Introduction to Agentic AI

This introductory-level course is geared for non-technical business professionals seeking to harness the power of Artificial General Intelligence (AGI) to improve their productivity, enhance decision-making, and drive innovation within their organizations. This course is valuable for a wide range of industries and job roles.

 

Some roles that might benefit from attending include:

- Technical Professionals

- AI Practitioners

- Business Analysts

- Software Developers & Architects

- Technology Managers

- Security, Governance and Compliance Professionals

This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you’ll learn how to:

• Distinguish Agentic AI from Other AI Paradigms: Define the core characteristics of agentic AI and differentiate autonomous agents from traditional machine learning models, generative AI applications, copilots, and deterministic automated workflows.
• Architect and Deconstruct AI Agent Core Components: Identify and integrate the critical structural pillars of an agent—including foundation models, goal frameworks, system instructions, tools, memory systems, and state management.
• Design Advanced Reasoning, Planning, and Prompting Mechanisms: Engineer prompts and behavioral instructions that guide autonomous planning and decision-making, enabling agents to decompose goals, use external tools, and execute complex, multi-step tasks.
• Implement Multi-Agent Collaboration and Orchestration Patterns: Compare common agentic system architectures and design frameworks where multiple specialized agents collaborate, delegate tasks, and coordinate activities to solve distributed problems.
• Deploy, Observe, and Evaluate Enterprise Solutions: Identify high-value enterprise use cases, determine appropriate levels of autonomy, and systematically evaluate performance using execution trajectories, tool interaction metrics, reliability, cost, and modern AgentOps observability practices.
• Secure and Govern Autonomous Systems: Mitigate security risks—such as prompt injection, excessive permissions, and tool misuse—by applying robust guardrails, least-privilege access controls, human-in-the-loop interfaces, and responsible AI governance frameworks.

This course doesn’t require a technical background, however in order to be successful in this course you need possess:

• Basic computer literacy, and a fundamental understanding of business processes (such as marketing, data analysis, project management, or customer support, etc.)
• Basic data manipulation skills: While not required, a basic understanding of working with data, such as using spreadsheets (e.g., Microsoft Excel or Google Sheets) for data organization and simple calculations, would be beneficial for participants.
• Understanding agentic AI concepts, architectures, and practical applications.
• A general understanding of AI and Generative AI is helpful but not required.

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You’ll explore how agentic AI differs from traditional and generative AI, examine the essential building blocks of agentic systems