📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery, from foundations to a certified capstone project.
Sensors
• Sentinel-2, Landsat and commercial constellations: revisit, resolution, cost
• Spectral bands, radiometric calibration and surface reflectance products
• Cloud masking and the gaps it leaves in a monsoon-season time series
Indices
• NDVI construction, saturation at high biomass and soil background effects
• EVI, NDRE, NDWI and choosing an index for the question at hand
• Comparability across sensors and why raw index values are not interchangeable
Time Series
• Compositing, gap filling and Savitzky-Golay or harmonic smoothing
• Phenology metrics: start of season, peak and senescence
• Field boundary delineation and pure-pixel extraction
Analysis
• Crop type classification from phenological profiles
• Within-field variability and management zone delineation
• Anomaly detection against a field or regional baseline
Delivery
• Google Earth Engine and cloud-native geospatial workflows
• Validating against ground truth and yield records
• Delivering outputs to agronomists and insurers in a usable form
Earn government-registered certification in Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery
e-Certificate and e-Marksheet issued on successful completion.
