Chevron Left
Retour à Data Visualization with Python

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

4.6
étoiles
7,969 évaluations
1,079 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

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.

Filtrer par :

901 - 925 sur 1,065 Avis pour Data Visualization with Python

par Veronica A S

Apr 28, 2019

Good

par Franco M V

May 16, 2020

.

par Louis J

Jan 30, 2020

I have mixed feeling about this course. I think the purpose of this course (visualizing data) and the different ways of doing it is really motivating and awesome, specially when you realize all the things you can do (types of charts , maps etc...). This is actually awesome!

However, on the down sides:

-Each video repeats the steps on how the database used in each course has been "cleaned". I agree with the feedback from other people, reminding us one or two times is fine, but in each video... This is too much!

-I would have liked more practical exercises, specially to plot multiple linear regression models (and polynomial of different degrees, in particular), to display on a chart, and to make predictions. That would be great !

-Labs: they are of unequal difficulty: some are relatively easy to complete, some require more thinking/research and time, while some have no question at all or very little. Maybe it would be useful to re-organize the labs ?...

-Week 3: as everyone mentions, the "artist layer" method is only briefly covered in one of the lab. It would have be really useful to spend more time on it, and on all the things we do with it. Like others, I spent lot of time searching online, and it took me a full afternoon to complete that part of the final assignment !

To summarize: it's a very important and interesting course, but video lessons should be re-recorded with deleting all parts repeating the initial database processing, and adding more topics such as artist layers, etc. Also, maybe split each lab in 2 since there are few labs in this course, but if we follow them correctly, it requires quite few hours to spend on each lab (at least for "beginners" like us starting learning about this topic).

Thank You !

par Farrukh N A

Jul 01, 2020

I hold a degree in computer sciences with majors in Software Engineering so please take this review of the course seriously.

Unfortunately, this is the only course where it seems the teacher never had any outline as to what he needs to teach and how.

1) He has made the video lectures useless as he declared himself that the videos will be short but you have to 'read' lines and lines of lectures to get a grasp of the visualizations he will teach. I think he don't know if it was that easy for a person to get knowledge then he would have just read text books and would have gotten the degree as according to him there wouldn't be any need to educational institutions.

2) Many times, he introduces many 'advanced' functions of Python which was not taught in the previous course which was about Data Analysis by Python. I don't have any problem in learning new things everyday but using multiple advanced functions in a 'beginner' course makes it tough for student to grasp what he was trying to teach.

3) There are far better and easier ways to do many things but it seems he deliberately uses long, tedious and advances methods for plotting various graphs and makes things confusing again and again.

4) Lastly, he himself gives advanced quizzes for the stuff which were not even taught extensively and it makes hard to even pass them.

par Neil C

May 10, 2020

The rating of 3 is because there are some excellent points to this course and some issues. First, no doubting the Instructor knows his stuff and he has a good style, but for EVERY lesson to repeatedly go over the details of the data set used (and you can tell this is one clip pasted in every lesson) is mind numbing. Cover the data set once and then simply say "We will use our Canadian Immigration Data set, refer back to it if you have question" . Then use this time to go into a bit more detail on the graph mechanics. Secondly, there is no lab environment for the final assignment (as was provided in precious courses of the Data Science module). This overly complicates the assingment beyond the material being tested (I was bangin my head as to why I could not get a graph working until I realized it was the lack of an environmnet variable, not my code, that was causing the issue.

par Manuela G

Nov 19, 2018

The course itself was good.

Unfortunatly it was not clear at the beginning, that the "Data Analysis Module" is a pre-requisite. After struggling with the lab of week 3, I found out and took the Data Analysis Module. I tried the lab again - meanwhile the first part has changed - the file was not in the same structure. So, the code I wrote before was worthless. Took a while to figure this out.

Then in CC Lab the "conda install" did not run - neither in the lesson, nor in the lab - therefore I spent many hours struggling to find this out - didn't know, if it was my coding.

It would be good, to improve those "organisational problems". That's why I only gave 3 of 5 stars. It did cost me a lot of time.

The content and lessons and exercises and the lab itself is very good and interesting. Also the amount and speed, very good to handle besides a full-time job (if everything works ;-) ).

par Luisa V

Jun 01, 2020

The course is very informative with step by step explanations. However, there are too little teaching staff to answer all the students questions. As well, throughout the lab quite a few things were unclear (i.e. a certain map is not available for free users, a certain tiles doesn't work with maps, something must be downloaded/imported despite saying it must not). These things could have been mentioned in the lab instead of having to look through many students questions on the same issue up to two years ago. The importing/downloading parts of the code were also very slow on the notebook and it often had to restart often due to this. The final assignment discussion page often crashed and froze too but all the other discussion pages worked very well (no crashing or freezing, fast loading times).

par Terry G

May 04, 2020

The notebooks don't mention that Mapbox Bright isn't available for free anymore. This results in one of the map exercises in Week 3 to not have a map populate. Only after hammering away at the code and reviewing the forums did I learn that this map type isn't free anymore. There's also a section in the final where we are asked to populate labels on a bar chart. This wasn't covered at all in the material. Only after reading the forums and being linked to some obscure blog post was I able to figure this out.

Also critical items not converted the material: why when load a csv file from a URL do you sometimes need to add a .csv extension to the string and other times not (such as in the final map). Why does a .geojson file need a .json file extension when being fetched from a URL?

par Miranda C

Aug 01, 2020

This course was easier to follow than many of the others, partly because of much repetition, which is an essential yet often overlooked element of effective teaching. This is also one of the only courses where the instructor introduced themself in the video, which I really appreciated. If I was grading only based on the lessons and labs, I would give it 5 stars. However, the final project involved a lot of code that wasn't covered in any of the lessons. I know it wasn't just information I missed based on the countless questions in the forums. Thankfully, with the help of the other students, I was able to understand the concepts necessary to complete the project, but that's no excuse for not including the information within the course.

par 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.

par 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.

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 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.