Udemy – Interactive Map Visualization with Kepler GL and Streamlit 2024-12

Udemy – Interactive Map Visualization with Kepler GL and Streamlit 2024-12 Downloadly IRSpace

Apr 18, 2025 - 18:10 Updated: Apr 21, 2025 - 19:50

0 0

Udemy – Interactive Map Visualization with Kepler GL and Streamlit 2024-12

Interactive Map Visualization with Kepler GL and Streamlit Course. This course teaches you how to visualize large-scale spatial data using Kepler GL and easily share these interactive map visualizations with Streamlit. Kepler GL is an open source tool developed by Uber for efficient analysis and visualization of complex spatial data in real time. Streamlit is a Python framework that allows you to easily create interactive web applications, especially for data visualization or dashboard building.

This course is designed for people who want to enhance their skills in spatial data visualization. By learning Kepler GL, Streamlit, and Mapbox, you will be able to create engaging and informative interactive maps that help you better understand and interpret your data. Whether you are a data scientist, a developer, or a business analyst, this course will give you the tools you need to transform raw data into actionable insights.

What you will learn in the Interactive Map Visualization with Kepler GL and Streamlit course:

Master the Kepler GL UI: Without writing code, interact directly with the Kepler GL UI and familiarize yourself with its various features to gain a basic understanding of data visualization.
Creating Map Visualizations with Kepler GL: Using Google Colab, write code to create map visualizations with Kepler GL. Learn how to extract visualization settings and use them to customize maps to your needs.
Sharing Map Visualizations with Streamlit: Learn how to share interactive map visualizations with others using Streamlit so that users can easily view maps and perform spatial analysis without any extra effort.
Apply custom map styles with Mapbox: Overcome the limitations of default map styles to display richer and more accurate geographic detail by applying custom map styles with Mapbox.
H3 Data Generation: Learn how to convert point data into hexagon data to prepare for efficient spatial data visualization.

This course is suitable for people who:

Interested in using Kepler GL: Learn how to efficiently process large-scale spatial data and visualize different types of data.
Interested in using Streamlit: Easily deploy web applications and build beautiful map UIs.
Interested in using Mapbox: Apply custom map styles to create custom maps that match project needs.
Want to learn the complete map visualization workflow: master the entire process, including data preparation, visualization, styling, sharing, and deployment.
Interested in spatial analysis: Learn how to create interactive maps and analyze geographic data to gain deeper insights.

Interactive Map Visualization with Kepler GL and Streamlit Course Details

Publisher: Udemy
Instructor: Kyla Kim
Training level: Beginner to advanced
Training duration: 2 hours and 56 minutes
Number of lessons: 22

Course topics

Prerequisites for the Interactive Map Visualization with Kepler GL and Streamlit course

Basic Python skills required: Familiarity with Python, pip for library installation, and basic GitHub usage will make it easier to follow this course.