Rohmate Learn · AI Search
Understand AI Search.From Retrieval to Recommendation.
A practical course on how AI-powered search and discovery systems retrieve, evaluate, ground and generate answers, and how businesses can build durable visibility across this changing ecosystem.
20
Lessons
5+ Hours
Learning
100%
Free
1
Published Lesson
Why This Course
Discovery is becoming an answer-generation system.
Traditional search usually helps people find documents, pages and products. AI-powered search can go further by retrieving information, interpreting it and generating a response directly for the user.
That changes the visibility problem. It is no longer enough to think only about where a page ranks. Digital teams increasingly need to understand how information is retrieved, interpreted, selected as evidence and incorporated into generated answers.
This course explains the systems behind that process, including language models, retrieval, embeddings, vector search, RAG, grounding, citations, entities and the wider AI discovery ecosystem.
The goal is not to learn tricks for individual AI platforms. It is to understand the durable principles behind AI-mediated discovery and apply them responsibly.
Learning Outcomes
What You'll Learn
Understand how AI-powered discovery systems retrieve information, evaluate evidence, generate answers and shape visibility across search, assistants and emerging agentic experiences.
Course Curriculum
Learn step by step
Work through the lessons in sequence, complete each knowledge check and track your progress toward the final assessment.
Your Progress
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Lesson 1
PlannedAI Search: From Ranked Results to Generated Answers
Understanding AI Search
Lesson 2
Coming NextLLMs for Search: Models, Context and Their Limits
Understanding AI Search
Lesson 3
PlannedInside the AI Search Pipeline: From Query to Answer
Understanding AI Search
Lesson 4
PlannedEmbeddings, Vector Search and Hybrid Retrieval
Understanding AI Search
Lesson 5
PlannedRetrieval-Augmented Generation: How RAG Works
Retrieval, Grounding and Reliable Answers
Lesson 6
PlannedSource Selection, Citations and Provenance
Retrieval, Grounding and Reliable Answers
Lesson 7
PlannedEntities, Relationships and Knowledge Graphs
Retrieval, Grounding and Reliable Answers
Lesson 8
PlannedHallucinations, Freshness and Answer Reliability
Retrieval, Grounding and Reliable Answers
Lesson 9
PlannedContent Architecture for Retrieval
Designing Information for AI Discovery
Lesson 10
PlannedInformation Gain, Evidence and Original Value
Designing Information for AI Discovery
Lesson 11
PlannedMachine-Readable Meaning: Structured Data, Metadata and Feeds
Designing Information for AI Discovery
Lesson 12
PlannedAEO and GEO: Scope, Evidence and Practical Application
Designing Information for AI Discovery
Lesson 13
PlannedAuthority, Trust and Brand Entity Visibility
AI Discovery Ecosystem
Lesson 14
PlannedMultimodal AI Discovery: Images, Video, Voice and Beyond
AI Discovery Ecosystem
Lesson 15
PlannedAI Commerce and Product Discovery
AI Discovery Ecosystem
Lesson 16
PlannedLocal and International AI Discovery
AI Discovery Ecosystem
Lesson 17
PlannedMeasuring AI Search Visibility
Measurement, Agents and Strategy
Lesson 18
PlannedPrompt Variation and AI Search Testing
Measurement, Agents and Strategy
Lesson 19
PlannedAgentic Search and the Rise of AI Agents
Measurement, Agents and Strategy
Lesson 20
PlannedBuilding a Future-Proof AI Search Strategy
Measurement, Agents and Strategy
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