Master Large Language Models

Learn from industry practitioners who've built real AI systems. Our September 2025 program combines hands-on experience with deep technical understanding.

Explore Program Details

Built by Practitioners, Not Academics

Most AI courses teach theory. We teach what actually works in production environments. Our curriculum comes from teams who've deployed LLMs at scale, faced real debugging sessions at 2 AM, and learned what enterprise clients actually need.

You'll work with the same tools and constraints we use every day — limited compute budgets, messy data, and stakeholders who need results they can understand.

Production deployment strategies with real infrastructure constraints
Debugging techniques for when models behave unexpectedly
Cost optimization approaches that actually matter in business
Integration patterns that survive contact with existing systems

Technical diagram showing LLM architecture and data flow patterns

Your Learning Journey

Every person brings different experience to this field. We've designed flexible paths that meet you where you are — whether you're coming from software engineering, data science, or traditional machine learning.

Foundation week: Architecture deep-dive and environment setup

Hands-on: Fine-tuning your first model with real data

Production deployment: Infrastructure and monitoring

Advanced techniques: RAG, tool use, and optimization

Code editor showing LLM training configuration and parameter optimization

Garrett Thorne

Senior ML Engineer

The hardest part isn't training the model — it's everything that comes after. Getting reliable results in production taught me more than any research paper ever could.

Knox Brennan

AI Systems Architect

I've seen too many brilliant models fail because nobody thought about how they'd integrate with existing systems. We focus on building things that actually work.

Learn from People Who've Been There

Our instructors aren't just researchers — they're the people who get called when production systems break. They've navigated the gap between what's possible in theory and what's practical with real budgets, deadlines, and stakeholder expectations.

Each week includes office hours where you can discuss your specific challenges, whether that's debugging a training run or figuring out how to explain your model's decisions to a non-technical team.

Meet the full teaching team →

What's Actually Happening in AI Right Now

Dashboard showing model performance metrics and deployment statistics

The Reality of Model Deployment

Most companies are struggling with the basics — reliable inference, consistent responses, and costs that don't spiral out of control. We cover the unglamorous but essential aspects that determine success.

Updated March 2025

Network diagram showing distributed AI system architecture and data pipelines

Beyond the Hype Cycle

While everyone talks about AGI, actual businesses need solutions for document processing, customer support, and data analysis. Learn to build systems that solve real problems profitably.

Updated February 2025

September 2025 Cohort

Applications open May 2025. We're looking for people with technical backgrounds who want to build practical AI solutions — not just understand the theory.

Duration

12 weeks intensive

Format

Evening sessions + weekend labs

Class Size

Limited to 24 participants

Prerequisites

Programming experience required

View Full Curriculum Schedule a Call