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!!!
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 :)
par Toan L T•
Oct 21, 2018
This course is really good. The instructor did a great job introducing common graphs, charts and map techniques. What they look like. How, where and when to use them.
The lab is time-intensive which give chance to thoroughly practice the technique. One more plus point is the lab uses real data and guide you through the step of retrieving, cleaning, analyzing, visualizing and mapping.
par Mirena T T•
Apr 24, 2020
Great course, extremely thorough! Interesting assignments. It is more than obvious that the author has put time and effort into it. Thanks for that :)
par Olin H K•
Apr 19, 2020
Bottom Line Up Front: You are going to have to teach yourself using Google for the Final Project
This course was unique in the Data Science Professional Certificate Progression in that the content of the videos was not very helpful, making your rely on the labs to teach yourself.
The labs were not great in walking you through all the parameters that were available for each type of plot, and while you can copy and paste solutions and tinker to learn things, the course didn't leave me with a good understanding of how or why things work and thus, unable to apply solutions creatively and appropriately without much effort.
By far my least favorite course of the 7 IBM courses I have completed so far.
par Paul B•
Feb 29, 2020
Like other reviews I was really looking forward to this course in the IBM syllabus but was very disappointed. Videos were very high level and repetitive - and there were a lot of them. The detail in the exercises was better but there were significant challenges in getting them to work. And then the final assignment was a bit of a joke. The visualisations you were expected to produce had not been taught in the course and as you'll see from the forums requires a lot of work arounds. I would suggest this course needs a bottom up re-write. Do less but cover it better!
par Aylin B E•
Mar 16, 2020
The video content was not extensive and it was recommended to study on labs for more detiled information, however, like many people who took the lesson, I had difficulty opening and using the lab labs.cognitiveclass.ai. When I wrote about the problem to the support team, they said they already escalate this issue to their partner to take care of it and fix it as soon as possible. I completed assigments and labs on a different compiler.
I'm disappointed about this course after all the good courses I took on Coursera. I hope they will fix the issue quickly.
par Chu Y C•
Jun 11, 2020
quiz had strangely tricky questions, which were not thoroughly covered in the videos. And as others have said, the final assignment challenged us to do a bunch of things that are out of the scope of this topic. It would have been much better if we had more guidance on setting up the groundwork to perform the visualizations. For instance, I had to figure out how to import folium into my notebooks, which took up some time - some direction might have helped with that. Overall, I did learn some from the material, but the experience could be way better.
par Johannes W•
Aug 30, 2019
The videos were unfortunately pretty useless. At least half of the time the respective dataframe was processed (but always in exactly the same manner... zero information about the actual new concept). In addition the videos were too short and the really important new concepts were only introduced by quickly showing the code snippets. There was often no explanation of key concepts. Unfortunately, overall one of the weaker courses on Coursera. The Data Analysis Python course is much better and explains similar concepts.
par Hui W F•
Dec 29, 2019
I enjoy the IBM certificate programme in data science so far. But this course is a great disappointment because of the followings. 1) The clips are not organised which waste us time to read the same contents (i.e. how to clean up the data) for more than five times. 2) The instruction is not clear without going into the details of the coding. 3) Some of the images of the assignment are incorrect, misleading many of us to spend extra time to fix something that should not be fixed. Hope Coursera can redo this course.
par Sarah W•
Aug 26, 2019
The class is beneficial as it allows you to understand how to create visualizations of your projects. However, the final project for this class was very hard to understand. A lot of the parts that were expected to be completed were no where in the videos or labs. In the forum, you could tell because a lot of people were confused about the same stuff. Others and I ended up using other sources as a way to get the results Coursera was wanting, rather than what Coursera taught us.
par Jennifer B•
Mar 12, 2020
This course does very little teaching. The labs demonstrate how to do things, but there is little explanation of why, and no theory about visualisation at all. Instead, students are simply taught to follow recipes. Also, for the past week, the IBM servers have been extremely unreliable. I haven't taken off any stars as it's not the fault of the teaching staff, but it's a bad look when an IBM run course can't actually get the IBM computing services to work properly.
par Gilles W•
Apr 09, 2019
Videos are so so, the same introduction for all videos with 2 minutes of data formatting, which is exactly the same in all videos, leaving only few minutes at the end of the vid's for the content of the lesson. The examples in Jupyter were interesting but not very well structured. At the end, I better used Google and Pandas documentation to solve problems and learn about the topic. Not a bad lesson, but there are just more effective way to learn in my opinion.
par MAJ A S•
Jun 22, 2020
There's a lot of good material, and ultimately enough to integrate into successive work in data science.
On the frustrating side, most of the explanations focused on "what" rather than "why", and there's so many "why" left unanswered when choosing to address a problem with these tools.
Additionally, most of the questions were either insultingly easy or incredibly difficult. Plenty of googling in addition to reviewing presented material.
par nicole b•
Jun 14, 2020
The videos are very repetitive and do not offer much in terms of preparation of the lab. They are very short and say the same thing about the structure of the data. The labs are very good but I had to spend time looking up solutions online that were outside of the taught material. The course really needs to be updated.
par Roberto S•
Jun 25, 2020
The provided material is really bad. I don't see the point of doing this course, when you have to search on internet how to do everything.
I learnt doing some things during the assessment, but not using almost any of the instructions given during the videos. They were completely useless.
par Tom S•
Apr 13, 2020
I felt that the curriculum was not structured in a manner conducive to learn the material. Too much of the training and lab work was to execute already prepared commands without an explanation as to why we were doing using these commands. In addition, the training material could have used more detailed explanations and then lab work allowing the student to apply this knowledge. Instead, you watch a lot of abbreviated videos and then do a single lab exercise that has the student try out certain aspects of what was covered.
