Natural Language Processing (NLP) empowers computers to understand, interpret, and generate human language. It bridges the communication gap between humans and machines, enabling applications like chatbots, machine translation, and sentiment analysis. NLP tackles diverse challenges, from deciphering word meanings (semantics) and sentence structure (syntax) to understanding context and intent. Core NLP tasks include tokenization, part-of-speech tagging, named entity recognition, and coreference resolution. Modern NLP leverages powerful language models, including large language models (LLMs) like BERT and GPT, trained on massive datasets. These models capture complex linguistic patterns, driving advancements in conversational AI, text summarization, and question answering. NLP continues to evolve, pushing the boundaries of human-computer interaction.