Course Overview
Vector databases have become a core component of modern AI systems, enabling semantic search, recommendation engines, and retrieval-augmented generation pipelines. By storing high-dimensional embeddings, vector databases allow applications to retrieve information based on meaning rather than keywords.
This mentor-led programme introduces the fundamental concepts behind vector search and embedding-based retrieval systems. Participants explore how embeddings are created, how vector similarity works, and how vector databases support scalable semantic search applications.
Through practical scenarios, learners implement simple vector search pipelines and integrate them with AI applications. By the end of the course, participants will understand how vector databases support production systems such as AI assistants, recommendation engines, and knowledge retrieval platforms.
Hands-On Learning
Build a semantic search prototype using embeddings and a vector database.
Mentor-Led Sessions
Mentor-led sessions exploring real-world vector search architectures and implementation scenarios.
Career-Ready Skills
Understand and implement vector search systems for AI applications.
Learning Outcomes
Design semantic search architectures using vectors
Analyse embedding strategies for AI retrieval
Implement vector indexing and similarity search
Evaluate retrieval relevance and search performance
Communicate vector search architecture decisions
Lead development of embedding-based AI features
Prerequisites
Basic understanding of databases or data systems
Familiarity with APIs or programming basics
Interest in AI or search technologies
Detailed Syllabus
Step-by-step learning journey from basics to professional practice
Topics Covered
- AI retrieval ecosystem overview
- Course tools and environment setup
- Responsible AI and data usage
- Introduction to embeddings and vector search
Skills You'll Gain
Master these in-demand skills through hands-on practice
Career Progression
A clear view of the roles this programme supports, what typically comes next, and where learners progress over time
Ways to Learn
Choose the learning format that works best for you and your team
Live Online
Instructor-Led Training
Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
- Live instructor interaction (real-time)
- Trainer-led walkthroughs and real examples
- Guided resources and session notes provided
- Structured Q&A and practical discussion
Price per person
Group enrolments and early planning options available.
All prices are exclusive of VAT where applicable. Group enrolments and custom packages available on request.
Prefer a Faster, Personalised Route into IT?
Not everyone learns best in a group. If you want focused guidance, faster clarity, and confidence you can use on the job, our 1-to-1 Fast-Track Training gives you private, mentor-led support tailored to your experience and goals.
"Many learners choose 1-to-1 when they want understanding, not memorisation."
Exam & Certification Information
Everything you need to know about the certification exams
Important Information
You will receive an Xcademia certificate of completion based on participation and successful completion of labs and scenario simulations.
Credential
Certificate of Completion
On successful completion of Vector Database Fundamentals, learners receive an Xcademia Certificate of Completion. This standalone certificate is issued directly by Xcademia and is aligned with globally recognised frameworks and best practices.
Frequently Asked Questions
Everything you need to know about this course
A vector database stores embeddings and allows similarity-based search to retrieve information based on meaning rather than keywords.
Ready to Start Your Learning Journey?
Take the next step in your professional development