- Level: Beginner
- Prerequisites: None
- Assessments: Weekly Micro Assessments; Full Assessment in the Final Week
Week 1: Introduction to AI in Agriculture
Learning Outcome: Understand how AI transforms farming.1.1 Overview of challenges in agriculture.
1.2 Role of AI in precision farming.
1.3 Examples of AI applications in agriculture.
Practical Component
Analyze agricultural data for insights.
Week 2: AI for Crop Management
Learning Outcome: Learn AI techniques for crop monitoring.1.4 Disease detection using AI.
1.5 Monitoring crop health with drones and sensors.
1.6 Predicting yield with AI.
Practical Component
Use AI tools to predict crop health.
Week 3: AI in Livestock Management
Learning Outcome: Explore AI applications in livestock care.1.7 Monitoring livestock health with AI.
1.8 Feed optimization using AI.
1.9 Automating livestock tracking and care.
Practical Component
Develop a simple AI model for livestock monitoring.
Week 4: Smart Irrigation Systems with AI
Learning Outcome: Optimize water usage in farming.1.10 AI for real-time water monitoring.
1.11 Predicting irrigation needs with AI.
1.12 Reducing water wastage using smart systems.
Practical Component
Simulate an AI-powered irrigation system.
Week 5: Sustainable Farming with AI
Learning Outcome: Use AI to enhance sustainability in farming.1.13 Reducing pesticide use with AI recommendations.
1.14 Optimizing energy usage on farms.
1.15 Promoting sustainable farming practices.
Practical Component
Design a sustainability-focused farming system.
Week 6: Final Project
Learning Outcome: Build an AI solution for a farming challenge.1.16 Define a use case (e.g., disease detection).
1.17 Develop and test the solution.
1.18 Present the project to peers.
Practical Component
Deliver a working AI model for agriculture.