"Introduction to Language Models (LLMs)" provides an overview of the fundamental concepts and principles behind language models, which are algorithms designed to understand and generate human language. In this topic, learners delve into the structure and functionality of LLMs, exploring how they process and analyze text data to predict and generate coherent sentences. Key areas covered include the architecture of LLMs, such as recurrent neural networks (RNNs) and transformer models, as well as the training process involving large datasets. Additionally, learners examine the applications of LLMs across various domains, including natural language processing (NLP), machine translation, text generation, and sentiment analysis. Through this introductory exploration, learners gain a foundational understanding of LLMs and their significance in advancing language-related tasks in artificial intelligence (AI) and machine learning (ML) fields.