3.8  2 reviews on Udemy

Data Visualization with Python

Understand, explore, and effectively present data using the powerful data visualization techniques of Python.
Course from Udemy
 13 students enrolled
 en
Understand and use various plot types with Python
Explore and work with different plotting libraries
Understand and create effective visualizations
Improve your Python data wrangling skills
Work with industry-standard tools like Matplotlib, Seaborn, and Bokeh
Understand different data formats and representations

You'll begin with an introduction to data visualization and its importance. Then, you'll learn about statistics by computing mean, median, and variance for some numbers, and observing the difference in their values. You'll also learn about key NumPy and Pandas techniques, such as indexing, slicing, iterating, filtering, and grouping. You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization using this comparison. You'll explore different plots, including custom creations. After you get a hang of the various visualization libraries, you'll learn to work with Matplotlib and Seaborn to simplify the process of creating visualizations. You'll also be introduced to advanced visualization techniques, such as geoplots and interactive plots. You'll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful and insightful visualizations. You'll study how to plot geospatial data on a map using Choropleth plot, and study the basics of Bokeh, extending plots by adding widgets and animating the display of information.

About the Authors

Mario Döbler is a graduate student with a focus in deep learning and AI. He previously worked at the Bosch Center for Artificial Intelligence in Silicon Valley in the field of deep learning, using state-of-the-art algorithms to develop cutting-edge products. Currently, he dedicates himself to apply deep learning to medical data to make health care accessible to everyone.

Tim Großmann is a CS student with an interest in diverse topics ranging from AI to IoT. He previously worked at the Bosch Center for Artificial Intelligence in Silicon Valley in the field of big data engineering. He's highly involved in different open source projects and actively speaks at meetups and conferences about his projects and experiences.

Erik Sevre is a Doctoral Student in Computational Science and Technology at Seoul National University. He is a researcher at Seoul National University.

Data Visualization with Python
$ 94.99
per course
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