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Cheat at Search with LLMs

  • up to 4 weeks
  • Intermediate

This course offers a practical approach for search teams to adopt LLMs to improve search. Learn how to drive relevant, profitable search results and see outcomes faster with your search engine.

  • LLM integration
  • Search engine optimization
  • Query understanding
  • Content understanding
  • Search relevance

Overview

In this course, you'll learn how to enhance your search engine's relevance using Large Language Models. You'll gain skills in query and content understanding, and learn to deploy LLMs in production efficiently. The course is designed to help you sidestep traditionally complex processes and achieve structured, well-formed queries, ultimately improving your team's search outcomes.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Professional Certification
    upon course completion
  • Full-time
    course format
  • Live classes
    delivered online

Who is this course for?

Search teams

Eager to evolve that crufty-old search engine towards a modern approach.

Search startups

Eager to get a fast start with a modern approach to search, sidestepping old, outdated practices.

Team leads and managers

Excited to organize their work in a way aligned with modern approaches to Relevant Search.

This course will help you increase your team's velocity in building relevant search applications using AI. You'll learn to sidestep complex processes with LLMs and connect with a community of search professionals. Ideal for search teams and startups looking to modernize their approach.

Pre-Requisites

1 / 3

  • Basic understanding of search engines

  • Familiarity with AI concepts

  • Interest in improving search relevance

What will you learn?

Week 1: Query corrections with LLMs
Learn how to correct queries using Large Language Models to improve search relevance.
Week 2: Zero shot query understanding with LLMs
Understand queries without prior examples using LLMs.
Week 2: Few shot query understanding
Learn to understand queries with minimal examples using LLMs.
Week 2: Content understanding
Gain insights into content understanding to enhance search relevance.
Week 3: Modeling similarity
Learn to model similarity in search queries and content.
Week 3: Two tower embedding models
Explore two tower embedding models for improved search relevance.
Week 3: Hybrid Search
Combine lexical and vector retrieval for hybrid search systems.
Week 4: LLM as a judge
Use LLMs to evaluate and rank search results.
Week 4: LLM as a judge/pairwise ranker
Implement LLMs as pairwise rankers to enhance search relevance.

Meet your instructor

  • Doug Turnbull

    Principal AI Engineer in Search, Daydream

    Doug Turnbull is an expert in search technology and relevance engineering, currently serving as Principal Engineer at Daydream. He has led machine-learning-driven search initiatives at Reddit and Shopify, and co-authored the influential book Relevant Search.

Upcoming cohorts

  • Dates

    Feb 2 — Feb 27, 2026

$1,300