🌟 Why Agentic AI Now?

The future of Generative AI lies not just in powerful LLMs — but in intelligent agents that can reason, use tools, remember context, and act autonomously.

Agentic AI is powering the next generation of copilots, autonomous research agents, customer assistants, and more. This bootcamp is your hands-on path to mastering this game-changing technology.

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🧭 What You'll Learn 

✅ Week 1: Foundations of Agentic AI

• What is Agentic AI? How it differs from GenAI and LLM apps
• Evolution: LLMs → Tools → Agents → Multi-Agent Systems
• Key building blocks: Reasoning, Memory, Tools, Planning
• Use Cases: Healthcare, Research, Automation, Customer Support

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✅ Week 2: LLMs + Tools + Frameworks

• Anatomy of an AI Agent (Perception, Planning, Memory, Actuation)
• Toolformer and OpenAI Function Calling
• LangChain fundamentals for tool use
• LangGraph for multi-agent orchestration
• LangChain Expression Language (LCEL) basics

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✅ Week 3: Memory and Retrieval-Augmented Context

• Adding memory to agents: short-term vs long-term
• Implementing vector-based memory with LlamaIndex and FAISS
• Using ChromaDB, Weaviate, and Redis for memory storage
• Context compression, summarization, and document retrieval

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✅ Week 4: Tool Usage & Web Integration

• Building and integrating tools (e.g., search, calculator, API calls)
• Using LangChain tools, OpenAI functions, and custom Python tools
• Connecting agents to external systems: Databases, APIs, Files, Browsers
• Using AutoGPT-style memory/tool loops

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✅ Week 5: Planning and Advanced Reasoning

• Zero-shot and multi-step reasoning patterns (ReAct, Tree of Thought)
• Task decomposition with planning agents
• Hierarchical agent design: Managers, Workers, Sub-Agents
• Implementing Reflexion: agents that critique and self-improve

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✅ Week 6: Multi-Agent Collaboration

• Building cooperative and competitive agents
• Agent messaging, feedback loops, and workflows with LangGraph
• Shared memory, message-passing, and interrupt handling
• Real-world demo: Autonomous research assistant with agents

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✅ Week 7: Deployment and Integration

• Building production-ready agent systems with FastAPI, Docker, LangServe
• Cloud integration: AWS, Azure, GCP
• Scaling with Kubernetes (overview)
• Monitoring, logging, and observability for agent-based systems

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✅ Week 8: Capstone + Career Mastery

• Final Capstone: Build and present your own multi-agent system
• GitHub portfolio, documentation, and peer review
• Resume-building and interview coaching for Agentic AI roles
• Job market preparation: Freelancing, startup, and enterprise roles

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🧰 Tools & Frameworks You’ll Master

Category	Tools/Frameworks
LLMs	OpenAI, Hugging Face Transformers
Memory	LlamaIndex, ChromaDB, Weaviate, Redis
Tool Use	LangChain Tools, OpenAI Function Calling
Agents	AutoGPT, ReAct, Reflexion, BabyAGI, LangGraph
Planning	LangChain Planners, ReAct, Tree of Thought
Orchestration	LangGraph, LCEL
Deployment	FastAPI, Docker, LangServe, REST APIs
Vector DBs	FAISS, ChromaDB, Weaviate, Redis
Bonus	GitHub Copilot, VSCode, Postman, Streamlit (for UI demos)

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💎 What Makes This Bootcamp Different?

• 🎯 100% Live Instructor-Led (No pre-recorded fluff)
• 🧠 End-to-End Implementation: Build complete agent systems from scratch
• 🚀 Enterprise-Grade: Learn tools used by companies building AI copilots
• 🤖 Production-Focused: Learn how to deploy and scale multi-agent systems
• 💼 Career Outcomes: Resume templates & mock interviews

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🎓 Who Should Join?

• ML Engineers and Data Scientists transitioning to GenAI
• Developers looking to build AI applications and agentic systems
• DevOps/MLOps professionals moving toward AI infrastructure
• Product Managers/Founders building AI-first startups

 

🎁 Bonuses

• ✅ 20+ plug-and-play agent templates
• ✅ Access to premium Agentic AI Discord/Slack community
• ✅ Resume & LinkedIn Optimization Templates
• ✅ Sample project portfolio with agent systems
• ✅ Lifetime access to recordings and updates