Admission Open-2026
PG Diploma in Geospatial Data Science
Master geospatial technology with hands-on training in GIS, Remote Sensing, Python, LiDAR, Drone Processing & Google Earth Engine — in 6 months.
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The Postgraduate Diploma in Geospatial Data Science (PGDipGDS) is a one-year programme that provides foundational knowledge and practical skills in GIS, remote sensing, geospatial analytics, data science, programming, databases, machine learning, and GeoAI. Through hands-on training, projects, and internship experience, students develop expertise in spatial data analysis, geospatial application development, and data-driven decision-making.
The programme prepares graduates for entry-level geospatial and data analytics careers, as well as further postgraduate study and research.
Highlights
- Fundamentals of GIS and Spatial Analysis
- Remote Sensing Basics and Digital Image Processing
- LIDAR and Drone data processing
- Google earth engine and R Programming
- Web GIS
- Introduction to Data Science
- Python Programming
- Database Management
- Machine Learning, Deep Learning and GeoAI
- Big Data and Geospatial Analytics
Fee
(*Discounted Price Rs. 55,000/-) (Pay In installments)
Fee : Rs. 61,000/- (INR)
Course Curriculum
1. Fundamentals of GIS and Spatial Analysis
-Introduction to GIS
-Coordinate Systems and Projections
-Vector Data Models
-Raster Data Models
-GIS Data Collection Methods
-Spatial Analysis using Vector Data – Overlay Analysis, Hotspot Analysis
-Geostatistical Analysis
-3D Analysis using DEM Data
-Hydrological Analysis
2. Remote Sensing Basics and Digital Image Processing
-Principles of Remote Sensing
-Satellite Platforms and Sensors
-Image Interpretation and Enhancement Techniques
-Digital Image Processing
-Image Classification – Supervised, Unsupervised, Object-Based Accuracy Assessment – User Accuracy, Producer
-Accuracy, Kappa Coefficient, AUC and ROC Curve
-Working with Synthetic Aperture Radar (SAR) – Creation of Interferogram
-Spectral Indices (NDVI, NDBI, NDWI)
3. LIDAR and Drone data processing
-Introduction to LIDAR systems
-LIDAR data processing, classification
-DEM and contour generation from LIDAR data
-Introduction to Drone Technology – Data Processing, Image Mosaic & DEM generation
4. Google earth engine and R Programming
-Introduction to GEE platform
-Image processing & visualization
-Vegetation, water, snow & urban index generation Land Surface Temperature (LST) analysis
-Digital Elevation Model (DEM)& terrain mapping
-Land Use Land Cover (LULC) analysis
-R Fundamentals & Spatial Data Basics
-Vector Data Handling & Visualization
-Raster Data Processing & Analysis
-Advanced Mapping & Project Application
5. Web GIS
-Web Mapping Concepts
-Leaflet
-GeoServer
-OpenLayers
-Web Map Creation
6. Introduction to Data Science
-Data Science Fundamentals
-Data Analytics Process
-Types of Data
-Data Collection Techniques
-Statistical Concepts for Data Analysis
7. Python Programming
-Python Basics, Variables and Data Types
-Conditional Statements and Loops
-Functions and Modules
-File Handling
-Object-Oriented Programming
-NumPy & Pandas
-Data Cleaning and Preprocessing
-Exploratory Data Analysis (EDA)
-Data Visualization using Matplotlib and Seaborn
8. Database Management
-SQL Fundamentals
-PostgreSQL
-Database Design
-Queries and Joins
-Spatial Databases with PostGIS
9. Machine Learning, Deep Learning and GeoAI
-Supervised Learning & Unsupervised Learning
-Regression Techniques
-Classification Algorithms
-Clustering Methods
-Model Evaluation
-Introduction to AI
-Deep Learning Fundamentals
-Convolutional Neural Networks (CNN)
-Object Detection in Satellite Imagery
-Land Use/Land Cover Classification
-GeoAI Applications
10. Big Data and Geospatial Analytics
-Big Data Concepts
-Hadoop and Spark Overview
-Geospatial Big Data