Awesome Search KG

Courses

4 min read

Courses

Courses and structured training for learning search and information retrieval — from free introductions to paid cohort-based programs. Companion to the Books reading list and the How to Start a Career in Search learning path.

Cohort-Based / Practitioner Training

Cheat at Search Essentials

Instructor: Doug Turnbull (led search at Reddit, Shopify, Wikipedia; author of AI-Powered Search and Relevant Search)

A free, beginner-friendly introduction to core retrieval concepts — an “ELI5” overview of how modern search works.

  • Format: 3 live virtual (Zoom) sessions with Q&A, ~3 hours total; recordings provided
  • Dates: May 8–14, 2026
  • Price: Free
  • Covers: BM25 and lexical retrieval · Embeddings and vector databases · Semantic Search vs token matching · Search Evaluation metrics (NDCG) and their limitations · when embeddings complement vs replace lexical techniques

🔗 https://maven.com/lls/5c240b

Best as a first structured exposure before tackling the concepts in depth.

AI-Powered Search: Modern Retrieval for Humans & Agents

Instructors: Trey Grainger (Founder, Searchkernel; author of AI-Powered Search) and Doug Turnbull (co-author of AI-Powered Search and Relevant Search)

The advanced, applied counterpart — building production AI search and retrieval systems. The cohort version of the AI-Powered Search book (see Books).

  • Format: 4-week live cohort (4–8 hrs/week): two 1.5-hr instructor sessions weekly, guest lectures, labs, optional office hours
  • Dates: July 1–31, 2026
  • Price: $1,950 USD
  • Audience: AI engineers working on search/ranking, search practitioners pursuing systematic relevance gains, technical leaders planning search experiments
  • Covers: Agentic Search loops · RAG optimization · query intent analysis · Bi-Encoder vs Cross-Encoder · matrix factorization · Learning to Rank (LambdaMART) · semantic caching · Click Models · active learning · feature engineering for production · Hybrid Search and multimodal approaches

🔗 https://maven.com/search-school/ai-powered-search

The natural next step after Cheat at Search Essentials or the foundational reading in Books.

Instructors: Trey Grainger and Doug Turnbull (authors of AI-Powered Search), with guests Kevin Butler (Sr. Search & AI Engineer, KMW Technology), Radu Gheorghe (Vespa), Jon Handler (OpenSearch at AWS), and Matt Overstreet (PM, IBM OpenSearch).

A free, multi-instructor survey of the cutting edge of AI search — broader and more advanced than the two courses above, drawing on practitioners across the ecosystem.

  • Format: 10 live virtual (Zoom) sessions with Q&A, ~10 hours total
  • Dates: June 15–30, 2026
  • Price: Free
  • Covers: Agentic Search · adaptive relevance pipelines · control vectors · PageIndex · modern RAG · scaling vector search for production · LLM as Judge · Late Interaction

🔗 https://maven.com/lls/f48679

Good breadth-first exposure to where the field is heading; pairs well with the hands-on depth of the paid cohort.

University Courses & MOOCs

Freely available academic material, good for rigor:

  • Stanford CS276 / CMU 11-642 — Search Engines — university IR course materials available online
  • Coursera — Text Retrieval and Search Engines (UIUC, ChengXiang Zhai) — auditable for free
  • Introduction to Information Retrieval (Manning, Raghavan, Schütze) — the standard text doubles as a self-study course; free online (see Books)

Vendor & Hands-On Academies

Free, practical, product-flavored intros — good for the tools step of the learning path:

  • OpenSource Connections — Think Like a Relevance Engineer (TLRE) — the practitioner-standard relevance training (OpenSource Connections)
  • Vector-DB academies — Weaviate, Qdrant, and Pinecone each publish free hands-on courses
  • DeepLearning.AI short courses — short, free modules on embeddings, RAG, and retrieval

Course offerings and dates change. Verify current availability before enrolling.

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