"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.
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About this Course
Learner Career Outcomes
26%
30%
Skills you will gain
Learner Career Outcomes
26%
30%
Offered by

IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Syllabus - What you will learn from this course
Introduction to Data Visualization Tools
In this module, you will learn about data visualization and some of the best practices to keep in mind when creating plots and visuals. You will also learn about the history and the architecture of Matplotlib and learn about basic plotting with Matplotlib. In addition, you will learn about the dataset on immigration to Canada, which will be used extensively throughout the course. Finally, you will briefly learn how to read csv files into a pandas dataframe and process and manipulate the data in the dataframe, and how to generate line plots using Matplotlib.
Basic and Specialized Visualization Tools
In this module, you learn about area plots and how to create them with Matplotlib, histograms and how to create them with Matplotlib, bar charts, and how to create them with Matplotlib, pie charts, and how to create them with Matplotlib, box plots and how to create them with Matplotlib, and scatter plots and bubble plots and how to create them with Matplotlib.
Advanced Visualizations and Geospatial Data
In this module, you will learn about advanced visualization tools such as waffle charts and word clouds and how to create them. You will also learn about seaborn, which is another visualization library, and how to use it to generate attractive regression plots. In addition, you will learn about Folium, which is another visualization library, designed especially for visualizing geospatial data. Finally, you will learn how to use Folium to create maps of different regions of the world and how to superimpose markers on top of a map, and how to create choropleth maps.
Reviews
TOP REVIEWS FROM DATA VISUALIZATION WITH PYTHON
Good course, some of the lab assignments did not load properly so it was difficult to practice... (week 2 & 3). Assignment was good after using Jupyter Notebooks as the scripting interface. Thank you!
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 :)
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.
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