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Coursera

Hands-On AI Agent Development with Claude API in Python

Packt via Coursera

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Overview

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Build practical skills for developing AI agents with Python and the Claude API. You’ll learn how LLMs, transformers, prompting, multimodal AI, RAG, MCP, and fine-tuning support modern AI applications. You’ll begin with core AI concepts and prompt engineering, including zero-shot and few-shot prompting, prompt evaluation, and frameworks for writing effective prompts. You’ll then explore Claude models, API capabilities, SDKs, API keys, and the Messages API. Next, you’ll examine AI application architecture, latency, rate limits, and RAG pipelines, including reranking for limited context windows. You’ll then learn how AI agents use tools, define tool interfaces, chain tool calls, and apply tool-use best practices. This intermediate course is designed for Python developers and technical learners interested in building AI applications. Basic Python and API knowledge is recommended; prior AI development experience is helpful but not required. By the end of the course, you will be able to build Claude-powered AI applications, create RAG pipelines, design AI agents, implement tool calling, chain tools for complex tasks, and apply effective prompting and architecture practices. This course is based on Hands-On AI Agent Development with Claude API in Python, by Delta X Technology LLC. Copyright © 2024 Justin Barnett All rights reserved. No part of this course may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Syllabus

  • Introduction
    • In this module, we will introduce the course, its objectives, and the key topics you will explore as you progress. We will establish a foundation by defining essential AI terminology and commonly used acronyms. We will also prepare you with the core vocabulary needed to understand subsequent concepts in AI and agent development.
  • AI Overview
    • In this module, we will explore the fundamental technologies and techniques behind modern generative AI, including LLMs, Transformers, multimodal models, RAG, MCP, and fine-tuning. We will examine prompt engineering strategies such as zero-shot and few-shot prompting and introduce a structured framework for writing effective prompts. We will also learn how to evaluate prompts and models to select and optimize AI approaches for different applications.
  • Claude 3 API Overvie
    • In this module, we will explore the Claude API ecosystem and examine the differences among Opus, Haiku, and Sonnet models. We will learn how to obtain an Anthropic API key, work with available SDKs, and understand the API's core capabilities. We will also use the Messages API to build practical interactions with Claude and establish the foundation for developing AI-powered applications.
  • AI Application Architecture
    • In this module, we will examine the architectural principles and design considerations involved in building scalable AI applications. We will build a RAG pipeline from scratch, explore reranking strategies, and address practical challenges such as latency, rate limits, and limited context windows. We will also introduce AI agents and compare open-source and closed-source models to help you make informed architectural decisions.
  • Tool Calling with Claude
    • In this module, we will explore how tool calling extends Claude's capabilities and enables the development of more functional AI agents. We will learn how to define tools, integrate them into agent workflows, and chain multiple tool calls to solve advanced tasks and answer complex questions. We will also apply best practices for reliable and effective tool use when building practical AI agent applications.

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Packt - Course Instructors

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