DeepLearning.AI Courses - Build Memory-Aware Agents

Learn more: https://bit.ly/4slpBEM New short course built in collaboration with Oracle: Agent Memory: Building Memory-Aware Agents. Many AI agents work well within a single session but lose everything when the session ends. In this course, you’ll learn how to build a memory-first architecture that allows agents to persist knowledge, retrieve relevant context, and update what they know across sessions. Using Oracle AI Database, LangChain, and LLM-powered pipelines, you’ll build a complete agent memory system that turns a stateless agent into one that can learn and improve over time. In this course, you’ll learn to: - Design a memory-first architecture and understand why stateless agents struggle with long-horizon tasks - Build persistent memory stores and implement a Memory Manager that orchestrates how agents read and write memory - Scale tool use by treating tools as procedural memory and retrieving them with semantic search - Implement memory extraction, consolidation, and write-back pipelines so agents can update what they know - Assemble a fully stateful memory-aware agent that loads prior context and improves across sessions The course is taught by Oracle’s Richmond Alake, Director of AI Developer Experience, and Nacho Martínez, Principal Data Science Advocate at Oracle. Enroll now: https://bit.ly/4slpBEM