| Attribute | Detail |
|---|---|
| Format | Recorded Lectures (Self-Paced) |
| Level | Beginner |
| Duration | 1 Month (2-3 Hours per Week) |
| Certification | e-Certification + e-Marksheet |
| Fee | Free |
| Tools | Python Google Colab Arduino Raspberry Pi OpenCV ThingSpeak Environmental Sensors |
About the AI and Robotics for Environmental Sustainability Course
Explore how Artificial Intelligence and Robotics can support climate monitoring, wildlife conservation, renewable-energy management, and smart waste-management systems.
This self-paced course introduces environmental data, sensors, Computer Vision, intelligent monitoring, and sustainable technology applications for students, teachers, and STEM educators.
Program Highlights
• Introduction to AI and Robotics for environmental sustainability
• Four structured modules delivered through recorded lectures
• Flexible learning through the NanoSchool e-LMS platform
• Coverage of climate, conservation, energy, and waste management
• Exposure to Python, Arduino, Raspberry Pi, and AI tools
• Real-world examples and sustainability-focused applications
• e-Certification and e-Marksheet after successful completion
• Mentor support for course and technical queries
Course Curriculum
Module 1: AI for Environmental Monitoring
- Introduction to AI-based environmental monitoring
- Climate, weather, air-quality, and water-quality data
- Environmental data visualization using charts and dashboards
- Forecasting and early-warning system concepts
Module 2: Robotics for Conservation
- Robotics applications in wildlife and habitat conservation
- Sensors and camera systems for remote monitoring
- AI-based wildlife identification and image recognition
- Responsible use of drones and automated systems
Module 3: Renewable Energy Optimization
- AI applications in solar and wind-energy systems
- Energy-generation and demand forecasting
- Battery, storage, and smart-grid concepts
- Energy-efficiency solutions for schools and buildings
Module 4: Smart Waste Management
- Introduction to intelligent waste-management systems
- AI-based waste identification and classification
- Robotics and automation for waste segregation
- Smart bins, recycling, and circular-economy principles
Tools, Techniques, or Platforms Covered
Python Google Colab Arduino Raspberry Pi OpenCV ThingSpeak Environmental Sensors
Real-World Applications
- Analyze basic climate, weather, and pollution datasets
- Understand wildlife-tracking and habitat-monitoring technologies
- Study AI applications in solar and wind-energy management
- Explore smart bins and automated waste-segregation systems
- Develop sustainability ideas for school and STEM projects
Who Should Attend & Prerequisites
- Students from Classes 9-12 interested in AI, Robotics, or environmental science
- Science, Computer Science, Mathematics, and Environmental Studies teachers
- STEM educators, Robotics-club coordinators, and Eco-club coordinators
- School coordinators, curriculum developers, and self-learners
Certification
