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 :)
By 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.
By Joao L•
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•
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•
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•
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•
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•
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•
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•
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•
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.
By 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.
By 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.
By 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.
By 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.)
By 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.
By Arvont H•
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 Hanru L•
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.
By James P•
This is a crucial course however does very little in the way of teaching. The final assessment is also rather buggy. I could not get the dashboard to display in the provided online notebook, so I had to complete the tasks locally. You could argue that this serves better as a teaching aid, however the videos and lessons do not cover enough.
By 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.
By Martha C•
The first part of the course was good as I learned about creating visualizations for EDA. Unfortunately, the section on dashboards was not done well, in my opinion, and the final assignment was quite frustrating. I kept getting errors with my code but did not have enough knowledge from the course to understand how to fix them.
By 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.
By 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>.
By 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.