Fundamentals of Agentic AI and Autonomous Systems Training Course
Formats⟩Live Virtual: 4 hrs./1 Day |In-Person: 6 hrs./1 Day
Fundamentals of Agentic AI and Autonomous Systems teaches participants to AI systems that can plan, make decisions, and take action across workflows. The course explores how agentic systems are structured, including components such as planning, memory, tools, and multi-agent setups, as well as common business applications like automation and decision support. Participants will learn how these systems operate through orchestration concepts, along with strategies for ensuring reliability, managing risk, and establishing governance and will be able to evaluate and apply agentic AI within their organization.
Learning Objectives »
Learn how agentic AI systems differ from traditional AI.
Describe key components and workflows of agentic systems.
Identify business use cases for agentic AI.
Understand how agentic systems operate and are managed.
Recognize risks and apply governance considerations.
Outline a basic roadmap for adopting agentic AI.
Course Agenda
Foundations of Agentic AI
Chatbots and Agents
Core Components of Agentic AI
Researching, Drafting, and Triggering
Business Patterns
Workflow Automation
Decision Support
Customer/Service Agents
Internal Copilots
How Agentic Systems Work
Non-technical view of Orchestration
Single vs. Multi-Agent Set Ups
Reliability Levels
Human-in-the-Loop Checkpoints
Risk, Governance and Compliance
Key Risks
Hallucinations and Bias
Over-automation and Data Leakage
Security
Governance Policies
Roles of Central AI Council
Evaluation and Monitoring
Agentic AI Roadmap
Maturity Paths
Capabilities and Roles Needed
What’s Trending
Fundamentals of Agentic AI and Autonomous Systems Training Course
Formats⟩Live Virtual: 4 hrs./1 Day |In-Person: 6 hrs./1 Day
Fundamentals of Agentic AI and Autonomous Systems teaches participants to AI systems that can plan, make decisions, and take action across workflows. The course explores how agentic systems are structured, including components such as planning, memory, tools, and multi-agent setups, as well as common business applications like automation and decision support. Participants will learn how these systems operate through orchestration concepts, along with strategies for ensuring reliability, managing risk, and establishing governance and will be able to evaluate and apply agentic AI within their organization.
Learning Objectives »
Learn how agentic AI systems differ from traditional AI.
Describe key components and workflows of agentic systems.
Identify business use cases for agentic AI.
Understand how agentic systems operate and are managed.
Recognize risks and apply governance considerations.
Outline a basic roadmap for adopting agentic AI.
Course Agenda
Foundations of Agentic AI
Chatbots and Agents
Core Components of Agentic AI
Researching, Drafting, and Triggering
Business Patterns
Workflow Automation
Decision Support
Customer/Service Agents
Internal Copilots
How Agentic Systems Work
Non-technical view of Orchestration
Single vs. Multi-Agent Set Ups
Reliability Levels
Human-in-the-Loop Checkpoints
Risk, Governance and Compliance
Key Risks
Hallucinations and Bias
Over-automation and Data Leakage
Security
Governance Policies
Roles of Central AI Council
Evaluation and Monitoring
Agentic AI Roadmap
Maturity Paths
Capabilities and Roles Needed
What’s Trending
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