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!!!
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 :)
par Terry G•
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•
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•
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•
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•
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•
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.
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.
par Glen T W P•
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•
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 Lindsey K•
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.
par Ryan H•
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•
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•
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.
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•
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•
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•
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•
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•
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•
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 Tanya S•
I felt that the course was a bit disorganized. The actual code bits that were used in labs were hard to follow and material covered in final assignment required a LOT of independent googling of pandas libraries. Overall, it was a good overview but this course fell short compared to the other courses in this specialization.
par Toby C•
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 Jovita A•
Needs further improvement, examples: (1) discuss important features/syntax ... go over it, may need not be too detailed but simple instructions on what the parameters do, (2) dont repeat throughout the case because it is assumed that the students knew it from the start so that other topics can be discussed or included.
par Claudia R C•
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•
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.