What Will You Learn?
In this course, you will learn how to build an agent with long-term memory by creating a personal email agent that can respond, ignore, and notify the user using writing, scheduling, and memory tools. You’ll develop your agent’s memory by adding facts to its memory store, providing examples to learn the user’s preferences, and optimizing system prompts to evolve instructions based on previous responses."jjj"
About This Course
Provider: DeepLearning.AI
Format: Online
Duration: 1 Hour 4 minutes to complete [Approx.]
Target Audience: Intermediate level
Learning Objectives: In this course, you’ll learn how memory works and how the three types of memory – semantic, episodic, and procedural – are used in agentic workflows.
Assessment and Certification: NA
Instructor: Harrison Chase.
Course Prerequisites: Basic Python coding experience and understanding of LLM prompting and LLM application development..
Key Topics: By the end of this course, you will have the foundational mental framework to build an agent with long-term memory using LangGraph.
Topic Covered:
- Introduction
- Introduction to Agent Memory
- Baseline Email Assistant
- Email Assistant with Semantic Memory
- Email Assistant with Semantic + Episodic Memory
- Email Assistant with Semantic + Episodic + Procedural Memory
- Conclusion
- Quiz
- Appendix - Tips and Helps
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