1
Concepts of Agentic AI
Explain the concepts of agentic AI, autonomous agents, and multi-agent systems in the context of business and technology.
Learning Outcomes
2
Learning Agentic AI Use Cases Across Industries
Recognize Indian and global use cases of agentic AI in sectors such as finance, healthcare, manufacturing, and education.
3
Evaluating AI Solutions
Design strategies for implementing AI agents while considering scalability, governance, and interoperability.
4
Practical AI Implementation
Analyze real-world applications of AI agents in workflow automation, enterprise integration, and decision-making.
5
Ethics, Law & Privacy
Evaluate risks, ethical concerns, and failure modes in autonomous systems.
6
Future Trends
Anticipate future trends in autonomous AI, including self-improving agents, human-AI teaming, and regulation.
Program structure
Lesson Plan
5 modules • 51hours total length
Module 1: Foundations of Agentic AI
Module 1: Foundations of Agentic AI
What you'll learn
- Define AI agents and differentiate them from traditional AI models
- Classify types of agents: reactive, proactive, and generative
- Trace the evolution from early autonomous systems to LLM-driven agents
- Analyze core agent architectures and multi-agent foundations
- Explain advanced capabilities like memory and context handling
- Review Indian pilot use cases such as NIC chatbots
Skills you'll gain
AI AgentsAgent ArchitecturesMulti-Agent SystemsGenerative AgentsContext HandlingMemory ManagementCase Study Analysis
Module 2: Multi-Agent Collaboration
Module 2: Multi-Agent Collaboration
What you'll learn
- Explain communication protocols for agent coordination
- Analyze cooperative, competitive, and hybrid collaboration models
- Apply MAS in domains like supply chain, finance, and healthcare
- Design education and simulation environments using multi-agent systems
- Resolve conflicts and build consensus in distributed systems
- Evaluate decentralized governance models such as DAOs in Indian contexts
Skills you'll gain
Agent CommunicationCollaboration ModelsSupply Chain MASFinancial Trading AgentsHealthcare MASDAO GovernanceConflict Resolution
Module 3: Workflow Automation with Agents
Module 3: Workflow Automation with Agents
What you'll learn
- Apply agentic AI for business process automation in enterprises
- Differentiate orchestration vs. choreography in workflow design
- Use agentic tools like LangChain, AutoGPT, and BabyAGI for automation
- Monitor and manage agents with AgentOps and human-in-the-loop systems
- Integrate APIs and enterprise systems for agent workflows
- Analyze BFSI, HR, telecom, logistics, and insurance automation case studies
Skills you'll gain
Workflow AutomationOrchestration & ChoreographyLangChainAutoGPT/BabyAGIAPI IntegrationAgentOpsIndustry Case Studies
Module 4: Risks, Governance & Ethics
Module 4: Risks, Governance & Ethics
What you'll learn
- Identify common failure modes and security risks in autonomous agents
- Detect and mitigate bias in autonomous decision-making
- Apply governance and oversight frameworks for multi-agent systems
- Ensure auditability, explanation, and regulatory compliance
- Conduct adversarial red-teaming to test agent security
- Design human override, fail-safe, and liability structures for MAS
Skills you'll gain
Risk ManagementAI SecurityBias MitigationGovernance ModelsExplainabilityRed-TeamingHuman Override
Module 5: Future of Agentic AI
Module 5: Future of Agentic AI
What you'll learn
- Analyze next-gen trends: self-improving agents and human-AI teaming
- Apply multi-agent simulations for economies, markets, and policies
- Explore industry use cases in finance, manufacturing, and education
- Evaluate blockchain, DeFi, quantum, and metaverse-driven agent innovations
- Assess defense, agriculture, and Indian pilot projects in agentic AI
- Build long-term strategies for leveraging agentic AI in business and society
Skills you'll gain
Next-Gen AgentsHuman-AI CollaborationMulti-Agent SimulationBlockchain & DeFi AgentsQuantum AIMetaverse AgentsIndustry Applications
