This tutorial will provide an introduction to Large Language Models (LLMs) for interested researchers in the visualization (Vis) community. It will first motivate why LLM4Vis is an important area of research and how Large Language Models (LLMs) can be lever- aged to solve various NLP tasks for visualizations. We will delve into the basics of language models, covering model architectures, including the Transformer architecture, and discuss various train- ing methodologies, from pre-training to fine-tuning. We will then dive deeper into Large Language Models, elucidating their emergent abilities and practical applications in visualization tasks, including prompt engineering, instruction tuning, and model variations for processing text, tables, and images. In the final part, we will focus on applying LLMs for information visualization, covering an array of applications such as visual text analytics, natural language inter- faces, chart question answering, text generation, visual..