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Curriculum reference · Free · Updated 2026

AI SEO Course Syllabus: 8 Modules & 34 Lessons

The AISEOCourse.academy curriculum contains 8 modules and 34 lessons covering traditional SEO, AI search, GEO, AEO, citation analysis, content retrieval, entities, off-page authority, measurement and experimentation, with the practical outcome of every lesson.

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Course facts

Free AI SEO Course 2026. 8 modules · 34 lessons · Self-paced · Beginner to advanced · Free · No account required · Certificate: not currently offered.

Format: written lessons with stated objectives, worked examples and practical exercises you run against your own site and query set. Every lesson ends with a key principle and links its primary sources. Platform facts are sourced to Google's own documentation; the teaching priority is implementation over terminology.

This page is the curriculum reference. For the self-directed route through it, read the learning roadmap; experienced SEOs can take the fast track instead.

What you will be able to do

By the end of the syllabus:

Foundations

Explain how search engines crawl, index and rank pages, and distinguish traditional results from AI-generated search experiences such as Google AI Overviews and AI Mode.

Research

Build a commercial query universe, run repeatable AI-search query sets and analyse which domains and URLs receive citations.

Content and entities

Write clearer, self-contained answer passages, improve entity naming and page structure, create genuine information gain and audit brand and entity consistency.

Authority and measurement

Evaluate links, mentions and third-party corroboration, identify external citation opportunities, track mentions, citations and source share, and connect visibility to conversions.

Testing

Run controlled SEO experiments and automate repeatable work without automating judgement.

The syllabus is not built around memorising GEO terminology. It is built around producing work you can use on a real website.

Module 1 · 6 lessons · Prerequisites: none

SEO Foundations

How search engines work, search intent, crawl and index, architecture, internal links, on-page optimisation, backlinks and authority. The foundation everything else extends.

  1. 1.1 How Search Engines Work: Crawl, Index, Rank
    Practical outcome: check whether an important page is indexed and identify whether its bottleneck sits in crawling, indexing or ranking.
  2. 1.2 Search Intent: The Reason Behind the Query
    Practical outcome: classify target queries by intent before deciding what to create.
  3. 1.3 Crawlability and Indexability
    Practical outcome: identify technical barriers preventing an important page from being crawled or indexed.
  4. 1.4 Site Architecture and Internal Links
    Practical outcome: map a topic cluster and strengthen the internal path to its commercial page.
  5. 1.5 On-Page Optimisation
    Practical outcome: audit and improve one page against its actual search intent.
  6. 1.6 Backlinks and Authority
    Practical outcome: assess the authority gap around one commercially important page.

Module 2 · 4 lessons · Prerequisites: Module 1 recommended

Understanding AI Search

AI Overviews, AI Mode, how language models retrieve and select sources, citations, eligibility and query fan-out.

  1. 2.1 Google AI Overviews and AI Mode
    Practical outcome: record which AI-search surfaces appear across your own queries and which domains they cite.
  2. 2.2 How Language Models Retrieve and Choose Sources
    Practical outcome: treat pages as sources containing retrievable information, not only URLs competing for rankings.
  3. 2.3 AI Citations and Source Eligibility
    Practical outcome: distinguish ranking, mention and citation visibility in your own tracking.
  4. 2.4 Query Fan-Out and Answer Variability
    Practical outcome: measure AI visibility with repeated runs instead of one prompt and one screenshot.

Module 3 · 4 lessons · Prerequisites: Module 2

AI SEO & GEO Research

Query universes, prompt research, running a repeatable query set, citation-source analysis and competitor visibility.

  1. 3.1 Query Universes and Prompts
    Practical outcome: build a commercial query universe of 20 to 30 questions.
  2. 3.2 Running a Repeatable Query Set
    Practical outcome: establish a repeatable AI visibility baseline.
  3. 3.3 Citation Source Analysis
    Practical outcome: create a citation-source log and identify recurring domains.
  4. 3.4 Tracking Competitor Visibility
    Practical outcome: identify where competitors have AI-search visibility that you lack.

Module 4 · 4 lessons · Prerequisites: Module 3 recommended

Content & Retrieval

Answer passages, entity naming, information gain, evidence, original data, content architecture and freshness.

  1. 4.1 Answer Passages and Extractable Content
    Practical outcome: rewrite buried answers into clear, independently understandable passages.
  2. 4.2 Entity Naming and Descriptive Headings
    Practical outcome: make the important entities and topics on a page unambiguous.
  3. 4.3 Information Gain, Evidence and Original Data
    Practical outcome: find where an important page can add information competitors do not provide.
  4. 4.4 Content Architecture, Freshness and Internal Links
    Practical outcome: strengthen a topic without creating cannibalisation.

Module 5 · 4 lessons · Prerequisites: Module 4 recommended

Entity & Brand Authority

Entity consistency, authorship, third-party corroboration and structured data where appropriate.

  1. 5.1 Entity Consistency Across the Web
    Practical outcome: run an entity consistency audit.
  2. 5.2 Authorship and Demonstrated Expertise
    Practical outcome: connect important content to the people responsible for it.
  3. 5.3 Third-Party Corroboration and Reputation
    Practical outcome: identify brand claims that lack independent corroboration.
  4. 5.4 Structured Data for Entities
    Practical outcome: choose appropriate structured data without treating markup as a GEO switch.

