📚 Syllabus & Course Curriculum
Agriculture & Food Technology
Module-by-module breakdown of Agriculture Course: Precision Farming, AI, and Smart Agriculture, from foundations to a certified capstone project.
Foundations
• Within-field variability and management zones as the premise of precision agriculture
• GNSS guidance, controlled traffic and the 4R nutrient framework in practice
• Where precision spend pays back and where uniform management is still cheaper
Sensing
• Multispectral and NDVI imagery from satellite and UAV, and what the index does and does not show
• Soil, weather and canopy IoT sensors, and the calibration they need to be trusted
• The resolution, revisit-time and cost trade-off behind every sensing choice
Geospatial
• Spatial data, yield maps and zone maps in QGIS and Google Earth Engine
• Interpolation between sample points and the error it quietly introduces
• Aligning layers from different sensors and dates into one decision surface
AI Applications
• Computer-vision crop and disease detection, and the labelled-data problem behind it
• Yield prediction and variable-rate application driven by the sensed layers
• Why a model trained in one region or season often fails in the next
Capstone
• Building a crop-health or yield-estimation workflow from sensing to recommendation
• The economics and connectivity limits that decide smallholder adoption
• Communicating an uncertain recommendation to a grower without overstating it
Earn government-registered certification in Agriculture Course: Precision Farming, AI, and Smart Agriculture
e-Certificate and e-Marksheet issued on successful completion.
