AI for Energy Solutions

This hands-on bootcamp explores the intersection of AI and energy, offering participants foundational knowledge and practical skills to tackle climate challenges. Attendees will delve into real-world applications of AI for energy, from optimizing energy demand and integrating renewable resources to designing smarter grids.

Participants will transform theory into action through hands-on projects using real-world energy data. Learn the fundamentals of AI applications in climate and energy systems, including generative AI, machine learning techniques and energy data analytics - while addressing pressing challenges in sustainability.

The program concludes with a project where participants develop and present AI-powered energy solutions and receive feedback. Whether you're new to AI or experienced, this bootcamp provides a platform for innovation and impactful problem-solving.

No prior experience with AI or energy systems is required. Knowledge of energy systems, basic Python programming, or fundamental statistics is helpful but not necessary. Join us to learn, build, and create solutions for a sustainable future!

Schedule

Week 1: Climate AI Foundations

• Introduction to AI applications in climate and energy
• How to Make an AI/ML Application for Climate Change
• Tutorial: Make your own AI application using StackAI (no coding required)

Week 2: Energy Systems & ML

• Energy technology, analytics and policy
• ML techniques for energy applications
• Hands-on workshop 

Week 3: Project Development

• Team formation and project ideation
• Technical implementation workshop
• Data visualization 

Week 4: Build & Present

• Project development
• Final presentations
• Industry perspectives

F.A.Q.

Who can participate?
MIT students, faculty, staff, and alumni. Community members and students from other universities are also welcome.

What's the time commitment?
8 hours per week (4 hours in class, 4 hours project work)

Do I need to attend all sessions?
Ideally, as content builds progressively

What will I create?
A functional prototype using AI to address energy-related climate challenges

Is this class for credit?
No