Advanced Advanced
Agentic AI
Build AI Agents with Tools, Memory, RAG & Multi-Agent Systems
8 weeks 8 Modules Weekend Batch 90+ enrolled
About This Course
Learn how to design and build intelligent AI agents using LLMs, tools, workflows, and multi-agent systems.
LLM applicationsAgent designRAG systemsLangChain & LangGraphMulti-agent systemsEvaluation & guardrails
What You'll Achieve
Build intelligent AI agents
Implement multi-step reasoning systems
Design production-ready AI workflows
Course Curriculum
Week 1
LLM Foundations + Prompting
- How LLMs work (practical view)
- API usage (OpenAI / Anthropic)
- Zero-shot, few-shot prompting
- Chain-of-thought reasoning
- Structured outputs (JSON)
- Project: Structured-response chatbot
Week 2
From LLM Apps to Agents
- LLM app vs agent vs workflow
- ReAct pattern
- Tool calling & function calling
- Project: Tool-using agent
Week 3
RAG Systems
- Embeddings
- Vector databases (FAISS)
- Chunking strategies
- Semantic search
- Project: Document Q&A agent
Week 4
LangChain & Tools
- Chains vs agents
- Memory types
- Tools integration
- LCEL basics
- Project: Conversational agent
Week 5
LangGraph & Stateful Agents
- Stateless vs stateful agents
- Graph workflows
- Multi-step pipelines
- Error handling & retries
- Project: Workflow agent
Week 6
Multi-Agent Systems
- AutoGen / CrewAI
- Agent roles & communication
- Tradeoffs (cost, latency)
- Project: Multi-agent assistant
Week 7
Evaluation & Guardrails
- Debugging reasoning
- Observability
- Evaluation techniques
- Output validation
- Safety checks
- Project: Add guardrails
Week 8
Deployment & Capstone
- FastAPI backend
- Streamlit / Gradio UI
- API + UI integration
- Cost optimization
Who Is This For?
AI engineers
Developers working with LLMs
Advanced learners
Meet Your Instructor
What Our Students Say
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