Vector Databases: From Embeddings to Applications

What You'll Learn

• Build efficient, practical applications, including hybrid and multilingual searches for diverse industries.
• Understand vector databases and apply them to GenAI applications without needing to train or fine-tune an LLM.
• Learn when best to apply a vector database to enhance your applications.

About This Course

Vector databases have become essential across fields like natural language processing, image recognition, and semantic search. With the integration of LLMs, they enable real-time data access, making applications such as Retrieval Augmented Generation (RAG) possible. This course provides a comprehensive understanding of vector databases, covering the formation and search of embeddings and guiding you in building powerful applications.

• Gain insights into your data using vector databases and LLMs.
• Build labs to form embeddings and conduct various search techniques for similar embeddings.
• Explore algorithms for rapid searches through large datasets.
• Build applications, including RAG and multilingual search, using vector databases.

By completing this course, you’ll have the knowledge to make informed decisions on applying vector databases to a wide range of applications.

Course Outline

• Introduction
  Overview of vector databases, their purpose, and applications in various fields.
• How to Obtain Vector Representations of Data
  Practical methods to create vector representations of data with code examples.
• Search for Similar Vectors
  Techniques for identifying similar vectors within large datasets.
• Approximate Nearest Neighbors
  Implementing approximate nearest neighbors to accelerate similarity searches.
• Vector Databases
  Overview of vector database architecture and capabilities with practical examples.
• Sparse, Dense, and Hybrid Search
  Explore different search methods and when to apply them in applications.
• Application - Multilingual Search
  Building an application for multilingual search using vector databases.
• Conclusion
  Recap of key concepts and next steps for implementing vector databases in projects.

Who Should Join?

This course is ideal for anyone interested in understanding and applying vector databases in their applications, with or without advanced machine learning skills.