Large Language Models (LLMs) are AI systems that can understand and generate natural language across a wide range of domains and tasks. They have become increasingly popular and powerful in recent years, thanks to advances in deep learning, data availability, and computing power. However, LLMs have limitations such as hallucinations and may benefit from fine-tuning or other optimization techniques to improve performance for specific applications. This article will explain what fine-tuning is, how it works, why it is important, what are the distinct types of fine-tuning, and what are the best practices and challenges involved in fine-tuning LLMs for business applications.