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Introduction to Maps in Folium and Python  online course
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Introduction to Maps in Folium and Python online course

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New
Location
South Africa
Bob Shop ID
655007447
Introduction to Maps in Folium and Python Overview
Our course, Introduction to Maps in Folium and Python, provides a thorough introduction to creating interactive maps using Python with the Folium library. Participants will explore geospatial data visualization, mastering essential techniques for effective map creation and analysis.

Structured into ten sections, the course begins with an introductory overview before progressing to creating the first Folium map and adding markers, layers, and base maps. Advanced topics include creating point maps, choropleth maps, and heatmaps, with each section building upon skills acquired earlier.

Hands-on learning is emphasised, with guided tutorials and real-world projects providing ample opportunities for practical application. By the end, participants will have both theoretical understanding and practical proficiency in creating interactive maps from scratch.

Designed for a broad audience, from beginners to intermediate learners, this course equips participants with the skills to tackle mapping projects confidently. Whether a student, data analyst, GIS professional, or Python enthusiast, this course provides a solid foundation in map creation and visualisation techniques, opening doors to new opportunities in geospatial data visualisation.

Introduction to Maps in Folium and Python Learning Outcomes
Develop proficiency in creating interactive maps using the Folium library in Python.
Construct diverse map types, including point maps, choropleth maps, and heatmaps.
Utilise markers and layers to enhance map visualisations.
Analyse geographical data and measure boundaries accurately.
Demonstrate the ability to create custom base maps.
Understand how to create and customise heatmaps for data visualisation.
Learn techniques for sharing and exporting maps for various purposes.
Gain practical experience by working on a project with provided source code.
Apply Python programming skills to manipulate and visualise geographical data.
Reflect on personal learning experiences and actively seek feedback for continuous improvement.

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