📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI-enabled Pest Management, from foundations to a certified capstone project.
Entomology
• Pest life cycles, damage thresholds and economic injury levels
• Integrated pest management hierarchy before chemical intervention
• Beneficial insects and the cost of indiscriminate treatment
Detection
• Image-based pest identification and confusable species
• Smart traps, acoustic and pheromone-based monitoring
• Sampling design so a count represents the field, not the trap
Forecasting
• Degree-day and phenology models for pest development
• Weather-driven risk forecasting and its uncertainty
• Regional surveillance and migratory pest early warning
Intervention
• Targeted spraying and spot treatment from detection maps
• Drone and ground-rig application constraints
• Resistance management and rotation of modes of action
Evaluation
• Measuring efficacy against untreated controls
• Residue, environmental and pollinator considerations
• Advisory delivery to farmers in a form that changes practice
Earn government-registered certification in AI-enabled Pest Management
e-Certificate and e-Marksheet issued on successful completion.
