good, but the notions in the exercises are sometimes just shown and not explained in enough depth. The exercises during the course are way easier than the final exam, that I found too difficult for the content of the course. Also, the difficulty of this exam is not comparable to the other exams in the same certificate (I am following the professional certificate in data science), that have been much easier and much better aligned with the content of the course material. I would cut on the material of the course and keep it simpler, plus simplifying the exam to actually reflect what has been taught.

par Baher

Aug 23, 2020

Hi,

In the final assignment, I had to explore the internet to get some codes to display the bar graph or the map. These codes were not covered in the class. The course needs to get improved by giving the keys of how to do things . For instance, the method .patches was never covered in the course. I do not know how to use it. It may be a part of panda library, but the method was critical to do the assignment. There are many other examples. I spent almost a night to finish the assignment because I took a long time to self learn these tasks. It is good at one side, but the course should help me.

Thanks

par Glen T W P

Jun 09, 2020

Explanations were clear and gave a good basic start to doing data visualization with Python, but the final assignment required searching on the Internet in order to accomplish the tasks; i.e. it is not possible to complete the final assignment using only information found in the course. You can take it 2 ways: that this is actually realistic for the real world (since there will always be problems you can't solve with what you already know), or that they didn't give a solid enough foundation so people actually know what to do with what they learnt.

par Chaohua L

Jul 17, 2019

I would recommend that there should be more contents in the lecture videos and the lab sessions. It would be good to have more practical tutoring on the code. for example, in the lab it only mentioned how to do annotation on an ungrouped bar chart, but the assignment requires to annotate on a group bar chart, which is hard when i just followed the lab steps, and i ended up doing hours of searching, alghough it's a helpful process. So it will be good if the course can add more details on different methods of using the libraries that were covered.

par Ryan H

Feb 06, 2020

This course felt less well organized and structured as compared to the other courses in the IBM Data Science track. The videos were sparse on detail, and while the labs did have a lot of good information, they were missing crucial material that was necessary for the final assignment. The final assignment also didn't include a Jupyter notebook template / starter code, which combined with the missing information from the labs made the assignment much more frustrating than those for the other courses in this series.

par Vyacheslav I

Nov 25, 2019

Almost good. But not much explanation given, quick brief on basic functionality. Most of the videos are 3-4 minutes long, where 30 seconds is logo + ending and additionally one minute in almost every video - explanation of the data. In almost every video. So, total explanation of particular functionality is close to 1:30 to 2 minutes. Plus, lecturer is soooooo bored with what he is explaining, that you want to go to sleep in 5 minutes. Final assignment was quite good. That is why it's 3 stars instead of 2.

par Brendan H

May 01, 2020

The labs were very informative, but the videos didn't add much of anything to my knowledge. The final assignment was incredibly difficult, and the course was all but useless for completing it. Almost everything for the final assignment had to be looked up elsewhere. When a final assignment tests over material never covered in the course, what purpose does it serve? There are many other reviews that have the same complaint. Something needs to be done to rectify this problem.

par Pedro

May 26, 2020

That`s a good course. I realised the Instructor efforts and his great skill and capabillity wich Python visualization. The final assignment pointed to activities that couldn't be deployed in another (or resident) Jupyter notebook, just only in an IBM cloud notebook.I expensed too much time trying to discover it. Some instructions should be better explained during the course. This is an important subject to be dealing in just tree weeks. Thank you.

par Awab A

Aug 30, 2019

The part of using the artist layer is a little ambiguous. Now after I finished the course I don't feel that I know clearly the difference between using the artist layer or using the scripting layer. In both cases we use plot function of a dataframe.

I think dedicating a week or more to discuss the actual functions and the way of using the matplotlib library may be better than previewing more visualization options like waffle chart and word cloud.

par William Z

Mar 20, 2019

Sorry to say but this course is actually worse than the others in have learned before.

I understand it may be hard to teach only the different tools for visualization such as folium, bar/pie chart. However, the speaker in this course speaks the same "WORDS", just like replacing the variable names when coding under instructions.

I did learn something in this course but just don't like the way we been given.

par Marnilo C

May 04, 2019

This course had several areas where it could be improved: (1) The Final Project was made much more difficult by requiring the students to use skills which were not taught in the course. This seems to defeat the purpose of testing, which is to test what was learned. (2) The course should have contained content which explains when it is more appropriate to use the specific types of visualizations.

par Steven T

Oct 27, 2018

Overall a good course, especially the final assignment is well done. However, there is too much focus on the class labs and practically no effort put into the videos. Within the class labs there are only comments as reference to how and why something is done which often lacks proper explanation (e.g. what the called methods in a chart mean, how loops are used to fit data etc.)

par Carmen R

Jul 26, 2020

I felt this class was not bad.... I do think that the quizzes are a bit too easy with the assignment being a serious step up. The assignment also required you to Google some how-to's, use some patches and reference prior courses which I feel asked a lot of learners. The info is good, the skill learned is pretty cool. Not the best class, with definite room for improvement.

par Bryan B

Dec 19, 2019

Although the idea of this course is good, it didn't have the same flow as the other IBM courses in the IBM Data Science Professional Certificate. There were no quizes during the videos, and the final project had concepts and code that weren't in any labs or videos. Even the hints from the professors in the discussion were misleading.

par Toby C

Feb 06, 2020

This course was good but for too many of the final assignment questions I really had a to look up how to do it on the web.

A better explanation of the key_on parameter in choropleths would help - even though the entry in the json file is features - the key_on value is feature.properties.<key> not features.properties.<key>.

par Claudia R C

May 10, 2019

The course is nice, but there are several issues that could be easily solved:

Some of the notebooks on JupyterLab were not working (e.g. "exploratory...").

On the final assignment page there were some bugs regarding the upload (i.e. question 3)

The videos in week 5 were too condensed and resulted hard to follow.

par 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.

par 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.

par 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.

par Daniel A

Sep 10, 2020

Still good overall but not as well designed as previous courses in the IBM data science certificate track. The final assignment is MUCH more difficult than any content in the labs and harder than previous final assignments, which isn't necessarily bad but it's inconsistent and unexpected.

par 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.

par 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.

par 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.

par 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!