MN
4.0Reviewed May 15, 2019
More in class projects similar to final assignment where we can challenge our knowledge as we are all remote and it takes time to communicate through the available coursera forums. Thank you.
Data Visualization with Python
One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story by visualizing data and findings in an approachable and stimulating way. In this course you will learn many ways to effectively visualize both small and large-scale data. You will be able to take data that at first glance has little meaning and present that data in a form that conveys insights. This course will teach you to work with many Data Visualization tools and techniques. You will learn to create various types of basic and advanced graphs and charts like: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps, and many more! You will also create interactive dashboards that allow even those without any Data Science experience to better understand data, and make more effective and informed decisions. You will learn hands-on by completing numerous labs and a final project to practice and apply the many aspects and techniques of Data Visualization using Jupyter Notebooks and a Cloud-based IDE. You will use several data visualization libraries in Python, including Matplotlib, Seaborn, Folium, Plotly & Dash.
Status: Seaborn
Status: Data Analysis
IntermediateCourse19 hours
Featured reviews
JG
5.0Reviewed Apr 16, 2020
This is a very helpful course. It introduces a variety of data visualization tools. The interesting practices in the lab sessions inspired me to explore different solutions for a problem.
HK
5.0Reviewed Apr 30, 2020
Very challenging, yet that's what make it's rewarding. Even though the course only takes 3 weeks, its difficulty is on par with the longer previous course. I enjoyed every problems on it!
AM
5.0Reviewed Aug 13, 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!!!
SB
4.0Reviewed Mar 5, 2020
The course was beautifully structured. I would like to request to add the conditions on which tiles Mapbox Bright works. At times the tiles dont work and we are not sure of the root cause.
SS
4.0Reviewed Sep 24, 2019
Kindly update the final assessment of this course work since it is quite difficult to work with it, as the content related to the assessment cannot be found in the course videos. Thanks !
SS
5.0Reviewed Nov 20, 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 :)
TR
4.0Reviewed Dec 24, 2020
The Course Was Good. It would have been better if some lab sections were covered in labs. As we all know understanding a code then reading might help the students grasp better faster and deeper.
CJ
5.0Reviewed Apr 22, 2023
Learnt a lot from this visualization course. The one I found most interesting was making the dashboard. Although sometime the code and indentation are tedious, but this might be useful in the future.
AA
5.0Reviewed Mar 31, 2020
This course was really interesting and it was great learning experience.A big thanks to a instructor.I got to know new things like folium library (most interesting library of python according to me)
MH
4.0Reviewed Jun 7, 2020
The labs were good but the issue was the extremely rushed up videos. A lot of concepts, especially the artist layer was not covered will in the videos, which made me give this course 4 stars.
CK
4.0Reviewed Mar 12, 2020
Good coverage of different plots. Videos are somewhat repetitive regarding the dataset (most of them could be about 20% shorter due to this). Labs (in Jupyter Notebooks) are great practice.