Course Outline
Introduction to: vectors, AI vector embeddings, popular AI embedding models, semantic search, distance measures
Overview of vector indexing techniques: IVFFlat index, HNSW index
PgVector extension for PostgreSQL: installation, storing and querying high-dimensional vectors, distance measures, using vector indexes
PgAI extension for PostgreSQL: installation, generating embeddings, implementing Retrieval-Augmented Generation, advanced development patterns
Overview of Text-to-SQL solutions: LangChain framework
Course outcome: By the end of the course, students will be able to design and build elements of AI-powered database applications using PostgreSQL extensions and libraries. They will gain practical experience with techniques for integrating large language models (LLMs) and vector search into real-world systems, enabling them to develop applications such as semantic search engines, AI assistants, and natural-language database interfaces.
Requirements
basic knowledge of SQL, basic experience with PostgreSQL, basic knowledge of Python or JavaScript programming languages
Audience: database developers, system architects
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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Testimonials (2)
The provided examples and labs
Christophe OSTER - EU Lisa
Course - PostgreSQL Advanced DBA
1. A very well-structured training program 2. The warm atmosphere the trainer created, along with his outstanding personal professionalism 3. That the trainer explained everything as if he were talking to a complete beginner, without slipping into any technical jargon.
