AI-201
Fundamentals of Agentic AI
Delve into Agentic AI, focusing on autonomous intelligent systems. Build a strong foundation in Conversational and Generative AI, progressing to hands-on development using the OpenAI Agents SDK. Explore AgentOps, deployment strategies, and observability to prepare for real-world AI applications.
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Details
This foundational course provides an intensive introduction to Agentic AI, a cutting-edge field focused on building autonomous, intelligent systems with memories, Agentic RAG (Retrieval Augmented Generation) and standards based MCP (Model Context Protocol) tool calling. Students will first establish a strong understanding of the essential building blocks: Conversational and Generative AI. We will then rapidly progress into the exciting realm of prototyping Agentic AI systems using OpenAI Responses API and OpenAI Agents SDK, emphasizing practical application and hands-on skill development, including crucial aspects of Short and Long-Term Memories, Standardized Tools Calling (MCP), Agentic RAG, AgentOps, Deployment, and Observability.
Key Learning Modules
Module 1Python Fundamentals & Modern Typing
Establish a strong foundation in Python syntax, data structures (lists, dictionaries, sets, tuples), control flow, and functions. Critically, we introduce Python's type hinting system, Generics, and Decorators emphasizing its importance for code clarity, error prevention, and maintainability, especially in complex AI projects.
Module 2Object-Oriented Programming (OOP) in Python for AI
Master the principles of OOP (classes, objects, inheritance, polymorphism, encapsulation, dataclasses) and understand how to apply them effectively in AI development. Learn to structure complex AI systems using object-oriented design for modularity and reusability.
Module 3Advanced Python Concepts: Asynchronous Programming & Performance
Dive into advanced Python features like asynchronous programming (asyncio) for building efficient and concurrent applications, crucial for handling large datasets and complex AI workloads. Explore performance optimization techniques and understand the role of Python's Global Interpreter Lock (GIL) and upcoming solutions like 'No GIL' for enhanced concurrency.
Module 4Mastering Autonomous AI Agents with OpenAI Agents SDK, Agentic RAG, and Memories
The heart of the course focuses on OpenAI Agents SDK, Agentic RAG, LangMem, and Zep mastery. Students will learn to leverage OpenAI Agents SDK to orchestrate complex AI workflows and develop truly autonomous agents capable of performing sophisticated tasks with minimal human intervention. We will also learn to store memories in LangMem and Zep. Hands-on projects will solidify these skills.
Module 5Agentic Design Patterns & Cloud Native Design Patterns
This module introduces the core concepts of Agentic AI design. Students will explore common design patterns for autonomous agents documented by Anthropic.
Module 6Future of Python & Python in AI
Explore the evolving landscape of Python, including upcoming features and performance improvements. Discuss the continued dominance of Python in the AI field and its application in cutting-edge AI domains like Machine Learning, Deep Learning, and Agentic AI.
Course Outcomes
Articulate the foundational principles of Conversational, Generative, and Agentic AI.
Design, develop, and deploy prototype Conversational AI systems.
Implement Agentic Design Patterns using the OpenAI Agents SDK framework.
Build autonomous AI Agents capable of performing complex tasks.
Store short and long-term memories in LangMem, Zep, and Vector Databases.
Deep understanding and implementation of Agentic RAG.
Construct and utilize MCP Servers and Agentic Clients to augment Large Language Models.
Understand the concepts of AgentOps in prototypical deployments.
Understand the concepts and potential applications of Agentic Payments.
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.