Enterprise Search with AWS Kendra and Machine Learning

Finding the right information across fragmented enterprise data sources can be a major bottleneck for modern organizations. This text-only course shows you how to leverage AWS Kendra, an intelligent search service powered by machine learning, to solve this challenge and make information discovery seamless. You will learn how to set up, configure, and optimize an enterprise search solution that understands natural language questions and retrieves precise answers from various document repositories. What you'll learn: - Understand the foundational concepts of semantic search and machine learning-powered information retrieval. - Configure AWS Kendra index structures and connect diverse data sources like S3, databases, and collaboration tools. - Apply natural language processing techniques to improve search relevance and query accuracy. - Implement modern search patterns, including hybrid search and integration with retrieval-augmented generation (RAG) workflows. - Secure your search infrastructure using AWS Identity and Access Management (IAM) and document-level access controls. - Practice tuning search results using relevance tuning, custom FAQs, and user feedback loops. The course begins with essential terminology of enterprise search and index architecture before guiding you through connecting data sources, tuning search relevance, and securing your implementation. You will work through written scenarios and conceptual exercises designed to build practical cloud search skills. This course is designed for IT professionals, data analysts, and cloud beginners who want to build modern search solutions without needing prior machine learning expertise. Start reading today to unlock the power of intelligent search for your organization.