Vector Search and Embeddings: Build Smart Search Applications

Are you looking to move beyond keyword matching and create search experiences that truly understand user intent? This course provides a foundational understanding of vector search and embeddings, empowering you to design and implement intelligent search solutions that deliver highly relevant results and minimize AI hallucinations. What you'll learn: * Understand the core concepts of vector embeddings and their role in semantic search * Learn to generate and manage vector embeddings for various data types * Explore fundamental embedding models and their impact on search relevance * Apply techniques for performing efficient vector similarity search * Implement hybrid search strategies combining keyword and semantic approaches * Develop retrieval-augmented generation (RAG) patterns to build grounded AI systems * Practice integrating a vector search service like Vertex AI Vector Search into an application The course begins with foundational concepts, progressing through practical implementation techniques for semantic and hybrid search, and culminating in advanced patterns like retrieval-augmented generation for robust AI applications. This course is designed for beginners interested in AI, machine learning, and application development, with no prior experience in vector search or embeddings required. Start building the next generation of intelligent search and AI applications today.