AI in Climate Science

Harness AI to Decode, Predict, and Protect Our Planet

MODE
Mode(Online) TYPE
Mentor Based LEVEL
Moderate

Skills you will gain:

AI in Climate Science is a future-ready, domain-specific course designed to bridge environmental science with artificial intelligence. This program introduces participants to AI models, tools, and datasets used to monitor climate change, model weather patterns, optimize resource usage, and support sustainable decision-making. Whether you are a researcher, policy analyst, engineer, or student, this course enables you to apply AI in real-world climate solutions and scientific research.

Aim:

To equip learners with interdisciplinary knowledge and applied skills to use Artificial Intelligence in solving pressing challenges in climate modeling, prediction, environmental monitoring, and sustainability.

Program Objectives:

To introduce AI methodologies relevant to climate science
To build interdisciplinary fluency between environmental and computational fields
To foster practical skill development for real-world climate problem-solving
To encourage ethical and data-driven climate decision-making using AI

What you will learn?

Week 1: Foundations of AI and Climate Systems

Module 1: Understanding Climate Science Basics

Chapter 1.1: Key Concepts in Climate Science (GHGs, Carbon Cycle, Feedback Loops)
Chapter 1.2: Climate Data Sources (Remote Sensing, Ground Stations, Models)
Chapter 1.3: Types of Climate Models (GCMs, Earth System Models)

Module 2: Introduction to AI in Scientific Contexts

Chapter 2.1: Overview of Machine Learning and Deep Learning
Chapter 2.2: Why AI for Climate? Use Cases and Opportunities
Chapter 2.3: Ethical AI in Environmental Research

Week 2: Tools and Techniques for AI-Driven Climate Analysis

Module 3: Data Handling and Modeling

Chapter 3.1: Preprocessing Climate Data (Time Series, Spatial Grids, Missing Data)
Chapter 3.2: Predictive Modeling for Climate Trends (Temperature, Precipitation, Sea Level)
Chapter 3.3: Remote Sensing and Image Analysis with AI

Module 4: AI for Climate Impact and Risk Assessment

Chapter 4.1: Extreme Weather Prediction (Floods, Droughts, Heatwaves)
Chapter 4.2: Land Use and Ecosystem Monitoring
Chapter 4.3: Emissions Tracking and Carbon Accounting with AI

Week 3: From Research to Policy and Action

Module 5: Decision Support and Simulation

Chapter 5.1: AI in Climate Policy Modeling and Simulation
Chapter 5.2: Socioeconomic Scenario Modeling and Risk Communication
Chapter 5.3: Urban Climate Adaptation Tools using AI

Module 6: Future of AI in Climate Science

Chapter 6.1: Open Datasets and Collaborative Platforms (Copernicus, CMIP, Google Earth Engine)
Chapter 6.2: Challenges in Scaling AI for Global Climate Modeling
Chapter 6.3: Career Paths, Research Opportunities, and Innovations Ahead

Intended For :

Open to students, researchers, engineers, environmental scientists, and data analysts
Basic knowledge of Python, statistics, or environmental science is helpful
Ideal for professionals in sustainability, urban planning, or ESG