Introduction to Natural Language Processing

Language is the primary way humans communicate, but teaching computers to understand our natural speech and text has always been a major challenge. This course provides a clear, conceptual introduction to how modern machines process, analyze, and generate human language. You will transition from understanding core linguistic rules to working with the latest machine learning models that power search engines, chatbots, and translation tools. What you'll learn: Understand core NLP concepts including tokenization, lemmatization, and part-of-speech tagging; Build basic text classifiers to perform sentiment analysis on real-world datasets; Apply vector representation techniques to convert raw text into meaningful computer-readable data; Explore language modeling fundamentals and how modern transformer architectures process sequence data; Implement basic prompt engineering techniques to interact with pre-trained large language models. The course starts with essential linguistic terminology and foundational text-preprocessing techniques before guiding you step-by-step through building simple classification models and working with modern transformer-based concepts. This text-based program is designed specifically for beginners with basic Python knowledge who want to enter the exciting field of language technology. Start reading today and build a solid foundation in the technology shaping the future of human-computer interaction.