Free ebookIntroduction to Large Language Models (LLMs): How They Work and What They Can (and Can’t) Do

Course Description

Introduction to Large Language Models LLMs How They Work and What They Can and Can’t Do is a practical ebook course in Information Technology within the Artificial Intelligence subcategory. It helps you understand what LLMs generate, why they sometimes fail, and how to use them responsibly in real work. You will build clear mental models that improve your ability to choose the right AI approach, communicate requirements, and set realistic expectations with stakeholders.

You will learn how tokens shape what an LLM can read and produce, how context windows affect in session memory, and why responses can change based on phrasing and placement of information. The course explains embeddings and semantic similarity so you can connect LLMs to knowledge sources and retrieval systems, and it clarifies the difference between pretraining and fine tuning to help you interpret claims about model capabilities.

A core focus is reliability. You will understand why hallucinations happen, how to evaluate output quality, and how to assess risk in business and technical settings. You will explore when large language models are the right tool for drafting, summarizing, classifying, and assisting analysis, and when to avoid or constrain LLM use due to privacy, safety, compliance, or accuracy requirements.

To make learning immediately useful, the ebook guides you through practical prompting for better outcomes and designing grounded workflows that reduce errors by anchoring generation to trusted context. By the end, you will have sound expectations and habits for using generative AI effectively, whether you are a developer, analyst, manager, educator, or curious professional.

Start this course today and build a clear, responsible foundation for working with LLMs in modern AI projects.