PostgreSQL AI: Introduction to semantic search Training Course

Gain mastery over AI integration in Postgres through this instructor-led live training in Czech Republic. Learn to configure extensions, implement pgvector embeddings, and connect LLMs for instant insights. Optimize queries and build intelligent systems through hands-on activities in a live-lab setting.

This 21-hour instructor-led training in Czech Republic assists data engineers and DBAs in integrating AI models into PostgreSQL. Participants learn to deploy optimized architectures, implement vector search, and enforce strict governance, ensuring secure and high-performance enterprise-grade AI solutions.

This course explores the foundational aspects of PostgreSQL server extensions and libraries designed to incorporate artificial intelligence into database systems. Key topics include similarity and semantic search utilizing embedding vectors, Text-to-SQL query capabilities, and Retrieval-Augmented Generation (RAG). Participants will learn to install PgVector and PgAI, as well as generate and load vector embeddings, establish vector indexes, implement semantic search and RAG workflows, and develop Text-to-SQL applications using LangChain with Python or JavaScript. Through live demonstrations and hands-on exercises, the course reinforces core concepts and practical skills.

This practical course is dedicated to the real-world application of performance tuning in PostgreSQL. Learners will acquire the skills to dissect query execution, refine indexing strategies, fine-tune memory and system settings, and effectively oversee workloads. Through practical exercises and real-world case studies, the course illustrates how to pinpoint and eliminate bottlenecks across both the database and system architectures.

This curriculum delivers the foundational expertise necessary to successfully deploy, configure, and administer PostgreSQL databases. Learners will discover methods for controlling user security, conducting backup and recovery operations, handling logs, and fine-tuning initial parameters. Via practical demonstrations, students will carry out authentic administrative duties and lay the groundwork for more complex areas such as performance tuning and replication.

In this instructor-led, live training at Czech Republic (onsite or remote), participants will explore the general and advanced aspects of PostgreSQL, including administration, performance tuning, advanced development, and replication. The course includes a series of hands-on, live-lab exercises covering setup, configuration, testing, deployment, and troubleshooting.

By the end of this training, participants will be able to:

• Use advanced administration techniques to configure and manage a PostgreSQL server.
• Optimize the database and queries for maximum performance.
• Replicate and scale a PostgreSQL server.

This instructor-led, live training in Czech Republic empowers advanced DevOps professionals and database engineers to implement PostgresAI at an enterprise scale. Participants will gain mastery in database cloning, AI-driven query optimization, and monitoring through hands-on exercises within a live-lab environment.

This course delivers a deep dive into replication, high availability, and cluster management in PostgreSQL. It enables participants to develop and manage multi-node setups, implement failover automation, and assess load balancing and connection pooling options. The program incorporates live replication exercises and recovery drills.

This instructor-led, live training in Czech Republic (online or onsite) is aimed at intermediate-level developers and administrators who wish to leverage the latest features and improvements in PostgreSQL 16.

By the end of this training, participants will be able to:

• Grasp the architecture and components of PostgreSQL 16.
• Exploit advanced SQL capabilities and PostgreSQL extensions.
• Apply security best practices and access controls.
• Execute database administration duties, encompassing backup, recovery, and monitoring.
• Enhance database performance via tuning and indexing strategies.
• Make use of PostgreSQL's native tools for high availability and replication.
• Integrate PostgreSQL with contemporary application development frameworks.