Course Overview:
This course equips learners with the knowledge and tools to understand and apply artificial intelligence (AI) in the context of energy transition and sustainability. With Vision 2030 driving massive investments in clean energy, smart cities (like NEOM), and carbon-neutral initiatives, the integration of AI in energy systems is more critical than ever.

Students will explore real-world AI applications in renewable energy optimization, carbon tracking, smart grid operations, and sustainable urban development — all within the Saudi and GCC context. Through a combination of case studies, hands-on tools, and industry insights, participants will be prepared to contribute to a greener, AI-powered future.

Learning Outcomes:
By the end of this course, learners will be able to:

Explain how AI technologies support clean energy and sustainability goals.

Analyze AI’s role in solar, wind, and hydrogen energy optimization.

Evaluate smart grid systems and demand response powered by machine learning.

Apply AI techniques in carbon emission tracking and forecasting.

Identify opportunities for AI in Vision 2030 mega-projects like NEOM and Red Sea.

Design basic AI-driven sustainability solutions using real-world tools and datasets.

Understand ethical, environmental, and regulatory challenges in applying AI to sustainability in Saudi Arabia.

13-Module Outline:
Module 1: Introduction to Energy Transition & Vision 2030
Why sustainability is at the heart of Saudi Arabia’s transformation.

The role of AI in enabling energy diversification.

Module 2: Fundamentals of AI for Non-Tech Professionals
Key concepts: machine learning, deep learning, data analytics.

AI tools relevant to sustainability and energy systems.

Module 3: Overview of Clean Energy Technologies
Solar, wind, hydrogen, and geothermal: KSA’s priorities.

Where AI fits in the value chain of clean energy.

Module 4: AI for Solar Energy Forecasting & Optimization
Predicting solar output, weather, and panel efficiency using ML.

Case study: AI in NEOM’s solar initiatives.

Module 5: Wind Energy & AI-based Turbine Optimization
Wind pattern analysis and predictive maintenance.

Interactive tools for wind data analytics.

Module 6: Smart Grids and AI-powered Energy Management
What are smart grids and digital twins?

Load balancing, outage prediction, and efficiency via AI.

Module 7: AI in Carbon Tracking and Emissions Forecasting
Tools and platforms for carbon footprint analysis.

AI in compliance reporting and ESG frameworks.

Module 8: Digital Twins in Urban Sustainability Projects
How NEOM uses AI-driven simulations.

Building sustainable infrastructure with real-time modeling.

Module 9: AI for Energy Storage and Battery Management
Predictive analytics in lithium-ion and alternative storage.

Applications in grid storage and EV charging.

Module 10: Case Studies from Saudi Arabia & GCC
Red Sea Project, NEOM, Aramco, and KAUST AI initiatives.

Interviews or curated video content from Saudi professionals.

Module 11: Building Your First AI-Driven Sustainability Solution
No-code and low-code tools (e.g., Power BI, Teachable Machine, Google Colab).

Hands-on mini project: emissions forecast dashboard.

Module 12: Ethics, Data Privacy & Green AI
Responsible AI in sustainability: avoiding greenwashing.

Saudi regulatory considerations and environmental ethics.