AI-201
Fundamentals of Agentic AI and DACA AI-First Development
Explore Agentic AI and DACA frameworks, building intelligent agents with UV, OpenAI Agents SDK, and protocols like MCP and A2A. Gain hands-on experience in design patterns and memory management.
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Details
This course introduces students to the principles and practices of Agentic AI and Data-Augmented, Context-Aware (DACA) AI-first development. Students will explore foundational theories, modern tools, frameworks and design patterns for building intelligent, context-aware AI agents. The course also covers Agentic Protocols like Model Context Protocol (MCP) and Agent2Agent (A2A) Protocol in depth. Through hands-on projects, students will gain practical experience in developing and deploying AI-driven applications.
Key Learning Modules
Module 1Agentic and DACA Theory
Explore the core principles of Agentic AI and Data-Augmented, Context-Aware (DACA) frameworks. Understand their applications in modern AI development and how they enable intelligent, autonomous systems.
Module 2UV and OpenAI Agents SDK
Master the development of AI agents using UV and OpenAI Agents SDK. Learn to build, configure, and test functional AI agents through hands-on projects, focusing on real-world applications.
Module 3Agentic Design Patterns
Study and apply common agentic design patterns to solve practical AI challenges. Gain expertise in designing robust and scalable AI systems using industry-standard approaches.
Module 4Model Context Protocol (MCP)
Learn to use Model Context Protocol (MCP) to enable AI agents to integrate with databases, APIs, and services for real-time data access. Support context management and interoperability across AI platforms.
Module 5Agent-to-Agent (A2A) Protocol
Study the Agent-to-Agent (A2A) protocol to facilitate secure, standardized communication and data exchange between autonomous AI agents. Support real-time collaboration for distributed problem-solving and multi-agent workflows.
Module 6Memory Management with LangMem and mem0
Implement memory management techniques using LangMem and mem0 to enhance AI agent context retention. Learn to build intelligent systems capable of maintaining state and context.
Course Outcomes
Explain the theoretical foundations of Agentic AI and DACA frameworks.
Utilize UV and OpenAI Agents SDK to build functional AI agents.
Apply agentic design patterns to solve real-world problems.
Implement memory management techniques using LangMem and mem0.
Use Model Context Protocol (MCP) to connect AI Agents and interact with external data sources, tools, and systems.
Use Agent-to-Agent (A2A) protocol is to facilitate secure, standardized communication and data exchange between autonomous AI agents.
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.