Introduction to Agentic AI

Module 1: Foundations of Agentic AI

• Trace the evolution of AI agents.
• Explore key agent types and behaviors.
• Compare assistants, copilots, workflows, and agents.

Module 2: Introducing AI Agents

• Explore core AI agent components.
• Understand agent reasoning and execution.
• Learn how agents use tools and data.

Module 3: Prompting for Agentic AI

• Write prompts with clear goals and roles.
• Guide planning, decisions, and tool use.
• Add memory, constraints, and guardrails.

Module 4: Architectures and Patterns for Agentic Systems

• Explore core agentic architecture components.
• Compare workflows, agents, and common patterns.
• Select architectures based on needs and risk.

Module 5: Tools, Decision-Making and Agent Behavior

• Understand agent decisions and tool use.
• Explore planning, execution, and evaluation.
• Manage failures, loops, and autonomy.

Module 6: Multi-Agent Systems and Coordination

• Explore multi-agent roles and collaboration.
• Coordinate tasks, context, and results.
• Evaluate benefits, failures, and complexity.

Module 7: Agentic AI in Real-World Applications

• Explore enterprise agentic AI use cases.
• Choose the right approach and autonomy.
• Connect agents with systems, data, and people.

Module 8: Evaluating, Deploying and Operating AI Agents

• Test and deploy AI agents.
• Track performance, cost, and reliability.
• Detect failures and continuously improve.

Module 9: Security, Governance and Responsible Agentic AI

• Identify security and operational risks.
• Apply guardrails, permissions, and oversight.
• Address governance, privacy, and accountability.