Module 6 · 4 lessons · Prerequisites: Modules 2 and 3

Off-Page AI SEO

Links versus mentions, publications, communities, comparison sites and citation opportunities.

  1. 6.1 Links Versus Mentions in AI Search
    Practical outcome: audit where your brand is linked, cited or only mentioned.
  2. 6.2 Earning Relevant Publications and Coverage
    Practical outcome: identify realistic publications where your expertise or data fits.
  3. 6.3 Communities, Forums and Comparison Sites
    Practical outcome: map the third-party source types that recur in your market.
  4. 6.4 Finding and Prioritising Citation Opportunities
    Practical outcome: build a prioritised source-opportunity list.

Module 7 · 4 lessons · Prerequisites: Module 3

Measurement

Metrics that still matter, AI mention and citation tracking, source share and tying visibility to conversions.

  1. 7.1 Metrics That Still Matter
    Practical outcome: define a measurement set covering traditional and AI search.
  2. 7.2 Tracking AI Mentions and Citations
    Practical outcome: build a repeatable AI mention and citation tracker.
  3. 7.3 Source Share and Competitor Benchmarks
    Practical outcome: turn citation observations into comparable competitor benchmarks.
  4. 7.4 Tying AI Visibility to Conversions
    Practical outcome: connect AI visibility to branded search, referrals, leads and revenue.

Module 8 · 4 lessons · Prerequisites: Modules 1 to 7

Testing & Scaling

Experiments, automation, repeatable workflows and keeping current as AI search changes.

  1. 8.1 Running SEO Experiments You Can Trust
    Practical outcome: run an experiment whose result can inform the next decision.
  2. 8.2 Automation Without Nonsense
    Practical outcome: identify one repetitive AI SEO workflow worth automating.
  3. 8.3 Building Repeatable Workflows
    Practical outcome: turn a successful process into a repeatable workflow.
  4. 8.4 Keeping Current as AI Search Changes
    Practical outcome: maintain an evidence-based update process.

GEO, AEO and AI citations in the syllabus

The three questions every prospective student asks, answered from the module map above.

GEO

Covered as a workflow, not an acronym lesson: Module 2 explains AI search, Module 3 researches queries, citations and competitors, Module 4 improves retrievability, Module 5 entities, Module 6 external sources, Module 7 measurement and Module 8 testing. Already know SEO? Start at Module 2 or 3.

AEO

Answer Engine Optimisation skills appear throughout: search intent, AI answers, answer passages, entity naming, descriptive headings, structured information and citation measurement, particularly in Modules 2 and 4.

AI citations

Introduced in Module 2 (eligibility), researched in Module 3 (query sets, source analysis, competitors), influenced through Modules 4 to 6 (retrieval, entities, off-page sources) and measured in Module 7.

Google AI Overviews and AI Mode have a dedicated lesson: 2.1 Google AI Overviews and AI Mode.

Working on citations right now? The standalone AI Citations guide covers the full pipeline in one place.

What you finish with

Complete the Workbench exercises rather than only reading, and the course produces working assets:

Query universe

A stable set of commercially relevant questions and prompts.

AI visibility baseline

A repeatable record of where your brand and competitors appear.

Citation-source log

Which domains and URLs are being used as sources, and how often.

Entity record

A canonical set of facts about your organisation and related entities.

Retrieval improvements

Important pages rewritten around clearer answers, entities and evidence.

Off-page opportunity map

A prioritised list of publications, communities and comparison pages.

Measurement framework

Traditional, AI visibility and conversion metrics tracked separately but connected.

Experiment log

What you changed, why, and what happened afterwards.

That is considerably more useful than a completion badge in a downloads folder.

Syllabus FAQ

The questions people ask before starting.

How many modules and lessons are in the course?

The curriculum contains 8 modules and 34 lessons: six in SEO Foundations and four in each of the remaining seven modules.

Is the course free?

Yes. The complete course is free, self-paced and available without an account or paywall.

Do I need SEO experience to start?

No. Beginners start with Module 1. Experienced SEO professionals can start with Module 2, and practitioners already comfortable with AI-search mechanics can start with Module 3.

Does the syllabus cover GEO?

Yes. GEO research begins in Module 3 and connects to retrieval, entities, off-page authority, measurement and testing throughout Modules 4 to 8.

Does the course cover AEO?

Yes. AEO-related skills appear throughout the syllabus, particularly search intent, AI answers, answer passages, entity naming, retrieval and structured information.

Does the course cover AI citations?

Yes. AI citations are introduced in Module 2, researched in Module 3, influenced through Modules 4 to 6 and measured in Module 7.

Does the course cover Google AI Overviews and AI Mode?

Yes. Lesson 2.1 is dedicated to Google AI Overviews and AI Mode, including how the experiences differ, how sources are presented and what Google's documentation says about eligibility.

Does the course include practical exercises?

Yes. Every lesson ends with a Workbench exercise applied to your own site or query set, so the course produces working assets rather than watch-time.

Does the course issue a certificate?

No. AISEOCourse.academy does not currently issue a certificate. The course is designed around practical implementation rather than credential completion.

Start the syllabus

You now know exactly what is in the course. Work through it in order, or jump to the module that matches your gap.

Start Module 1 · SEO Foundations →

Already an experienced SEO? Start with Module 2 · Understanding AI Search →

When you want to compare the wider training market instead, AISEOCourse.co publishes the independent AI SEO courses comparison and the AI SEO course market data.