AI learning paths
Sequences organized around professional outcomes. Follow a complete path or use each course independently.
Programming with AI agents
Learn Codex and Claude Code, then connect projects to local models.
- Developers, makers, and product teams
- Ship tested software changes through a controlled agent workflow.
AI systems engineering
Build RAG, agents, and model services with security, observability, and evaluation.
- Backend developers, ML engineers, and DevOps practitioners
- Operate a measurable, secure AI application that recovers from failures.
Open models and post-training
Move from running local models to serving, evaluating, and adapting them with your data.
- Technical learners with Python and GPU access
- Publish an evaluated adapted model behind a controlled API.
Applied AI for work and content
Automate real work and create media without losing privacy, licensing, or human review.
- Small businesses, educators, freelancers, and creators
- Build a useful workflow with evidence, permissions, and human approval.
Durations are estimates. Move forward when you can explain the result and repeat the practice without copying every step.