Packt

Agent Memory, Tools, and Multi-Agent Collaboration

Packt

Agent Memory, Tools, and Multi-Agent Collaboration

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Implement advanced prompting paradigms for multi-step reasoning

  • Build hierarchical RAG memory pipelines for long-term agent context

  • Deploy multi-agent systems with task delegation and consensus mechanisms

Details to know

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Recently updated!

October 2026

Assessments

4 assignments

Taught in English

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This course is part of the Agentic AI Systems: Design, Build and Deploy Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

This module explores advanced memory systems in AI agents, including layered memory structures, RAG pipelines, vector databases, and episodic memory management. Learners will gain practical skills in implementing and optimizing memory solutions for intelligent agents.

What's included

25 videos1 reading1 assignment

This module explores how to extend the capabilities of agentic AI using tools, focusing on integration, design, and safety. Learners will gain practical skills in implementing tool calling, composition, and error handling in AI agents. The module also covers advanced agent archetypes and their real-world applications.

What's included

20 videos1 assignment

This module explores the design and implementation of multi-agent systems, focusing on communication strategies, collaboration patterns, and human-in-the-loop integration. Learners will analyze different architectures and apply coding techniques to build scalable agent-based solutions. Practical exercises reinforce understanding of real-world applications like customer support and research automation.

What's included

19 videos1 reading2 assignments

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Packt
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