AI Agents & Autonomous Systems Development Training Course

Course Overview

Learning Objectives

• By the end of the course, participants will be able to:
• Understand the architecture and operating principles of AI agents and autonomous systems.
• Identify suitable business and operational use cases for AI agents.
• Design agent architectures using models, tools, memory, and orchestration components.
• Implement planning, reasoning, and task decomposition mechanisms.
• Integrate AI agents with APIs, databases, enterprise systems, and external tools.
• Apply retrieval-augmented generation to improve agent knowledge and responses.
• Design multi-agent systems for complex collaborative tasks.
• Implement human-in-the-loop controls and escalation mechanisms.
• Evaluate agent accuracy, reliability, safety, and operational performance.
• Identify security, privacy, governance, and compliance requirements.
• Develop monitoring and observability approaches for autonomous systems.
• Prepare practical strategies for deploying and scaling AI agent solutions.

Who Should Attend

Learning Outcomes

• Upon completion of the course, participants will be able to:
• Assess AI agent architectures and autonomous system designs.
• Identify and prioritize suitable AI agent use cases.
• Design agent workflows and task-decomposition strategies.
• Configure AI models as reasoning and decision-support components.
• Integrate agents with APIs, databases, enterprise applications, and external tools.
• Implement memory and context-management mechanisms.
• Develop retrieval-augmented agent solutions.
• Design and coordinate multi-agent workflows.
• Establish human oversight and controlled autonomy mechanisms.
• Evaluate agent performance, reliability, safety, and failure modes.
• Implement monitoring, security, governance, and observability controls.
• Develop an implementation roadmap for production-ready AI agent systems.

Course Outline