Unified AI learning platform
Modern AI learning paths for builders, platform engineers, and AI architects. Select AI Engineering for application builders or AI DevOps for production platform specialists.
Roadmap selection
Both paths share the same clean interface, saved progress, filters, search, resource cards, and project milestones.
Master CI/CD, Kubernetes, GitOps, model lifecycle, LLM serving, RAG, MCP, evaluation, observability, and AI security.
A structured path for software engineers moving from fundamentals to production-grade AI applications, RAG, MCP, and agents.
Path guidance
You want to build AI applications, master prompting, APIs, local models, RAG, MCP, and agentic AI systems.
You want to operate production AI platforms with CI/CD, Kubernetes, model serving, evaluation, observability, and security.
Complete AI Engineering first if you are newer to GenAI, then move into AI DevOps to become production-ready.
Unified outcome
Each roadmap ends with capstones that prove real ability: working apps, AI workflows, RAG systems, agents, deployments, dashboards, and runbooks.