AI-202
Advanced Agentic AI Engineering
Deepen your expertise in Agentic AI with advanced frameworks and design strategies. Learn to build enterprise-grade multi-agent systems with sophisticated reasoning, agent-to-agent communication, and robust frontends using Next.js and TypeScript. Capstone project included.
Available Sections:
Details
Building directly upon the foundational principles learned in AI-201, AI-202 propels students into the forefront of Advanced Agentic AI Engineering. This intensive course focuses on utilizing sophisticated libraries and frameworks, to design, develop, and deploy complex, enterprise-ready AI agent systems. Students will learn to create agents capable of sophisticated reasoning, intricate task execution, and collaborative problem-solving within multi-agent ecosystems.
Key Learning Modules
Module 1Advanced Agent Frameworks
This module provides a deep dive into Cloud Native Agentic AI, learning to build complex AI agents locally. Students will learn to leverage advanced features for agent configuration, workflow orchestration, and collaborative agent design.
Module 2Sophisticated Agent Design & Complex Task Execution
Moving beyond basic agent functionality, this module focuses on designing agents that can handle intricate tasks and engage in sophisticated decision-making. Topics include advanced prompt engineering, memory management in multi-agent systems, and strategies for handling complex, multi-step tasks.
Module 3Agent-to-Agent Communication and Orchestration
A cornerstone of advanced Agentic AI, this module delves into the principles and practices of effective agent-to-agent communication. Students will explore different communication protocols, orchestration patterns, and strategies for building coherent and collaborative multi-agent systems.
Module 4MCP Server Development and Integration for Advanced Agents
Expanding on the MCP concepts from AI-201, this module focuses on developing and integrating robust Model Context Protocol (MCP) servers to enhance the capabilities of advanced agents. Students will learn to build scalable and efficient MCP architectures for complex agentic solutions.
Module 5AgentOps principles specifically applied Cloud Native Deployments
Including agent lifecycle management, configuration management, and best practices for operating cloud-based systems in production environments.
Module 6Agentic Frontend Development with Next.js and TypeScript
This module shifts focus to the user interface, introducing Next.js and TypeScript for building dynamic and user-friendly frontends for agentic systems. Students will learn to create interactive web interfaces that seamlessly integrate with backend AI agents, ensuring optimal user experience.
Module 7Capstone Enterprise Agentic Solution Project
The course culminates in a significant professional project. Students will apply all acquired knowledge to design and develop a complete enterprise-level agentic solution. Projects will emphasize AI-to-AI communication, MCP Server and Knowledge Graph integration, and a modern, user-centric web frontend.
Course Outcomes
Proficiently utilize advanced Agentic AI frameworks, particularly OpenAI Agents SDK, and apply AgentOps principles for Agentic systems.
Design and implement sophisticated AI agents capable of complex task execution and decision-making.
Architect and manage effective Agent-to-Agent communication and orchestration within multi-agent systems.
Develop and integrate robust MCP Servers to enhance advanced agent capabilities.
Build dynamic and user-friendly Agentic frontends using Next.js and TypeScript.
Design and develop complete enterprise-level Agentic AI solutions incorporating advanced concepts and technologies.
Prerequisites
Note: These prerequisites provide essential knowledge for success in this course. If you haven't completed these courses, consider taking them first or reviewing the relevant materials.