Autonomous AI Agents & RAG Architect
Build autonomous multi-agent systems and retrieval-augmented generation (RAG) applications that think, plan, and execute real-world workflows. Master LangChain, LangGraph, LlamaIndex, Vector Databases, and tool calling.
🎯 Core Competencies You Will Master
Target Job Roles & Titles
Course Outline & Milestones
📁 Phase 1: Advanced Prompting & Function Calling
2 CoursesStructured Outputs & Tool Calling with OpenAI & Claude
JSON schema outputs, tool calling, error recovery, and system prompt engineering.
Vector Embeddings, Semantic Search & Vector Databases
Cosine similarity, chunking strategies, indexing in Pinecone/Chroma, and hybrid search.
📁 Phase 2: Production RAG & Multi-Agent Swarms
3 CoursesProduction RAG Systems with LlamaIndex & LangChain
Parent-document retrievers, reranking with Cohere, query decomposition, and handling tabular data.
Multi-Agent Systems with LangGraph & CrewAI
Stateful cyclic agent graphs, human-in-the-loop approvals, role delegation, and self-correcting agents.
Evaluation, Guardrails & LLM Security (NeMo Guardrails)
Preventing prompt injections, measuring hallucination with Ragas, and enforcing strict response schemas.
📁 Phase 3: Production Deployment & Capstone
2 CoursesDeploying Agentic Systems: Webhooks, Streaming & UI (CopilotKit)
SSE token streaming, connecting agents to web UI, WhatsApp/Slack bots, and asynchronous queues.
Final Capstone Project: Autonomous Enterprise Workflow Agent
Build a multi-agent solution that performs a multi-step business workflow autonomously.
Real-World Capstone Project
Autonomous Enterprise Research & Workflow Swarm: Build an AI agent system that autonomously researches company data, generates executive briefs, and executes actions across Slack, Google Docs, and CRM.
Official PBIAcademy Career Diploma
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