Unleashing Search Engines Potential with RAG
Training Program: Unleashing Search Engines Potential with RAG
Duration
1 day
price
500 USD / person
Location
Via Video Conference
Satisfaction Rate: ★★★★½ 4.5/5
Objectives
This training equips developers and search engine maintainers with the skills to enhance search engines by implementing a Retrieval Augmented Generation (RAG) solution.
✔ Combine the power of Large Language Models (LLMs) with vector search
✔ Improve search relevance, precision, and context-awareness
✔ Understand and implement RAG-based conversational AI solutions
By the end of the training, participants will be able to integrate RAG into search engines to provide more intelligent and context-aware results.
Audience
This course is designed for:
✔ Software developers
✔ Search engine maintainers
✔ Data engineers
A basic understanding of software development will help participants get the most out of this training.
All our courses are accessible to people with disabilities.
Curriculum
- Introduction to Search Engines
- Understanding the search ecosystem
- Search engine architecture
- Lucene-based search vs. vector search
- Introduction to LLMs & Prompt Engineering
- A brief history of Large Language Models (LLMs)
- Exploring the LLM ecosystem
- Understanding the limitations of LLMs
- Crafting effective prompts for better search responses
- Understanding the Structure of a RAG System
- RAG system architecture
- Key tools and frameworks
- Benefits of RAG in search applications
- Five Steps to Creating a RAG Solution
- Building a Chat Service
- Extracting embeddings for efficient search
- Understanding user queries for relevance
- Creating effective prompts
- Enabling AI-driven conversational behavior
Upcoming Sessions
✔ Tuesday, 18th November 2025
✔ Tuesday, 16th December 2025
✔ Tuesday, 17th February 2026
✔ Tuesday, 21st April 2026
✔ Tuesday, 26th May 2026
✔ Wednesday, 16th September 2026
- On-Demand Sessions Available – Custom scheduling upon request.
- Registration closes 48 hours before each session starts.
Prerequisites
✔ Basic knowledge of HTTP & REST
✔ Basic programming skills
✔ Laptop with Java 17 (minimum required)
✔ IDE and command-line terminal
Teaching Method
- 40% Presentation & Demonstrations
- 40% Hands-on Labs
- 20% Q&A & Discussions
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