All paths
Software / AI Engineer
Agentic Engineer
Build production agents: RAG, multi-agent, MCP/A2A, security, and MLOps.
Outcomes
- Design multi-agent systems with reliability + cost budgets
- Ship RAG that survives real corpora
- Instrument LLM apps with evals, traces, and rollbacks
The curriculum
- 01Prompt Engineering Mastery
From zero-shot to structured reasoning
Intermediate · 22h · Prompt Engineering - 02Retrieval-Augmented Generation for the Enterprise
Vector databases, hybrid search, reranking, and production RAG
Intermediate · 24h · Retrieval Augmented Generation - 03Multi-Agent Systems in Production
CrewAI, LangGraph, A2A, and enterprise orchestration
Advanced · 26h · Multi-Agent Systems - 04
- 05Vector Databases & Knowledge Graphs
Pinecone, Weaviate, Qdrant, Neo4j
Intermediate · 16h · Vector Databases - 06AI Security & Red Teaming
Prompt injection, jailbreaks, and defense-in-depth
Advanced · 24h · AI Security - 07