Training Course in AI Search (GEO, AEO, and SGE)
This is a 5-day, hands-on training program designed to equip marketers, content strategists, SEO, and digital professionals with the foundational knowledge and practical skills to optimize for AI-powered search and answer engines like Google SGE, Gemini, Perplexity, and ChatGPT.
Course Overview
| Course Title | Training Course in AI Search (GEO, AEO, and SGE) |
| Organization | Tech For Development (T4D) |
| Venue | Tech For Development (T4D) Training Center along Tala Road, Runda, Nairobi |
| Duration | 5 days |
| Target Industries |
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| Target Job Roles |
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| Course Fees (face-to-face training) |
USD 1100/KES 75,000 (Exclusive of VAT) |
| Course Fees (virtual training) | USD 500/KES 55,000 (Exclusive of VAT) |
| Training Modes | Virtual and face-to-face training |
| Payment | Payment should be made to the Tech For Development (T4D) bank account on or before the start of the course |
| Accreditation | Upon successful completion of the training, participants will receive a Tech For Development Certificate of Course Completion |
Course Summary
This is a 5-day, hands-on training program designed to equip marketers, content strategists, SEO, and digital professionals with the foundational knowledge and practical skills to optimize for AI-powered search and answer engines like Google SGE, Gemini, Perplexity, and ChatGPT.
The course covers the functionality of language models (LLMs), including:
- Tokenization, which is the core unit of AI understanding
- How models generate text through next word prediction
- The science behind hallucinations and retrieval-augmented generation (RAG)
You will explore neural networks, unsupervised/self-supervised learning, supervised learning, and reinforcement learning with human feedback (RLHF).
These concepts have been framed within the context of AI search relevance and content visibility.
Who Should Attend This Course?
The course is ideal for:
- Digital Marketing Professionals
- SEO Content Creators and Copywriters
- Technical SEO Analysts
- AEO (Answer Engine Optimization) Consultants
- Data Scientists
- Machine Learning Engineers
- Web Developers
- Any other individual interested in AI search
Course Objectives
By the end of this 5-day training, participants will be able to:
- Understand the role of tokens in natural language processing and their impact on how search engines interpret queries and content
- Explain how large language models (LLMs) like GPT and BERT function, including next word prediction, attention mechanisms, and context windows
- Identify causes of AI hallucinations and explain their implications in AI-generated search results
- Describe the Retrieval-Augmented Generation (RAG) framework, including how external data improves LLM accuracy in search
- Define and apply Generative Engine Optimization (GEO) strategies to improve content visibility in AI-generated search environments like Google SGE
- Implement Answer Engine Optimization (AEO) by structuring content to directly answer user queries and improve retrieval relevance
- Utilize structured data and semantic markup (e.g., Schema.org) to support AEO and enhance content discoverability by AI
- Analyze and adapt content based on how AI search engines retrieve, rank, and summarize information
What are the Requirements for Taking this Course?
- Basic understanding of digital marketing and SEO
- General knowledge of how AI works
- Familiarity with content management systems (CMS) such as WordPress, Wix, and Webflow
- A laptop or desktop computer
What are the Training Approaches?
- Interactive Lectures
- Live Demonstrations
- Hands-on Exercises
- Group Discussions
- Prompt Engineering Practice
- Real-world Case Studies
- Knowledge Checks & Quizzes
- Collaborative Group Work
Course Modules
Course Outline
Module I: Foundations of AI Search
- What is a token? (word, sub word, character, BPE)
- Tokenization examples (OpenAI, HuggingFace)
- Token limits and context windows
- How tokens influence semantic matching for search relevance
- Google SGE’s need for precision in query interpretation
Practical Exercise:
- Tokenize a sample query and webpage
- Compare how AI search understands short vs. long queries
Module II: Generative Models & Language Behavior
- Next Word Prediction – How Large Language Models (LLMs) Think
- Statistical modeling: SoftMax and token probability
- Predictive generation vs. RAG (Retrieval-Augmented Generation)
- Completion vs. instruction-based models
- What is a hallucination in AI search?
- Why models hallucinate (lack of grounding, outdated info)
- Risks in search: Inaccurate answers in SGE results
Practical Exercise:
- Prompt a model with ambiguous vs. factual queries
- Analyze where hallucinations appear in AI-generated responses
Module III: Understanding Retrieval-Augmented Generation (RAG) in Search
- What is Retrieval-Augmented Generation?
- Combining LLMs with search/document retrieval
- Vector databases and semantic search
- How RAG Powers SGE, GEO, and AEO
- How Google SGE retrieves and summarizes web content
- Role of citations, grounding, and retrieval accuracy
- AEO content structuring to be “retrieval-friendly.”
- How GEO benefits from retrievable, semantically clear content
Practical Exercise:
- Explore a basic RAG demo using a query and documents
- Analyze a real SGE result: Identify retrieval vs. generation
Module IV: Training AI – How Language Models Learn
- Overview of Neural Networks – The Thinking Engine
- Forward pass, backpropagation, layers, and weights
- Types of Learning in AI Search - Unsupervised/Self-Supervised Learning, Supervised Learning, and Reinforcement Learning with Human Feedback (RLHF)
Practical Exercise:
- Identify supervised vs. unsupervised examples in AI search
- Explore how human feedback has changed AI answers over time
Module V: AI Search in Practice (GEO, AEO, and SGE)
- What is Google SGE, how does it work, and what impact does it have on traditional SEO?
- Bing Copilot Search, Perplexity, You.com
- How LLMs rank and cite content
- Definition and strategy shift from SEO
- Writing content for generative visibility
- Entity-based content structuring and topical authority
- Examples of GEO-friendly content
- Optimizing for direct answers (Zero-click search) - FAQ, How-To, schema markup
- How AI detects structured responses
- JSON-LD, Schema.org, and semantic HTML
Module VI: Aligning Content for SGE, GEO, and AEO
- SGE Content Criteria: Expertise, Clarity, Recency
- Tips for citation in AI snapshots
- Leveraging RAG concepts in content creation
Practical Exercise:
- Analyze a webpage and rewrite for GEO + AEO
- Test its performance in SGE and other AI search tools
Course Administration
Methodology
This instructor-led training course is delivered using a blended learning approach comprising presentations, guided practical sessions, web-based tutorials, and group work.
Accreditation
Participants will receive a Tech For Development Certificate of Course Completion.
Training Venue
Held at the Tech For Development Training Centre.
Accommodation & Airport Transfer
Arranged upon request.
Email: letstalk@techfordevelopment.com
Phone: (+254) 790 824 179
Tailor-Made
Customised training available.
Payment
Send proof of payment to letstalk@techfordevelopment.com.
