Prompt Engineering and NLP Architectures on AWS Bedrock

As generative AI becomes central to modern software, developers need structured patterns to guide large language models reliably. This text-based course helps you transition from basic prompting to building sophisticated natural language processing (NLP) applications on AWS Bedrock. You will gain a deep understanding of how to orchestrate foundation models, structure complex prompt templates, and manage text generation workflows. By reading through clear code examples and conceptual breakdowns, you will learn to construct production-ready NLP architectures that deliver consistent, high-quality results. What you'll learn: Understand foundational NLP concepts and the Bedrock ecosystem; Design structured prompt templates and multi-step prompt architectures; Configure foundation models for tasks like summarization, translation, and classification; Implement Retrieval-Augmented Generation (RAG) patterns for custom data integration; Apply security, cost optimization, and prompt evaluation best practices. The course starts with essential terminology and core NLP concepts before guiding you through prompt design workflows. You will progress from simple model calls to advanced multi-prompt architectures and RAG patterns using clear, written explanations and code snippets. This course is designed for software developers, data enthusiasts, and beginners eager to build AI-driven language tools, with no prior experience with Bedrock or NLP required. Start reading today to master prompt architecture and build next-generation language applications.