Technical · 3-5 days
AI Engineering Bootcamp
The most comprehensive hands-on AI engineering program available. Covers the full production AI stack: RAG pipelines, autonomous agents, fine-tuning, evaluation frameworks, deployment patterns, and observability. Taught by engineers who have shipped 20 AI products to production.
What you'll walk away with
Build production-grade RAG systems with evaluation pipelines
Design and deploy autonomous AI agents
Fine-tune models for domain-specific tasks
Implement CI/CD for AI applications
Set up monitoring, observability, and drift detection
Curriculum
LLM fundamentals for engineers
Embedding models and vector databases
RAG architecture: chunking, retrieval, reranking
Agent frameworks: tool use, planning, memory
Fine-tuning: LoRA, QLoRA, dataset curation
Evaluation: automated evals, human-in-the-loop, benchmarks
Deployment: containerization, serving, scaling
Observability and production monitoring
In-person preferred. Up to 30 participants. Laptops required.
Ready to train your team?
Every program is customizable. Tell us about your team and we'll build the right experience.
Request a Quote →FAQ
Frequently asked questions
Who should attend the AI Engineering Bootcamp?
Engineers and developers who need to build production AI — it covers RAG, agents, fine-tuning, deployment, and evaluation over 3–5 days.
Is it production-focused or introductory?
Production-focused. The goal is to take engineers from concept to production-ready, with hands-on labs rather than lectures.
What will engineers be able to build afterward?
RAG pipelines, agentic systems, fine-tuned models, and the evaluation/observability needed to ship and maintain them in production.