The course with the IBM Lab is a very good way to learn and practice. The tools we've learned in this module can supply a good material to enrich all data work that need to be presented in a nice way.
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!!!
par prattya d•
Very few guidelines to complete assignments
par Federico D•
Really bad course: too much redundance
par vicky t•
worst course please update the lab pls
par Gaurav R B•
Course is not organized properly
par Slim S•
No documentation, no summary
par Besaleel F d A J•
Very poor videos.
par Akshay J•
very bad course
par Imtiaj A C ,•
I have done other 2 courses in this specialization....but frankly speaking, this course was far better than those....the type of things that we handled in the lab was very interesting and also intriguing....in other courses, the labs were just about the same as the video lectures....no new things except one or two....but here, they were very thorough and we learnt a great deal of things outside of the video lectures.....
About the final assignment, i thought it would be boring and very noobish as i experienced in other two course....but to my surprise it was so great....it just put what i learnt in this course to a test and i had to do everything by myself....it was quite unlike the other ones where i was baby-fed by giving most of the code in a notebook and completing the rest which was so easy that it rarely felt like an assignment let alone the final one.....
And that is why loved this course very much.....about the labs, about what i learnt and about the final assignment....i genuinely think these are gonna help me to accomplish my goal for what i took this course....
And i would like to request the course instructors and maintainers to make other courses in this specialization like this one especially the labs and final assignment.
par Alex J C•
I started, stopped, started, stopped, and started and finished this course. Partly because my job got demanding and I had to pause; partly because some of the concepts in this course weren't always clear the first time I looked at them. It was when I needed to create charts for my job and I was actually working with Python to do those assignments that the concepts in this course finally clicked. Once they did, I was able to push past the finish line.
With this happening, I remembered the important truth of coding skill: it's like a muscle. It only grows when you exercise it. That said, I wish this course offered more exercises (perhaps ungraded FYI exercises, or expanded lab work) in creating various charts.
The maps section rocked! That was, I think, my favorite part of the course, especially when creating the choropleth map for crime in San Francisco. I remember when I did GIS projects in my work 25 years ago, when specialized software ($15,000 - $20,000 per license) was required. Now, in just lines of Python code, you can create an even more precise map. Once I complete my certificate for data science in Python, I will be looking for GIS courses available at Coursera!
par Rohit B•
The course really highlights the power of Python's visualisation. It is really cool to see the charts as well as map functionality that comes free with Python. With some basic programming experience, far more powerful visuals can be created than some very high-end off the shelf programs. I really liked the features such as Word Cloud as well as Choropleth maps.
1 The videos can be a trimmed a bit - Almost every video re-iterated the data cleanup exercise, which got repeatitive after the first 2 videos.
2 More examples of map related lab exercises would be very helpful for those like me who want to delve into this further.
Powered by detail-oriented labs, this course amazes the learners with what can be achieved using Visualization libraries. The course beautifully covers all the plots used by Data Scientists in day-to-day life along with their variations. Going through this course, the learner takes a step towards mastering the art of storytelling, something expected of a good Data Scientist. Nowhere you would feel that prior knowlegde of Visualization is necessary to assimilate the concepts taught.
Lectures are great and so are the videos. The team really must have worked hard to make this course interesting. Loved it!
par Klaus-Dieter W•
This was a pleasant experience! Fiddling with the bar chart to remove labels and ticks on the y axis, as well as the annotation of the percentages on top of the bars turned out to be more work than expected, but is was fun! I had not used Choropleth maps until now, so this was really cool. Folium is awesome! Supposed that you plan an update of the course, you might want to take into consideration that the more recent versions of Folium seemingly had a change in the way Choropleth maps are called.
In summary, thanks a lot for putting a lot of work into this course!
par Рашид У•
Жаль, что я не начал знакомство с Python вообще, и с данной темой в частности, с данного курса. Но лучше поздно чем никогда . Все курсы данной специализации от IBM заслуживают высшей оценки - такой проработанной подачи материала, такого уровня подготовки я не встречал.
