How to build AI Agents with Claude API in Python

Unlock the power of Anthropic's state-of-the-art language models with this comprehensive developer's guide to building production-ready AI agents using Python. Designed for software engineers, data scientists, and AI enthusiasts, this course bridges the gap between theoretical artificial intelligence concepts and practical, hands-on implementation. Instructor Justin Barnett guides you step-by-step through the Claude 3 API landscape, detailing the specific differences, pricing structures, and rate limits across the model family to help you make cost-effective architectural decisions. You will master the fundamentals of Retrieval-Augmented Generation (RAG) by constructing a custom pipeline from scratch, leveraging vector databases to feed external knowledge directly to your LLM-powered applications. Beyond basic API interactions, you will dive deep into structural topics like the Model Context Protocol (MCP) and systematic evaluation frameworks. By learning how to write robust system prompts and establish metrics to run systematic evaluations, you will be equipped to iterate, debug, and confidently scale your AI applications from simple code scripts to resilient, autonomous agents capable of solving real-world business challenges.