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Learner Reviews & Feedback for Data Visualization with Python by IBM

4.5
stars
9,820 ratings
1,475 reviews

About the Course

"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....

Top reviews

LS
Nov 27, 2018

The course with the IBM Lab is a very good way to learn and practice. The tools we've learned in this module can supply a good material to enrich all data work that need to be presented in a nice way.

AM
Aug 13, 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!!!

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1176 - 1200 of 1,469 Reviews for Data Visualization with Python

By Lyn S

Aug 19, 2019

This really isn't a class, it's a lab, and that would be fine, but we have to watch a few one-two minute videos that should not exist - they are meaningless and waste of time and just end up saying - make sure to do the lap. Delete the short videos and just say - do the lab. The content of the class is very simple, which is fine, and this is one of the classes that doesn't create a very difficult exercise as a test (yea!). Although I will say for me, it took me hours to figure out the box plot, the little no-line nuances, etc. I don't know if was easy and I just could not find the right commands and parameters. All in all not a bad class - because WOWOWOWOIEE - I had no idea making stunning maps was so easy.

By Colette C

Mar 24, 2020

The subject matter of this class was very enjoyable. However, the level of presentation of the material was not in depth enough . As a person who is not from a computer science background, this class was extremely challenging; not because it was too difficult per se, but because I was not given the tools needed to be able to confidently complete the Final Assignment. It took many days of researching, watching several videos outside of the Coursera platform, and a lot of trial and error, to be able to complete the course. In addition, the labs had trouble loading (not Coursera's fault, as it was through another site) quite a lot, which hindered my progression.

By Markus B

Dec 5, 2021

Pro:

T​his course significantly improved my visualization skills in Python.

C​ontra:

T​he videos are too short ( 4 min each)

Course is unbalanced: w​eek 1-4 are very easy and much faster to complete than 4 weeks. Week 5 (graded exercise) took longer than weeks 1-4 combined.

I​nformation for completing week 5 were not given in thecourse material.

C​onclusion:

I​ learned a lot because I did a much reading on information required for the exercises but not provided by the instructors.

=> The course could be much more efficient.

T​his course is not suitable for people not willing to spend much time on literature research.

All others will enjoy the course.

By Drew K

Aug 3, 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.

By 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.

By Maria N W

Sep 17, 2021

The final project/assignment was very problematic with the Theia software. The skelton code provided had some glitches. It was frustrating because I understood the concepts, but I had to debug the provided code then figure out the Theia interface. Hopefully, it will help the next class if they are instructed ahead of time not to use Edge/Explorer, Firefox seems to work best with Theia. Also, save your code in a Wordpad or MS Word doc once you think you have it correct, that way if you get knocked off Theia, you can just paste it back in without restarting from Step 1.

By Joao L

Jan 26, 2021

The final assignment is good as it pushes us to solve the problems with small help. I think that could be said explicitly to use skill labs in the start, can be hard for some people to understand what to use to execute the tasks. Also as we do not have the notebook link some pictures are too small to understand the answers.

Other thing is the repetition on all the videos about the dataset preparation, it can be showed only on first video and use the time to explain better some concepts.

I think the course is good and has a lot room for improvement.

By Glen T W P

Jun 9, 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.

By 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.

By Lindsey K

Dec 22, 2020

The course videos were good, the labs seemed great, and then the final project hit. WHAM! It was way harder than the course materials and had many requirements that were not in the course material. One of the biggest things I learned was how to find my answers elsewhere! For completing the project, Google and the discussion board were more helpful than the course material. You should either add content to the labs and videos or adjust the final project (at least add hints to the assignment)... or you will continue to create frustrated students.

By Steve H

Jan 21, 2021

Week 1 and 2 are OK, but the week 3 videos are completely useless. Basically, each one says "there's a package that does X" but doesn't tell you how to use the package. Then, the quiz questions are about the syntax for using the package. The explanations in the labs are minimal, which would be OK if there had been more info in the videos. Unlike previous courses, there is not a notebook template for the final assignment, so you'll be doing it all from scratch; plan to spend a lot more time than the "average of 1 hour 16 minutes".

By Ryan H

Feb 6, 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.

By 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.

By Lyle W

Mar 28, 2021

I was glad to learn the tools and techniques taught in this class, but the typos and grammatical errors throughout the curriculum caused confusion and distracted from the learning process. Some of the videos are helpful, but others present concepts without context and seem to be aimed at an audience that has already mastered the material. Overall, I think the coursework was appropriately challenging and the final project gives you good hands-on experience to build on in the future.

By Brendan H

Apr 30, 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.

By PEDRO L S S

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.

By 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.

By 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.

By Marnilo C

May 4, 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.

By 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.)

By Hizniye I B

Aug 27, 2021

I have nothing to criticise except that all these tools could also be taught without being dependent on the IBM platform. It's not a bad platform, it's just that you heavily rely on the internet to complete assignments. That's a bit frustrating if you want to complete an assignment while you're on the road or just have a bad connection in general. Except for that: flawless!

By 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.

By Arvont H

Mar 29, 2021

The material we learned will be useful. But, the Week 5 assignment had to much busy work concerning making screenshots. I got some tips on the forum though that allowed me to make the submissions while minimizing the number of screenshots I took. Hint: create the app with mode equal to 'external' instead of 'inline' and print save the resulting browser tab as a PDF.

By Tammara S

Aug 26, 2021

It was a good course. I really enjoyed it when the labs worked. The labs did not work most of the time. It was frustrating and degraded the learning experience. I spent hours combing the forum and the Internet to find solutions. I was desperately afraid that I would not be able to complete the final assignment. I am glad I was able to finish.

By Hanru L

Mar 28, 2021

I thought the final assignment shall be focus on Matplotlib and seaborn, but found it was only about "dash". And it is too complicated and exhausting with many bugs. I don't think python has advantage to build a dashboard since it is much easier to use Tableau and Power BI to build it. The final assignment should be restructured and improved.