Все курсы из данной специализации - это готовые методички, которые можно потом использовать в повседневной работе. Ничего лишнего, всё по делу. Спасибо всем, кто принимал участие в создании курсов данной специализации от IBM - я восхищен!
par Hoang V A•
The course is great , especially with the support of the instructor. However, because we do not have solutions for final assignment, I do not know whether my code/code structure was appropriate, efficient, effective, smart, tidy even the result was correct. Code structures also my concern. I coded 5-6 lines, steps to get the correct result while others may use only 1 line to get one. That's really matter i think so.
par Md. A A J•
This course focused on hands on examples for practicing Matplotlib and python on IBM cognitive lab for data visualization using different tools. Also all videos and lecturers made are great and helpful to show graph, plot , charts and maps. The course contents are clear, precise and lecturer is very knowledgeable.
Joining and getting help from course mates and moderates in discussion forum is Excellent!
Ashfaque A. Joarder
par Rahul B•
Firstly, I want to thank wholeheartedly to the instructor Alex Akson sir, all the lab sessions were great. The content was very elegantly balanced as it was neither hard nor easy, I feel like I learnt a lot of things. The explanation of every plot/topic was very easy . Final assignment took a little bit more time but it was totally worth it. Thank you again for teaching this course. I appreciate all your efforts.
par Deborah B•
This course was fun, interesting and challenging. The final assessment was a true challenge because it require a combination of materials that were covered in the course, but also required a bit of additional information and expertise as well. Finishing those assignments gave me much more confidence in my ability to perform these kinds of assignments in real engagements and assignments.
par Pola A N J•
One of the best courses in the certification. The assignment is tougher than previous courses and that is one of the reasons I loved the course. Also, the labs are very well structured and presented. Gives a nice overview of Pandas in the 1st lab.
Overall, I think this instructor is very good at communicating his ideas and has a good grasp on what his teaching goal and methodology.
par RISHI K•
The course contains a good length of data visualization knowledge with python . This course contains number of hands on labs and notebook session which is an excellent feature to enhance skills i.e. practical work is more as compared to the theory work .
The lectures are beautifully taught and designed by the Alex sir .
Thanks to Coursera and IBM , and a big thanks to Alex sir .
par Maximiliano E•
I thought this course was a bit tough but still very interesting. I gained lots of insights and ideas on Data Visualization methodology and techniques and I am looking forward to applying this knowledge going forward. Recommended course if you want to get good insight and ideas on how to work with data viz and how to prepare the data in order to present it more professional.
par Michio S•
In this IBM program, the discussion forum is well managed.
Whenever I posted my questions, I got help from teaching staff.
Although there is a variability in response time, they responded to all my questions.
Thanks to that, I managed to pass this course with 100% grading.
Especially, I want to give a good credit to Lakshmi Holla for mentoring the students including me.
par Nataly O•
Thanks to instructors. But as always a few improvements are possible. 1) Personally I missed the voice of the speaker from previous 2 courses. 2) I think that extra quizes inside the lessons will be very useful - Don't hesitate to add more tasks for students as intermediate progress assessment.
Anyway, I gained a valuable Data Vis experience from this course. Thanks!
par Mats B F•
There were some issues I spent a lot of time on in the final assessment. The first was loading the file into the notebook. The second was troubleshooting the choropleth map. I had written the key_on code slightly wrong. You can consider explaining in some more detail how to upload files - and also the code you use - !get.
The course was all in all very interesting.
par Senthamizhan V•
I thought the syllabus will cover only matplotlib and seaborn. I didn't expect to learn geospatial data visualization in this course. I learnt a great deal about folium and it's versatility. I feel it's a great addition to the course. Such modules will enable aspiring data scientists to expand their domain knowledge and excel in unorthodox data science areas.
par Toby O•
Not sure if the creator gave enough tips and tricks to help provide solutions for the final assignment. I had to use alternate solutions not provided.
The examples given are good but quite simple in places, and only work in specific circumstances. This may be because there are simply too many solutions to go through in this short course.