Really bad course: too much redundance

worst course please update the lab pls

One of worst courses I've ever taken.

Course is not organized properly

Final assignment is horrible.

No documentation, no summary

Many labs are broken

Very poor videos.

very bad course

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.

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!

I enrolled in the "Data Visualization with Python" course as part of the "IBM Data Science Professional Certificate" specialization on Coursera. The course is well-structured, making complex concepts easy to grasp for both beginners and those with prior experience in Python. The hands-on approach with practical examples and Jupyter notebooks help me to apply what I am learning in real-time, which greatly enhance my understanding. The use of popular libraries like Matplotlib, Seaborn, and Folium provide a solid foundation for creating insightful and interactive visualizations. One of the best parts of the course is the emphasis on storytelling through data. The instructors do a fantastic job of demonstrating how to transform raw data into compelling visual insights, which is an essential skill in the field of data science. The project at the end of the course is particularly valuable, as it provides me a chance to showcase my skills by creating meaningful visualizations on real-world datasets. Overall, this course is a key stepping stone in my data science journey, and I would highly recommend it to anyone looking to build strong data visualization skills with Python.

Dear Teaching Staff, first of all, I want to apologize with you for some of my firts post on the Course Forum. I wrote them very upset because I did Not get at 1st time the results expected as I use to. Sorry for that.!!! Said that; I want to give you a feedback in order to improve the courses yet to come. It is Ok when teachers show you the A, B, C of any topic and then, expect from you with the final assignment the students´ showing the the X, Y and Z of that topic in question. I do not have any problem with that. I fact I remember at The University the the teachers did exactly that. The diference is, they did explain those expectations at the very begining of the course. This course is far from copy or paste code as someone said on the Forum, but although all of you were very diligents with the doubts, mistakes we made, the problem with the Jupyter lab, etc. I think that you should had explain better the A, B, C of the course making the Quizes more challenging since the begining. That´s all I like to say to you. Again thanks a lot for such an inteletual and learning experience. I´ll keep going trough this path!!!TY

I recently had the pleasure of taking the "Data Visualization with Python" course, and I must say it was an absolute game-changer for me. The course was packed with information, yet still accessible and easy to follow.

From the very beginning, I was blown away by the instructor's expertise and teaching style. He took the time to explain everything in detail and provide real-world examples that helped me fully grasp the concepts. The course covered everything from basic plotting with Matplotlib to advanced visualizations using Seaborn and Plotly.

What really stood out to me was how the course focused on the practical application of data visualization in real-world scenarios. By the end of the course, I had the skills and knowledge to create stunning and informative visualizations that could be used in presentations, reports, and more.

Overall, I cannot recommend this course enough. Whether you're a beginner looking to learn the fundamentals of data visualization or an experienced data scientist looking to take your skills to the next level, this course is an absolute must-try.

The course was great - I learned a lot of the python visualization packages. The end of module Labs could have been broken down into smaller units at logical boundaries. While they were good I found them very long for one sitting. More focus on Artist layer would help - anyway the real world problems would require fair amount of programming.

On the other side, I had encountered some technical questions which I posted in the forum. There was no response from the course staff - I spent nearly 2 days fighting for a column title in the final assignment and was hoping someone will try to help. As much as possible, I try to find the solution myself and also help others in similar situation, I did need some help on two occasions in the final assignment which I could not get.

All in all a great experience!

The Data Visualization with Python course offered by IBM on Coursera provided an exemplary learning journey. The course content was meticulously organized, and the instructors displayed profound expertise while maintaining an engaging and stimulating atmosphere. The hands-on assignments and real-world projects proved to be invaluable, offering practical skills that are readily applicable. The comprehensive coverage of Python libraries such as Matplotlib, Seaborn, and Plotly served as a pivotal toolset for mastering data visualization techniques. Undoubtedly, this course surpassed my expectations, empowering me with the confidence to craft influential visualizations to eloquently convey insights. I wholeheartedly endorse this course to anyone seeking data visualization excellence.

The course starts with the introduction and history of Visualization, Matplotlib and its architecture. Followed by introduction and hands-on experience of Histogram, barcharts, boxplots, scatter plot and bubble charts. This course also introduced the advanced visualization tools like Folium for visualizing Geospatial Data, along with Plotly, Plotly.graph_objects, and Plotly express command, also understood how a dashboard can be used to answer critical business questions. At the end the course ends with Peer Graded Assignment to get hands-on practice of everything learnt and made a dashboard.

Thank you Coursera and IBM for this amazing learning experience.

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.

Improvements:

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.

Even this is not an exhaustive course about data visualization, after taking this course I've learned a lot about libraries and concepts that were new to me (such as Waffle Charts, Folium and Dash). The integration with IBM cloud services is awesome but some more work needs to be taken on Theia web based app (it takes some time to load and the right side including the editor is not always loading so you have to try several times until you have a functional app). I'm giving this course a 5 star rating, even with the Theia tiny problems and I'm confident that IBM and Coursera teams will continue to improve the materials and tools.

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!

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!

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!

Challenging but rewarding! The final project is by far the most difficult part and does include things that are not covered in the course, but Dr. Pooja gives enough hints throughout the exercise. It's essentially fill in the blank, and context clues will lead you to the answers if you put forth the effort. I had actually learned a lot about Dash by the end of it, and I now have a solid template for other interactive Dashboards in the future!

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.

Thanks anyway.

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