PostgreSQL AI: Introduction to semantic search Training Course

Develop expertise in AI integration with Postgres through this instructor-led live training in Kenya. You will learn to configure extensions, apply pgvector embeddings, and connect LLMs for immediate insights. Optimize queries and construct intelligent systems in a hands-on live-lab environment.

This 21-hour instructor-led training in Kenya empowers data engineers and DBAs to integrate AI models into PostgreSQL. Participants will 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 fundamentals of PostgreSQL server extensions and libraries designed to integrate artificial intelligence techniques into database systems. Key topics include similarity and semantic search using embedding vectors, Text-to-SQL querying, and Retrieval-Augmented Generation (RAG). Participants will learn to install PgVector and PgAI, generate and load vector embeddings, create vector indexes, implement semantic search and RAG capabilities, and develop Text-to-SQL applications utilizing LangChain with Python or JavaScript. Through demonstrations and practical exercises, the course reinforces core concepts and essential skills.

This practical, hands-on course concentrates on the real-world application of performance tuning in PostgreSQL. Participants will gain proficiency in analyzing query execution, optimizing indexes, adjusting memory and system parameters, and effectively monitoring workloads. By engaging with real-world scenarios and live exercises, learners will learn to identify and resolve bottlenecks at both the database and system levels.

This program equips you with the fundamental skills needed to install, set up, and oversee PostgreSQL databases with confidence. You will explore methods for enforcing user security, executing comprehensive backups and restorations, managing logging outputs, and optimizing key performance parameters. By engaging in hands-on activities, you will apply practical administrative techniques and build a strong foundation for tackling advanced subjects like performance tuning and replication.

In this instructor-led live training Kenya (onsite or remote), participants will gain knowledge of the general and advanced aspects of PostgreSQL, including administration, performance tuning, advanced development, and replication. This is achieved through a series of hands-on live-lab exercises that cover 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 live, instructor-led training in Kenya empowers advanced DevOps professionals and database engineers to deploy PostgresAI at an enterprise scale. Participants will gain mastery over database cloning, AI-driven query optimization, and monitoring through hands-on exercises in a live-lab environment.

This module delivers a deep dive into replication techniques, high availability standards, and cluster oversight for PostgreSQL. It enables learners to construct and supervise distributed environments, automate failover procedures, and evaluate various load balancing and connection pooling technologies. The training features live replication exercises and simulated recovery scenarios to enhance learning outcomes.

This instructor-led, live training in Kenya (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:

• Understand the architecture and components of PostgreSQL 16.
• Utilize advanced SQL features and PostgreSQL extensions.
• Implement security best practices and access controls.
• Perform database administration tasks, including backup, recovery, and monitoring.
• Optimize database performance through tuning and indexing strategies.
• Utilize PostgreSQL's built-in tools for high availability and replication.
• Integrate PostgreSQL with modern application development frameworks.