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 Azhan A•
The reason I'm giving it 4 stars is because the although the content was good, the labs were challenging but there are something which I found missing, for example, there should have been more information on libraries related to cholorpleth map. !wget was not working on my PC's jupyter notebook and looking it up on the internet was even harder because this extension or whatever it is big on its own. I don't know what to write to get the correct google search.
par Monali C•
It was a great learning experience with coursera.After Data Science course ,learning Data Visualization with Python was my next target to complete.I learned many basic and advance things about how to work with data using visualization.With every questionior and assignments it was interesting and challenging to learn from this course.Thank you coursera for this course it was really helpful to learn and know about data visualization more accurately.
par Will S•
I believe a more comprehensive review of the material discussed in the Final Assignment would be beneficial. Perhaps including a directory of other topics outside of course and under which courses to find the material. I have all the information from prior IBM courses to complete assignment, but I did spend a bit of time just looking for my old labs trying to find material that covered the Final Assignment questions.
par Katherine F•
There is a lot of repetition regarding the data within the videos, but thankfully they are quite short (especially when played on double speed). Unfortunately there are some issues completing later modules and the assignment on any browser other than Chrome because of compatibility issues with Leaflet/Folium. Other than that, the course is pretty good. iPython notebooks do make learning a lot nicer than it can be.
par Francisco M•
The course is good but sometimes the exercise texts are not very clear and some of the lessons are very straightforward, leaving many doubts. The course should have a larger series of exercises and an automatic correction system that facilitates the review of the exercises. In addition, it would be interesting to have a module on how to use IBMDB2 without the online platform, but through Jupyter on the computer.
par Eugene T B•
The lectures make everything seem simple, but you really have to dive into the labs and make a point of studying on your own. You can easily get through most of this course just by running the Jupyter Notebooks that are provided then copy/pasting and editing for the final. If you really want to get something out of the course, you really have to motivate yourself to learn the material.
par Oriana R•
Honestly, out of all the courses I've taken so far, this one was the best, in terms of presentation. The instructor repeated a lot of the formatting for each code block and by the end, one could easily remember what code to use for the specific visualizations.
The only reason I did not give 5 stars was because I thought the final assignment deviated a bit, but otherwise, a good course.
par Ankur G•
A good course to learn know-how of Data Visualization using Python language so as to facilitate analysis and visualization of data to make effective decisions. I thank the professors to make this course interesting and worth it. Only thing is, videos can be made in a better way so as to facilitate people with non programming background. Maybe some basics of programming would help.
par Benjamin S•
This course has one advantage over the others in the series: practice time. The labs are more thorough and provide more practice problems. However, the overall quality in production of this course is lower than the others. Additionally, there were some points awarded on the final project for things simply not covered in the lectures or labs, which was frustrating to say the least.
par Cameron L•
The last third of the course was not much more than two Jupyter notebooks that I Shift-Entered through, with a few problems presented to work out on my own. These were usually able to be completed by copy and paste, I learned more in one question in the final quiz, which required me to to the Maplotlib documentation site and apply that to the question. I expected more.
par Chung S M•
It is a very useful course for data visualization. It guides you through all the steps to create graphs. It is a difficult course compared to the previous Python courses because generation of graphs requires a substantial amount of input and can be hard to memorize. The instruction was useful in helping students practice, but some more instructions are recommended.
par Taha m•
Course is very well taught, it would be better if they taught us Artist Layer a little bit in detail, also the Final assignment is little bit difficult from what we have learned from the course, it would be better if labs content taught us in a video because in video we see in realtime. Overall its a great course for learning Data Visualization in Python.
par Rodrigo J S•
Overall, the course is good, but some additional explanation on some parameters for the graphs (specially ar the Artist level) would be good. Apart from the platform issues (xlrd was almost never loaded and need to be loaded and imported, and some downtime issues), I would suggest to move the final assignment to a 4th week, as they do on other courses.
par Jianxu S•
It is an excellent class in terms of practice and playing with tools. The weak part is that the course does not cover much the logic behind different choices of graphics. Often, we just create a plot and tweak it to make it more appealing. Overall, I would still recommend this course to people who are new to the visualization aspect of data science.
par Brian B•
The videos get repetitive as they each walk through and explain the exact same dataset as if you've never seen it before, but after the first few times, you figure out you can skip past that part. The skills learned are quite cool and this class shows how to easily make several different kinds of charts and dynamic maps from a dataframe.
par David B•
Covers a large range of subjects and gives you are good overview of lots of visualization techniques.
However, in covering a lot of ground in a short time, I found I needed to do quite a lot of extra reading to ensure I understood what was being taught.
For me, probably the toughest of the 7 Data Science modules I have completed to-date.
par Benoit P D•
I learnt a lot about pandas, matplotlib, seaborne, data visualization (different types of plots), folium and wordcount. Overall the course is very good. The jupyter notebook assignments are very nice. Folium is fairly bleeding edge so a lot has changed between the last version of the library and the one currently used by the assignment.
par Alistair J W•
This was the most challenging course thus far in the IBM Data Science concentration. The quizzes are as simple as the earlier courses but the final programming assignment is much less cookie cutter and required substantial reading of the matplotlib API. As a result I think it took longer and I learned more than in previous courses.
par Edward L•
More time should have been spent describing and showing examples in bar charts and choropleth. Only simple bar charts were used nothing related to multiple bars for grouped items were demonstrated. Some for the Choropleth. Simple example in lesson that wasn't anything like the requirements for the final assignment was discussed.
par Hao H•
This course is much more difficult than the previous courses of IBM Data Science Professional Certificate series. Lack of tips and procedures makes it a challenge both to follow the video and to finish the final assignment. However this is similar to the real environment where you have to solve problems yourself.
par Dibyaranjan S•
This course is great for those who want to learn the art of visualization in python using different packages available for python.The only thing I want to point out is that it is using outdated packages of some libraries.Once the assignments are updated with the latest libraries ,Then it will be a 5 start course
par Stephen E•
Good work through the information. Assignment challenged your knowledge. Would have given 5 stars but I continually had issues with the Jupyter Notebook crashing. I had to restart the server or just leave it for a couple hours. The content was great, but Jupyter notebook frustrated me incredibly!
par Manal C•
Excellent Instructor. One of the best in the series. Very clear explanations, and resourceful.
One suggestion - edit Question 4 of the final assignment so that a who student copy/pastes the instructor's image would not get more points than if they put in the code they did to try to get it.
par Sumit P M•
This data visualization course teaches very basic graphs. Two good thing I came to know through this course are Folium and two layers in Matplotlib which was interesting. I was Expecting some more interactive graphs to learns by taking this course but the course disappointed me there.
par Wu J•
The workload for lab is quite big compared to other learning component in this course.
The most difficult and time-consuming part in lab and assignment is not about the visualization, is about data processing. Suggest having a more structured data pre-processing summary at the front.