Cheat at Search with LLMs

New
·

4 Weeks

·

Cohort-based Course

Vibe-code your way to Relevant Search

This course is popular

10 people enrolled last week.

Previously at

Shopify.com
Reddit
OpenSource Connections
Wikipedia
LexisNexis

Course overview

Practical approach for search teams to adopt LLMs to improve search

Achievable, Relevant Search without the PhD


Great query and document understanding once took months of dedicated expertise to see results. With AI, you can see wins within weeks or days. Learn how to cut to the heart of your user's search problems, driving relevant, profitable search results.

Who is this course for

01

Search teams eager to evolve that crufty-old search engine towards a modern approach

02

Search startups eager to get a fast start with a modern approach to search, sidestepping old, outdated practices

03

Team leads and managers excited to organize their work in a way aligned with modern approaches to Relevant Search

What you’ll get out of this course

Increase team velocity

Help your understaffed search team see better outcomes faster with your search engine

Cheat at search with LLMs

Sidestep traditionally complex query and content enrichment with Large Language Models

Make the unstructured, structured

Learn how there's no longer such a thing as "unstructured search". Turn any piece of query into a structured, well-formed query to your search backend

Make it a reality in production

Kick the theoretical to the curb. Deploying LLMs to production has gotten easier and easier. Smaller/local LLMs smarter. Do it all without a big OpenAI bill.

What’s included

Doug Turnbull

Live sessions

Learn directly from Doug Turnbull in a real-time, interactive format.

Lifetime access

Go back to course content and recordings whenever you need to.

Community of peers

Stay accountable and share insights with like-minded professionals.

Certificate of completion

Share your new skills with your employer or on LinkedIn.

Maven Guarantee

This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.

Course syllabus

Week 1

Jul 1—Jul 6

    Jul

    1

    Optional: Pre class help

    Tue 7/14:30 PM—5:30 PM (UTC)
    Optional

    Jul

    3

    Lesson 1 - Query corrections with LLMs

    Thu 7/34:30 PM—5:30 PM (UTC)

Week 2

Jul 7—Jul 13

    Jul

    7

    Lesson 2 - Zero shot query understanding with LLMs

    Mon 7/74:30 PM—5:30 PM (UTC)

    Jul

    9

    Lesson 3 - Few shot query understanding

    Wed 7/94:30 PM—5:30 PM (UTC)

    Jul

    10

    Guest Speaker - Daniel Tunkenlang - Modeling Queries as Bags of Documents

    Thu 7/104:30 PM—5:30 PM (UTC)
    Optional

    Jul

    11

    Lesson 4 - Content understanding

    Fri 7/114:30 PM—5:30 PM (UTC)

Week 3

Jul 14—Jul 20

    Jul

    14

    Lesson 5 - Modeling similarity

    Mon 7/144:30 PM—5:30 PM (UTC)

    Jul

    16

    Lesson 6 - Two tower embedding models

    Wed 7/164:30 PM—5:30 PM (UTC)

    Jul

    18

    Lesson 7 - Hybrid Search

    Fri 7/184:30 PM—5:30 PM (UTC)

Week 4

Jul 21—Jul 26

    Jul

    21

    Lesson 8 - LLM as a judge

    Mon 7/214:30 PM—5:30 PM (UTC)

    Jul

    22

    Guest Speaker - René Kriegler - Quepid - an LLM as a judge tool for search

    Tue 7/224:30 PM—5:30 PM (UTC)
    Optional

    Jul

    23

    Lesson 9 - LLM as a judge/pairwise ranker

    Wed 7/234:30 PM—5:30 PM (UTC)

What people are saying

        Doug was to me and our team a mentor, the resident expert in search matters. He has a rare combination of humility, brilliance, and friendliness
Bertrand Rigaldies

Bertrand Rigaldies

Principal Search Engineer - Shipt
        Taking a course from Doug is one of the best career moves you can make. He is a veritable powerhouse in Search Relevance
Audrey Lorberfeld

Audrey Lorberfeld

Software Engineer in Code Search - Sourcegraph

Meet your instructor

Doug Turnbull

Doug Turnbull

Principal AI Engineer in Search

Doug Turnbull is an expert in search technology and relevance engineering, currently serving as Principal Engineer at Daydream, where he builds hybrid search systems combining lexical and vector retrieval, and develops LLM-driven quality programs for e-commerce search. Previously, he led machine-learning-driven search initiatives at Reddit, significantly improving search relevance through Learning to Rank methods. Doug also advanced e-commerce search at Shopify and served as CTO at OpenSource Connections. He co-authored the influential book Relevant Search (Manning, 2016) and created popular open-source tools, including Quepid and the Elasticsearch Learning to Rank plugin. He regularly speaks at industry conferences, making search relevance accessible to engineers.

A pattern of wavy dots

Join an upcoming cohort

Cheat at Search with LLMs

Cohort 1

$1,100

Dates

July 1—26, 2025

Payment Deadline

June 30, 2025

October 2025

$1,100

Dates

Oct 6—31, 2025

Payment Deadline

Oct 5, 2025
Get reimbursed

Course schedule

4-6 hours per week

  • Mondays

    12:30 PM ET

    Introduce this week's topic

  • Weekly projects

    2 hours per week

    Hands on projects making practical, LLM-driven search a reality

  • Wednesdays

    12:30 PT

    Second lesson of the week

  • Fridays

    12:30PM ET

    Closing this week's topic

Search gets better when we work together

Search gets better when we work together

Faster search development

Increase your team's pace of building relevant search applications using AI / Large Language Models

Own your search

Learn how to think about search problems in a way that matches to YOUR user's expectations

Grow your search network

Get connected to the broader search community, get to know others in your space solving challenging search problems

Frequently Asked Questions

A pattern of wavy dots

Join an upcoming cohort

Cheat at Search with LLMs

Cohort 1

$1,100

Dates

July 1—26, 2025

Payment Deadline

June 30, 2025

October 2025

$1,100

Dates

Oct 6—31, 2025

Payment Deadline

Oct 5, 2025
Get reimbursed

$1,100

4 Weeks