Ever feel like everyone's talking about AI, but nobody's teaching you how to actually use it?
Have no fear, because MIT xPRO's “Driving Innovation with Generative AI” is here. We got the opportunity to take part in the first cohort, and we learned A TON. Yes, even those of us who eat, sleep, and breathe AI every day can learn something from this course.
What you'll ACTUALLY learn: This isn't your typical “watch videos, take quizzes” online course. Over six weeks, you'll dive into the full spectrum of generative AI technologies guided by professors from MIT’s world-renowned faculty.
Here’s what’s included:
- The 6-week course teaches you to design AI solutions without coding.
- The course covers everything from LLMs to image generation to drug discovery and everything in between.
- You learn from 12 MIT professors through practical assignments.
- And you'll build real AI solutions that solve problems in your specific industry.
Here’s the week by week breakdown:
- AI Landscape Fundamentals: Neural networks, data requirements, and how generative AI differs from traditional machine learning.
- Visual Generation Models: The mechanics behind image generation, understanding latent variables, and analyzing inputs/outputs of systems like DALL-E and Midjourney.
- Large Language Models: The evolution of language models, their current limitations, and future applications across various fields.
- Specialized Applications: How genAI transforms coding, chemistry, and 3D design through molecular property prediction and structural design.
- Human-AI Collaboration: Techniques for creative expression and designing AI that complements human capabilities.
- Pro-Human AI Development: Addressing biases, implementing feedback-driven reinforcement learning, and aligning AI with user goals.
Our main takeaway? That building AI isn't just for engineers anymore. The course focuses on conceptual design rather than technical implementation, making it accessible for product managers, UX designers, and professionals from any industry looking to leverage AI.
Here’s our experience taking the course: Each week follows a consistent pattern that forces you to apply concepts to real-world problems:
- Identify a challenge in your industry.
- Design an AI solution (conceptually).
- Reflect on broader implications.
- Get feedback through peer review.
That last part—peer review—might be the secret sauce. You're not just learning from MIT professors but from dozens of professionals across different industries who provide tangible feedback on your work and show you how they're applying the same principles in their fields.
One week you might be reviewing an AI system designed for healthcare diagnostics, the next, a tool for architectural design. This cross-pollination of ideas creates a uniquely valuable learning environment.
We approached this course as someone who writes about AI daily but had limited experience designing AI systems. What surprised us most wasn't the technical content (though there were plenty of “aha!” moments, like an algorithm that literally prints robots) but how the course changed our thinking about responsible AI development.
Throughout the six weeks, we created six projects–here’s our two faves:
- “The Decider”—a GPT that helps tackle decision fatigue by ranking tasks, asking targeted questions to resolve priority conflicts, and applying importance weights. Think of it as a smarter to-do list that actually helps you figure out what to do first.
- An educational gaming companion AI that plays the role of a peer student at a magical school—think “Hermione” to the player's “Harry Potter”—who guides learning while keeping things fun.
The most valuable lessons came from being forced to think through every stakeholder who might interact with our AI—not just the primary user, but everyone from parents to teachers to society at large.
We had to consider questions like:
- Would this tool enhance learning or replace human teachers?
- Could kids form unhealthy attachments to an AI companion?
- How might this create or address equity gaps?
As the course progressed, our educational AI evolved from being an “always available perfect friend” to a more realistic presence that respects healthy boundaries—a transformation that would NEVER have happened without the course's emphasis on ethical design.
If you want to read more about our experience and takeaways, check out this MIT blog where Grant was interviewed about his experience!
Why take this course? This course doesn't just teach you to use AI—it teaches you to design AI. As we see things here at The Neuron, the future isn't one giant AGI making all our decisions for us, but a billion smaller AIs helping assist humans reach our full potential.
In a world where AI is reshaping every industry, learning to think like an AI designer might be the most valuable skill you can develop right now.
If you're considering taking the course yourself, here are the specifics:
- Next cohort starts: April 14, 2025.
- Time commitment: 4-7 hours per week.
- Duration: 6 weeks.
- Price: $2,979.
- Format: Online with continuing education units (3 CEUs).
Check it out here for more details; and if you sign up between now and April 11, you get 15% off! Don't say we never did anything for you...
