DAY 1 | 8th January, 2026: Session 1: Introduction and Core Concepts

This session introduces the fundamentals of Spatial Thinking, Geographic Information Systems (GIS), Remote Sensing, and geospatial data. Participants will learn about different types of geospatial data and commonly used formats. Through practical examples the session demonstrates the value of using spatial data analysis and visualisation.

DAY 1 | 8th January, 2026: Session 2: Creating, Editing, and Converting Vector Datasets

This hands-on session introduces participants to Google Earth. They will learn to navigate the interface, use essential tools, and create and edit spatial features such as points, lines, and polygons. The session also introduces Mapshaper for converting between file formats and cleaningvector data. By the end, participants will be able to explore, create, edit and convert vector datasets effectively.

DAY 2 | 8th January, 2026: Session 1: Visualising Spatial Data as Interactive Web Maps

Participants will learn core principles of map design, including symbology and data classification methods such as graduated, categorical, point and bubble maps. The session covers the use of colour schemes and essential map elements. Participants will then create interactive web-based visualizations using online mapping and visualisation tools such as Datawrapper and Flourish. The session also introduces techniques for joining tabular data with vector datasets for spatial visualisation.

DAY 2 | 9th January, 2026: Session 2: Converting Tabular Data into Spatial Data 

In this session, participants will learn to geocode tabular data using Google Sheets and visualise them as point and bubble maps. In this session participants will create story maps and overlay analysis using ArcGIS online and Felt Maps

LEARNING OBJECTIVE

Understand basic concepts of spatial thinking and GIS including spatial vs. attribute data, geospatial data types, and common spatial data formats.· Understand and apply basic map design principles such as elements of map, map symbology, classification methods, and color schemes to create clear and meaningful visual representations of spatial data.· Join, integrate, and clean datasets, including geocoding tabular data, performing attribute joins, and preparing data for map visualization· Create static and interactive maps—applying appropriate symbology, classification, and design principles as well to effectively communicate spatial insights to diverse audiences.

WHO CAN BENEFIT FROM THIS

Students, researchers, and professionals who want to convert their datasets into maps or create spatial data visualizations.

PRE-REQUISITE

Basic working knowledge of Excel, Google Sheets, or similar software for handling tabular datasets.

E-certificate (provided) for 70% attendance across both sessions. 

Also, Participants are required to keep their cameras on for at least 80% in both sessions each day.