Programme Parameters
Advanced Postgrad
4 Weeks (40 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
AI in Agriculture: Basics is an accessible entry point into how machine learning is transforming farming. You learn where AI adds value across the field: monitoring crop and soil health from imagery, detecting disease and pests, predicting yield, and guiding precision-farming decisions on water and inputs. The course introduces the data sources and methods at a foundational level and connects them to real agricultural problems, without assuming technical depth. You finish with a solid grounding in agricultural AI. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This foundational course covers AI in agriculture — how machine learning supports crop monitoring, disease detection, yield prediction and precision farming.
📋 Course Objectives
1. See where AI adds value in farming.
2. Monitor crop and soil health from data.
3. Understand disease and pest detection.
4. Grasp yield prediction basics.
5. Connect AI to precision-farming decisions.
👥 Who Should Enroll?
• Farmers and agronomists new to AI
• Agri-tech newcomers and students
• Rural-development professionals
• Anyone entering agricultural technology
🚀 Key Learning Outcomes
• A foundational grasp of AI in agriculture.
• The ability to follow the field’s methods.
• A springboard to agri-analytics.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Introduction to AI in Agriculture
What is AI in Agriculture? • Role of Technology in Modern Farming • Traditional vs Smart Farming • Applications of AI in Agriculture
Agricultural Data and AI
Types of Agricultural Data: Soil, Weather, and Crop Data • Introduction to Data Collection in Farming • Sensors and Data Sources • Importance of Data in Farming Decisions
AI Applications in Farming
Crop Yield Prediction Basics • Disease Detection in Plants • Soil Health Monitoring • Precision Agriculture Concepts
Smart Farming and Automation
Use of AI in Irrigation and Resource Management • Drones and Remote Monitoring Basics • Automation in Farming Equipment • Improving Efficiency and Sustainability
Future of AI in Agriculture
Emerging Trends in Agri-Tech • AI for Sustainable Agriculture • Career Opportunities in AI and Agriculture • Mini Learning Activity / Concept-Based Practice
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Artificial Intelligence |
| Covered Tool / Platform | Agricultural Data |
| Covered Tool / Platform | Precision Farming |
| Covered Tool / Platform | Crop Monitoring |
| Covered Tool / Platform | Data Analysis |
Frequently Asked Questions
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