For the final exercise, there was so much that wasn't covered in the course material. This took many extra hours searching for how to do things. While this type of searching might have been helpful in preparing for use of Python/Data Science outside of the course, none of the course material to date trained us on how to interpret the reference material. The final lab should be challenging, but not to the extent where the material presented doesn't provide the method for solving these problems. The curriculum designer should take this into account when building these classes.
Lastly, the tooling used for the course did not work for over a month. This added hours to my training. It also meant that I was never able to complete some of the lab exercises, or use the completed material as a reference for the final exam work. The Coursera help desk was not at all helpful in informing students of the issue and when it would be resolved, and only gave advice to try to recreate the same exercises (without the supporting code) in other environments. This added many hours to the time that I needed to complete the exercise.
par Ian A T•
May 07, 2020
While the data visualization tools outlined here are valuable, the final assignment for this course does a very poor job of assessing the things that were actually taught.
Early on, you are assured that the course will emphasize the scripting layer of matplotlib, rather than the more complex artist layer. In the final assignment, however, you are instructed to use the artist layer, and configure many parameters that were never covered in any of the labs or videos.
Likewise, utilizing geojson files for choropleth maps was covered in the most cursory manner - you are never requried to open a geojson file, or understand how it is configured. You just load it in and carry on with the assignment. However, without understanding the setup of a geojson file, no student is going to understand how to properly configure the key_on parameter when making their own choropleth map for the final assignment.
The ability to actually create a graph from a set of data is perhaps the smallest part of the final assessment. Everything else is fussing with irritating details, often details that we were never taught about in class.
par Yiannis E•
Jun 12, 2020
This was not a course. This was a "go get them tiger": the labs are there, go do them and come back for the assignment. And then, in the assignment there were features that we had to include in a chart that were not even hinted - let alone explained - anywhere in the course. If we the idea is that we must search for everything on the web, then the course should at least include references to websites where we can find relevant information. Back in my student days we called that "suggested reading". Some of the Multiple Choice questions were really annoying: do we really have to remember the first name of the creator of Matlab to become data scientists? Great Material, but a very frustrating overall experience since there was no teaching.
par David A•
Oct 22, 2019
While I enjoyed the content of this course, I feel that the instruction was disorganized. This course is part of a beginner sequence in data science, but the teacher assumes certain advanced skills are already known and does not teach them. For example, chart annotation is only briefly covered in the second lab, but the final assignment requires a depth of knowledge not taught in this course. If that's the case then chart annotation should be taught as its own section. A lot of the quizzes are written to trick you with ambiguous phrases, rarely do they actually test what is learned in the labs. I think the teaching in the other IBM data science courses is far better than this one, hopefully they improve this one.
par Shannon R J•
Nov 13, 2019
This is by far the least helpful course in the IBM Data Science Professional Certificate series. The videos contain mostly repeated info, so you really only learn much of anything from the labs. But even the labs are very basic compared to what you are expected to do for the final project. If I am paying for a course to teach me something, I shouldn't be teaching myself with help from Google. I can do that on my own, for free. If the "help" offered by the teaching assistant in the forum is code that doesn't look even vaguely familiar right after going through the course, doing all the labs, and getting a 100% on every quiz, then there is a big problem. I would absolutely not recommend this course
par Victor G R F d S•
Dec 26, 2019
The video lessons just tell you that do some things are possible, but just in theory they would explain how to do it on labs, but the labs aren't so clear. There are days that I try to download the files for final assignment and the link doesn't work and the mentores don't answer. I didn't want to give one star to the course, because all of the other courses from IBM Data Science certification are so good, but unfortunately this course definitively doesn't scores higher than that, because I had to study on matplotlib and other libraries documentations in order to do the exercises.
par oguz o•
Aug 11, 2019
by far the worst course of the whole certification program. Carelessly prepared content. Full of typo and mistakes. Quiz results are not even consistent. Different answers for the same question is considered wrong. If a question has two possible answers as multiple-choice, the answer should be one of those, right? Many of the videos are repeating each other. Very little information. Waste of time and money. If there was another way to get this certificate without taking this visualization course, I would pick that way.
par Ali M R H•
Oct 24, 2018
The course was not well organized. The instructor focused on providing very advanced content rather than simplifying the conpects in order to make it easy for the student to digest, and follow. In many times i had to search online to understand the content. Even in the final assignemt, it was asked to use many functions that was not itroduced before, and the attached files that were needed to answer the questions came with errors, and i had to search in stockoverflow to solve the attachments problems.
par Hesam R•
Dec 22, 2019
In my opinion, it's a terrible course. The labs seem to belong to an advanced course, whereas the videos are elementary and for absolute beginners. The labs take several hours and and even days to complete and understand, whereas it's claimed only an hour is required. None of the links/path at the final assignment worked! zero to none customer support, which is an absolute shame. The final assignments are way beyond the scope of a beginner course. Waste of money!!!
par Karan S•
Jul 30, 2019
Arguably the worst course in IBM certification. There were problems everywhere. The code boxes weren't loading in quizzes. The overall peer guided assignment was a nightmare since they were demanding the part which was not even taught. To sum it all up, peers checked my assignment incorrectly. The assignment grade calumniation took so long than usual. Keep in mind I've done previous courses in this IBM professional certification.
par Dmitriy M•
Jul 14, 2020
Worse course ever!
Don't waste your time - this course is just repetition of the same video "data cleaning" which is half of the whole course.
BTW they use outdated (unsupported) version of Python - Python 2. Not a big deal, but shows that the course itself is outdated. Other libraries used in the course are outdated as well - if you use latest versions you'll find some warnings or error because library has been moved forward.