Agentic AI refers to AI systems designed to operate autonomously, make decisions, and execute actions in dynamic environments. These systems go beyond passive data analysis and instead act as intelligent agents, adapting to real-world conditions and interacting with other systems or users.
Week-1. Understanding Agentic AI
Definition, Evolution, Importance
Week-2. AI Agents vs Traditional AI
Rule-Based vs Autonomous Systems, Applications
Week-3. LLMs as Autonomous Agents
AutoGPT, BabyAGI, LangChain Agents
Week-4. Building AI Agents with LangChain
Action Planning, Memory, Function Calling
Week-5. ReAct Framework & Thought Chains
Reflection, Self-Improvement, Adaptive Agents
Week-6. Planning & Goal-Oriented Agents
Task Decomposition, Multi-Step Reasoning
Week-7. Multi-Agent Collaboration
Swarm AI, Cooperative & Competitive Agents
Week-8. Decentralized & Distributed AI
Blockchain for AI Agents, Federated Learning
Week-9.Agentic AI in Business Automation
Customer Support Bots, AI Workflows
Week-10. AI Agents in Research & Creativity
Self-Learning Models, AI-Generated Insights
Week-11. Developing Custom AI Agents
Vision-Language Models, CLIP, DINO, Image Captioning
Week-12. Deploying Computer Vision Models
LangChain, OpenAI Function Calling
Week-13. Deploying Agents on Cloud
AWS, GCP, Azure, API-Based Deployment
Week-14. Capstone Project – Part 1
Designing an AI Agent for a Specific Task
Week-15. Capstone Project – Part 2
Implementing, Testing, and Optimizing the AI Agent