Learning Path Curriculum
AI Engineer
From Python fundamentals to RAG, agents, MCP and LLMOps — building AI systems that actually run.
Modules & Skills
Curriculum Modules
Master the technical stack through sequence-oriented modules with real hands-on lab tasks.
Python
The working language of AI engineering.
Topics Covered (2)
LLM Fundamentals
Tokens, context windows and inference.
Topics Covered (2)
Prompt Engineering
Structured outputs and reliable instructions.
Topics Covered (3)
RAG
Retrieval-augmented generation end to end.
Topics Covered (3)
Agent Engineering
Tool calling, agent loops and the guardrails that keep them in check.
Topics Covered (3)
LLMOps
Evaluation, observability and serving in production.
Topics Covered (2)
Model Context Protocol
One protocol for exposing tools, resources and prompts to any model client.
Topics Covered (2)
LLM Evaluation
Measure what your prompts and models actually do, before your users tell you.
Topics Covered (2)