Comentários e feedback de alunos de Data Visualization with Python da instituição IBM

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.

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 .

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.

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.

Thanks

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!

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.

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.

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.

While the course's material is very interesting and extremely helpful, there is a vast variety of different ways to visualisation and I'm afraid I had to search google for most of the last assignment's requirements.

I believe three weeks is not enough and there should be more exercises in this course. Other than that it was a thrill :)

The Data Visualization with Python course is really outstanding when compared to the others in this specialization. Alex is doing a great job explaining, the slides and examples are comprehensive, yet easily digestable. The in-depth exercises are the best in the whole specialization, quite challenging and therefore very effective.

This course outlines the importance of Visualization and where and how to use different type of representation such as Bar Graph, Area plot, Pie chart Scatter Plot, Box plot and others. The course also introduces to use of Plots to show Geo spatial data. and also introduces one to the different libraries used for plotting. .

The first properly challenging course I've encountered on Coursera and I loved every bit of it. I have an engineering background and I loved having to look for the answers on the internet and in the documentation. It wasn't simply spoonfed to me. If you pass this course, you will definitely gain proficiency in this subject!

Truly Awesome, I get a in-depth knowledge in this specialization and just precise content as well up to date. Correct combination of theory and explanation in detail then practical lab over recent topic covered then Project in each topic. Also final Capstone project is really rigorous. Thanks to Instructor and Coursera.

I completed this course as part of the IBM Data Science Professional Certificate and it was by far the best (so far, I have one more left). The videos were short and easy to understand, the labs were on point and many additional resources were offered. The instructor did a really good job when putting this together.

A well done course that really gives a decent overview and exposure to the python tools for data visualization. Although the projects take a bit of extra self studying and research to complete, the course provides a majority of other good sources to continue your understanding of the material beyond the lectures.

Very interesting course and a must take for people interested in learning powerful techniques with Python's Panda, Matplotlib and other libraries. At the end of the course, you will feel confident reading, manipulating and displaying data analysis in a wide array of graphs, charts and other stunning visual media.

I was a very difficult course for me but it was very instructive, I understood some of my weakness in Python and OOP so I need to work on that, now I know data visualization is a major topic in DS.

By the way, Google was a very useful tool to review new concepts for me and get ideas how to approach the problems.

Using python to create graphs and charts is very simple and easy, once u remember all the basic and keep trying. It seems to me that it is easier than any other reporting tools I used before. It is great that I know where to find the tool to create these charts and graphs if I need to prepare presentation. :)

Though the course videos were short, giving an introduction to how different charts look and to plot them, the lab sessions were the best and gave a plethora of information on data visualization. Also, I am glad that they included the folium part of the course in the assignments which were very well formed.

Nice lecturer and useful tools. This course was really interesting though pretty hard for me. Sadly at the end of the course I didn't feel that I gained enough skills to do the lab easily but maybe it just me. Anyway I ll definetely return to this course again to get the better understanding of some topics.

I really enjoyed this course! The labs used interesting, real-life data and did a good job explaining the purpose of each line of code in an easy-to-understand way. I appreciated the questions in the lab because they built on and stretched my understanding of Python from past courses. Thank you, Alex.

Really nice course. This course has helped me build up a number of Data Visualization skills, and I am able to draw meaning and conclusions from data easily and much faster. The course labs are excellent and the final assignment was a good way to test the skills that I developed during this course!

I feel this is harder than the other ones in the series, sometimes you need to google a little bit to figure it out.

I spend more time for a week, but I wonder why I have to do it in Python. I learn Python just for faster loops than R. Personally I think R need less coding and produce better graphs.

This is a very enjoyable course, even though I was familiar with most of the tools, I still got to learn a few new tricks. If you are not familiar with programming, you might find the final assignment a bit challenging. Therefore, I strongly recommend that you take the course labs very seriously.

Course is really good to learn all the fundamentals of data visualization along with the advance techniques to master it. Assignments and practices are designed very well by the instructors and you would have to put all your efforts to understand and master all the course. Kudos to the IBM team