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AI for Environmental Monitoring and Sustainability
Original price was: USD $99.00.USD $49.00Current price is: USD $49.00.
Harnessing the Power of AI for a Greener, Smarter Planet
Course Overview
The AI for Environmental Monitoring and Sustainability is a 3-day international virtual course that explores how artificial intelligence can transform environmental data into actionable insights. Through expert-led lectures, real-world case studies, and interactive coding sessions, participants will learn how to harness the power of AI, remote sensing, deep learning models, and AI-powered dashboards to drive sustainable decision-making. This course bridges the gap between environmental science and cutting-edge AI technology, offering a unique opportunity for professionals and researchers to advance their skills in environmental sustainability.
Course Objective
The course aims to equip participants with the hands-on skills and foundational knowledge necessary to leverage AI for environmental monitoring, sustainability analysis, and smart city solutions.
Learning Outcomes
- Develop AI literacy in environmental monitoring applications.
- Gain hands-on experience with tools like Google Colab and Streamlit.
- Learn how to use satellite and sensor data for sustainable insights.
- Contribute to developing smart, AI-driven environmental solutions.
Course Structure
📅 Module 1: Data-Driven Environmental Monitoring – Foundations
- Focus: Introduction to Remote Environmental Sensing and Smart Monitoring
- Topics Covered:
- Understanding data sources like satellite imagery, air quality sensors, and water data
- Exploring MODIS and Sentinel satellite datasets
- Hands-On: Visualize environmental data in Google Colab (pollution mapping)
- Case Studies: Smart monitoring systems for urban sustainability
📅 Module 2: Deep Learning for Climate and Pollution Pattern Detection
- Focus: AI Techniques for Climate and Pollution Studies
- Topics Covered:
- Image segmentation techniques for land, water, and air monitoring
- Training CNN models to classify land cover or detect pollution hotspots
- Hands-On: Build and evaluate an environmental pattern recognition model
- Customization: Tailor models for specific cities or regions
📅 Module 3: Smart Solutions – AI-Driven Environmental Decision Support
- Focus: AI-Powered Environmental Decision-Making
- Topics Covered:
- Introduction to AI-driven environmental policy tools
- Using multi-source data (pollution, traffic, green cover) for decision-making
- Hands-On: Build a smart city environmental health dashboard using Streamlit
- Model Deployment: Deploy and visualize models using Google Colab/Streamlit
- Use Cases: Applications in urban planning, disaster risk reduction, and smart greening
Who Should Enrol?
- Graduate and postgraduate students in environmental science, data science, AI/ML, and sustainability fields.
- Professionals, researchers, and environmental consultants.
- Urban planners, climate activists, and decision-makers passionate about using technology for sustainability.
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