This hands-on bootcamp explores the intersection of AI and energy, offering participants foundational knowledge and practical skills to tackle climate challenges. No technical skills or coding experience are required. You'll use intuitive low-code/no-code tools to create AI applications, with optional opportunities to explore coding for those interested in further technical learning. Participants 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 share AI-powered energy solutions. Whether you're new to AI or experienced, this bootcamp provides a platform for innovation and impactful problem-solving.

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

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This class is led and instructed by Jennifer Turliuk, former Practice Leader of Climate and Energy AI at the Martin Trust Center for MIT Entrepreneurship.

Class session topics:
-Climate change
-AI for climate solutions
-Energy
-AI for energy solutions
-Hands-on tutorials featuring no-code, low-code, and coding options for developing AI and ML solutions for climate and energy.

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Details

1. What is the name of the activity?
AI for Energy Solutions

2. Activity description:
This activity will introduce participants to the intersection of artificial intelligence (AI) and climate solutions, focusing on energy systems. Attendees will explore real-world applications of AI, such as optimizing energy efficiency, renewable energy integration, and creating actionable insights using data-driven methods.  No prior coding or AI experience is required, as the program incorporates user-friendly, low-code and no-code tools. Optional coding opportunities are also available for those interested. Participants will engage in hands-on workshops, including building models and tools to understand how AI can contribute to solving climate challenges in the energy sector.

3. Who is organizing the activity?
Led and taught by Jennifer Turliuk, former Practice Leader of Climate and Energy AI at the Martin Trust Center for MIT Entrepreneurship, and a MIT Sloan Fellow Master’s graduate, focusing on AI and Climate Tech. Supported by MITEI and Sloan Sustainability Initiative.
Contact: jturliuk@mit.edu https://linkedin.com/in/jenniferturliuk

Bio: Jennifer Turliuk is a technologist, keynote speaker, published author, climate tech investor and entrepreneur. She was Practice Leader, Climate and Energy AI at the Martin Trust Center for MIT Entrepreneurship; she built, researched and instructed AI for climate and energy solutions at MIT and beyond. She has delivered talks on AI for climate and energy solutions at Davos, COP29, the DOE ARPA-E Summit, TEDx, New York and SF Climate Weeks, MIT, Yale, Harvard, Climate Change AI and Terra.do. Recently, she was Partner of Climate Capital Syndicate (one of the most active funders of climate tech startups), and Partner and Co-Instructor of Climate Angels (an educational program about climate tech angel investing). Previously, she co-founded an education company, bootstrapped to self-sufficiency, raised VC funding, and exited through acquisition. Her work has been featured in The New York Times, Huffington Post, NBC, FOX, CBS, Fast Company, and Wired, and she has written for Forbes, VentureBeat, and Business Insider. She has been a board member, consultant, and mentor for entrepreneurs. She graduated from the mid-career MIT Sloan Fellows MBA program, Queen’s University, and Singularity University’s Global Solutions Program (at NASA Ames) - and was awarded an honorary degree from Humber College.

Description

AI for Energy Solutions

Introductory program on AI solutions for energy! Explore how artificial intelligence can drive solutions to climate challenges in the energy sector.

Description:

This hands-on bootcamp explores the intersection of AI and energy, offering participants foundational knowledge and practical skills to tackle climate challenges. No technical skills or coding experience are required. You'll use intuitive low-code/no-code tools to create AI applications, with optional opportunities to explore coding for those interested in further technical learning. 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 share AI-powered energy solutions and receive feedback from peers. Whether you're new to AI or experienced, this bootcamp provides a platform for innovation and impactful problem-solving.

No prior experience with coding, AI or energy systems is required. Knowledge of energy systems, basic Python programming, and/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 & AI for Energy
- Energy technology, analytics and policy
- AI techniques for energy applications
- Hands-on workshop 

Week 3: Project Development
- Team formation and project ideation
- Technical implementation workshop
- Data visualization 

Week 4: Build
- Project development
- Final project
- Industry perspectives

F.A.Q.

- Who can participate?
Anyone! Folks from early career to late career have participated across academia, industry, government, and more. 

- Do I need to know how to code?

Nope! The program is designed to be accessible to all. You'll work with low-code/no-code tools to build impactful AI applications for energy solutions. Optional coding opportunities are also available for those who are interested. 

- What's the time commitment?
Plan for approximately 8 hours per week:
4 hours of in-class time (2 hours of class plus making time).
4 hours of project work outside of class. 

- Do I need to attend all sessions?
Ideally, as content builds progressively. We are also recording the sessions, so if you miss one, you can catch up between. 

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

- Is this class for credit?
No

Schedule