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Free Download Oracle Database 26ai AI Vector Search for DBAs & Developers
Published 8/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 5h 26m | Size: 4.47 GB
Learn AI Vector Search, embeddings, similarity search, HNSW, IVF, and vector indexing in Oracle Database 26ai
What you'll learn
Explain Oracle AI Vector Search concepts, VECTOR data types, embeddings, and similarity search
Use VECTOR_DISTANCE() and multiple distance metrics to compare and rank vector embeddings
Create and work with HNSW and IVF vector indexes for approximate similarity search
Perform exact and approximate vector searches and interpret vector search execution plans
Configure and monitor the Vector Pool and understand its role in Oracle Database memory
Apply vector search concepts to enterprise scenarios, including basic RAG retrieval workflows
Requirements
Basic understanding of databases and SQL is recommended.
Basic AI knowledge is helpful but not required.
Learners should have access to an Oracle Database 26ai environment for the hands-on practices.
Description
This course contains the use of artificial intelligence.
Learn how Oracle Database 26ai enables AI Vector Search to bring semantic search capabilities directly into your database.
This course is designed for Oracle Database DBAs, developers, and IT professionals who want to understand and work with AI Vector Search using Oracle Database 26ai.
You will start with the fundamentals of vector data and embeddings, then progressively explore how Oracle Database stores, compares, searches, and indexes vectors. The course combines conceptual explanations, demonstrations, SQL examples, and self-paced practice activities to help you build a solid understanding of Oracle AI Vector Search.
You will learn how to work with the VECTOR data type, understand vector embeddings, and use VECTOR_DISTANCE() and different distance metrics to measure similarity between vectors. You will also explore exact and approximate similarity search and understand how vector search retrieves semantically similar information.
The course covers important vector indexing concepts, including HNSW and IVF vector indexes, and explains how these indexes support efficient approximate similarity search. You will also learn how to examine vector search execution plans, understand the Vector Pool, and work with relevant Oracle Database memory configuration and monitoring concepts.
The course also introduces Hybrid Search and provides a foundational understanding of how Vector Search can be used in Retrieval-Augmented Generation (RAG) applications.
What You Will Learn
- Oracle AI Vector Search architecture and fundamentals
- Oracle VECTOR data type and vector embeddings
- Vector distance metrics and similarity search
- Exact and approximate vector search
- HNSW and IVF vector indexes
- Vector search execution plans
- Vector Pool configuration and monitoring
- Hybrid Search concepts
- Basic Vector Search retrieval flow for RAG applications
Lab Environment & Requirements
The course includes self-paced practice activities to help you apply the concepts covered throughout the course.
To complete the hands-on practice activities, you will need access to a suitable Oracle AI Database environment.
Please note: A pre-configured lab environment is not provided with this course.
You can complete the practices using one of the following options
- Existing Database Environment: Use an existing Oracle AI Database 26ai environment, such as an on-premises or cloud-based environment. Oracle Database 23ai can also be used for the core Vector Search operations covered in these practices. However, Oracle AI Database 26ai is the recommended and validated environment for this course.
- Local Oracle AI Database 26ai Free: Install Oracle AI Database 26ai Free on your own computer using Oracle's official download and installation resources.
Detailed Lab Instructions and all required practice files are available in the course s section.
The goal of this course is to give you a strong technical foundation in Oracle AI Vector Search 26ai and the knowledge needed to understand how vector search can be designed, implemented, analyzed, and used in Oracle Database environments.
Who this course is for
Oracle Database DBAs who want to learn AI Vector Search in Oracle Database 26ai
Oracle Database developers who want to build applications using vector search
Developers and technical professionals interested in vector embeddings and semantic search
Database professionals who want to understand HNSW, IVF, similarity search, and vector search execution
IT professionals looking to apply Oracle AI Vector Search to enterprise search and basic RAG scenarios
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