Hands-On Introduction To Building Ai Agents With Strands

Hands-On Introduction To Building Ai Agents With Strands
Published 7/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 56m | Size: 3.11 GB
Hands-on guide to AI agents with Strands SDK: tool calling, memory, multi-agent systems
What you'll learn
Understand what AI agents are and how they differ from simple LLM calls
Install and configure the Strands SDK and connect it to a model provider (OpenAI, Anthropic, or Bedrock)
Build agents that reason, plan, and execute actions autonomously
Create tools with the @tool decorator so agents can call functions and APIs
Use conversation managers and agent state to manage memory and context
Compose multi-agent systems with the agents-as-tools pattern and Swarms
Requirements
Basic programming knowledge
Understanding of how LLMs work (having used ᑕᕼᗩTGᑭT or similar)
No prior AI agent experience required
Description
This hands-on course provides a practical introduction to building AI agents using Strands, an open-source, model-agnostic framework for creating intelligent applications that can reason, use tools, remember context, and collaborate with other agents.
If you've ever wanted to build AI agents that go beyond simple chatbots and can solve real-world tasks autonomously, this course is for you.
We focus on learning by doing. There are no theory-heavy slides or unnecessary complexity. Instead, you'll build AI agents from the very beginning using the Strands SDK.
You'll start by understanding what AI agents are, how they differ from traditional LLM applications, and how the reason-act-observe loop enables autonomous behavior.
Then we'll move straight into practice.
You'll install Strands, connect it to a foundation model, and build your first AI agent before gradually adding more advanced capabilities.
Throughout the course, we'll explore concepts including

• Building AI agents with Strands
• The reason-act-observe agent loop
• Tool calling
• Creating custom tools
• Research and information retrieval agents
• Conversation memory and agent state
• Task planning and multi-step workflows
• Multi-agent architectures
• Agents-as-tools
• Self-organizing agent swarms
• Prompt engineering for AI agents
• Safety, guardrails, and invocation limits
• Deployment, observability, and cost optimization

Although the examples are implemented in Python, Strands is available for both Python and TypeScript, and the concepts covered throughout the course apply equally to both SDKs.
Everything is explained through practical examples designed to help you understand not only how AI agents work, but also how to design, extend, and deploy them in real-world applications.
By the end of this course, you'll be able to start building AI agents that use tools, maintain memory, collaborate with other agents, and solve complex tasks using the Strands framework.
If you want a clear, beginner-friendly, and hands-on introduction to building AI agents with Strands, this course is for you.
Who this course is for
Developers wanting to build AI agent applications and autonomous systems
Backend and full-stack engineers working in Python or TypeScript
Anyone curious about building intelligent autonomous systems with a modern model-agnostic framework

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