Programme Parameters
Graduate / Intermediate
3 Days (4.5 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
This 3‑day course on Techniques and Tools for Smart Farming introduces participants to the latest innovations shaping agriculture. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This 3‑day course on Techniques and Tools for Smart Farming introduces participants to the latest innovations shaping agriculture.
📋 Course Objectives
1. Apply AI Enablement methods to authentic research and industry problems.
2. Build a defensible project you can showcase to supervisors, reviewers, or employers.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in AI Enablement
• R&D engineers and working professionals applying AI Enablement in industry
• Academics and educators building research or teaching capacity in AI Enablement
🚀 Key Learning Outcomes
• Tangible, reproducible AI Enablement work to show supervisors or employers.
• 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
Day 1 – Technological Innovations in Smart Farming
Explore the fundamentals of Smart Farming and digital agriculture • Deploy drones for crop monitoring and precision application • Implement IoT sensors for field monitoring and automation • Apply AI/ML for crop prediction and disease detection
Day 2 – Sustainable Practices and Future Farming Models
Assess the role of sustainability in modern agriculture • Design urban and vertical farming systems (hydroponics, aquaponics, smart greenhouses) • Adopt carbon‑neutral and regenerative agricultural approaches • Implement smart waste management and circular‑economy solutions
Day 3 – Data‑Driven Agriculture and Resource Optimization
Identify big‑data sources and their strategic importance in agriculture • Perform data analytics for crop‑yield optimization and resource planning • Utilize Farm Management Information Systems and smart decision platforms • Build AI predictive models for climate‑resilient farming
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Drones |
| Covered Tool / Platform | Internet of Things (IoT) |
| Covered Tool / Platform | Artificial Intelligence |
| Covered Tool / Platform | Machine Learning |
| Covered Tool / Platform | Robotics |
| Covered Tool / Platform | Big Data |
| Covered Tool / Platform | Farm Management Information Systems |
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