Building AI Agents with OpenAI

The Building AI Agents with OpenAI Specialization prepares you to design, develop, and deploy advanced AI agents using OpenAI models, AgentKit, memory systems, retrieval-augmented generation (RAG), and the Model Context Protocol (MCP). This program teaches you the same techniques used in modern AI-driven applications, personal assistants, automation systems, and multi-agent architectures. Across three hands-on courses, you will learn how AI agents plan, reason, use tools, store and retrieve memory, communicate with other agents, and connect with external applications. In Course 1, you’ll build foundational agent architectures, implement tool calling, configure environment variables securely, and create reasoning workflows. Course 2 focuses on intelligent memory design—including short-term memory, long-term memory, summarization, embeddings, vector search, and hybrid RAG + memory agents. You will also integrate knowledge retrieval using Pinecone and MCP context fields. In Course 3, you will deploy end-to-end AI assistant systems with Streamlit, create multi-agent communication flows (A2A, MCP), integrate APIs, implement personalization, and build complete cloud-ready agent applications. By the end of the specialization, you will be equipped to build scalable, production-grade AI agents capable of reasoning, recalling information, taking actions, and collaborating with other agents—skills essential for modern AI engineering and enterprise automation

• Design intelligent AI agents using OpenAI models and structured reasoning workflows
• Implement advanced memory systems including short-term, long-term, summarization, embeddings, and hybrid RAG
• Build multi-agent communication flows using MCP, A2A messaging, and shared context fields
• Deploy AI-powered applications with secure API integration and cloud-ready architectures

• Basic familiarity with the topic and common terminology
• Readiness to practice through applied exercises or case-based work