Tokens & Chunking Explained (GenAI Basics You MUST Know for AWS Exams)

Описание: Welcome to the first lesson in the Generative AI Concepts module, where we break down tokens, chunking, and context windows — three core ideas you must understand to work with large language models and pass AWS AI–focused exams.

In this video, you’ll learn:
✔ What tokens are and how LLMs understand text
✔ How tokenization breaks words into meaningful units
✔ What a context window is and why bigger context = better output (but higher cost)
✔ Why chunking is required when working with large documents
✔ How tokens and chunking improve performance, retrieval, and scalability
✔ Key AWS exam takeaways for Cloud Practitioner, AI Practitioner, and Solutions Architect

These concepts are foundational for:

Generative AI

LLMs

Retrieval-Augmented Generation (RAG)

AWS Bedrock & AI services

If you’re learning cloud + AI, preparing for an AWS certification, or just want a clear mental model of how GenAI works under the hood, this lesson is for you.

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