Module 15
Open-Source & Local AI
Own your entire stack. Pay nothing per inference.
Lessons
PremiumStart the 7-day trial to open this module.
You can still review the module outcomes, capstone, examples, and resources before upgrading.
15.1
Open-Source AI Landscape
Locked60 min
15.2
Running Models with Ollama
Locked45 min
15.3
Open WebUI & Local Interfaces
Locked50 min
15.4
Cloud GPU Deployment
Locked75 min
15.5
Private AI for Enterprise
Locked60 min
Expert Lens
Founder
Think like a founder: what user pain, distribution channel, pricing, and retention loop does this AI capability unlock?
Systems
Think like a first-principles systems builder: separate demos from durable products, and measure the bottleneck the model actually removes.
Infrastructure
Think like an AI infrastructure leader: account for data, latency, cost, reliability, evaluation, and deployment constraints before scaling.
Objectives
- Run production-grade AI locally and privately
- Master the open-source model ecosystem
- Build fully private AI systems
- Deploy self-hosted infrastructure at any scale
Capstone
Private AI Infrastructure
Build a complete private system: local model serving, RAG knowledge base, web interface, API — on infrastructure you own.
A fully self-hosted AI system with zero external data dependencies.
Real Examples
- Compare hosted APIs with local models for privacy-sensitive workflows.
- Run a local model test and document quality, latency, hardware, and maintenance tradeoffs.
- Decide when open-source control beats frontier-model convenience.
Mastery Checks
- Explain the core concept without buzzwords.
- Build a small working artifact, not just a note or prompt.
- Define an evaluation rubric and test against at least five edge cases.
- Estimate operational cost, failure modes, and human review requirements.