LinkedIn – Geospatial Raster Data Analytics in Python 2025-1

Geospatial Raster Data Analytics in Python. This course provides a comprehensive overview of raster data analytics in Python and is designed for data scientists and geospatial professionals. Participants will learn the fundamentals of working with raster data and Python tools such as GeoPandas and Shapely. Instructor Milan Yanusov covers everything from creating synthetic data to collecting, visualizing, and processing real data. Throughout the course, practical skills such as data exploration, resampling, reflection, combining single- and multi-band data, and performing advanced analytics are taught. Topics include an introduction to geospatial data, the basics of working with raster data, visualization, data slicing, regional statistics, and applying simple and complex functions to data. The course includes coding challenges to reinforce learning and, ultimately, provides guidance for continuing on the path to raster data analysis.

What you will learn

• Creating Synthetic Raster Data: Participants will learn how to generate sample raster data for learning purposes.
• Collecting and Visualizing Real-World Raster Data: This section teaches participants how to collect existing raster data and display it visually.
• Raster Data Modification: How to modify and enhance existing real-world raster data, including editing and processing it, is covered.
• Statistical and Visual Analysis of Raster Data: Participants will acquire the skills necessary to examine and analyze raster data both statistically and visually.
• Resampling and Reprojecting Raster Data: Skills required to change the resolution or coordinate system of raster data are taught.
• Combining Single-Band to Multiband Raster Data: How to merge different layers of single-band raster data to create multiband data is covered.
• Performing advanced analysis on multiband raster data: Participants will be introduced to more complex analysis techniques on raster data that include multiple bands of information.

This course is suitable for people who:

• Data Scientists: This course is ideal for data scientists who want to expand their skills in geospatial data analysis.
• Geospatial professionals: People who work in the field of geographic information systems (GIS) and remote sensing and are looking to strengthen their skills in Python.
• People looking to understand and work with raster data: Anyone interested in working with geographic image data and performing advanced analysis on it using Python.

Course details

• Publisher: LinkedIn
• Instructor: Milan Janosov, Ph.D.
• Training level: Advanced
• Training duration: 2 hours and 38 minutes

Course topics

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