Getting Started with Vector Databases and AI Embeddings: Discover how vectors embeddings and databases fuel modern AI search and applications

Idan Gabrieli

€82.99

Video Sep 2025 2hrs 1st Edition

Idan Gabrieli

€82.99

Video Sep 2025 2hrs 1st Edition

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Key benefits

Beginner focused foundation of vectors embeddings and databases in AI
Real world relevance with use cases from search RAG and recommendations
Clear pedagogy combining theory context and applied practical examples

Description

Artificial intelligence relies on vectors and embeddings to make sense of information in ways traditional databases cannot. This course begins by exploring the foundations, starting with the concept of vectors, embeddings, and similarity metrics. You’ll see how raw data is transformed into meaningful numerical representations that AI can analyze and compare. From there, you move into vector databases, the specialized systems designed to manage structured and unstructured data at scale. You’ll learn the workflows of vector search, understand how these databases function, and explore how to choose the right one for your projects. The course provides context for both the theory and the practical steps of working with vectorized information. The final section focuses on industry use cases that highlight the transformative impact of vector databases. You’ll discover how they power semantic search, drive recommendation engines, enhance retrieval-augmented generation, and support anomaly detection and visual search. By the end of the course, you’ll be prepared to apply these concepts to build innovative AI-driven solutions.

Who is this book for?

This course is designed for beginners curious about AI and data, as well as professionals seeking practical knowledge of embeddings and vector databases. It is ideal for data scientists, software developers, engineers, and business analysts who want to explore semantic search and AI applications. Product managers and tech leaders will also benefit from understanding how these technologies shape modern solutions. No advanced AI or database skills are required, though basic AI familiarity is useful.