Python for Linguistics: Analyzing Text with NLTK and XML

Language data is expanding rapidly, but manual analysis limits the scope of what you can discover. This course introduces you to computational linguistics using Python, showing you how to automate text processing and uncover deep linguistic patterns. By learning to program, you can scale your research from analyzing single documents to entire libraries. You will transition from manual text examination to automated linguistic analysis. Through clear, written explanations and practical code examples, you will learn to clean raw text, extract grammatical structures, and work with structured XML databases. What you'll learn: - Understand foundational computational linguistics concepts and key text-processing terminology. - Analyze raw text corpora using NLTK to perform tokenization, lemmatization, and part-of-speech tagging. - Parse, modify, and search structured XML linguistic databases using pythonic XML tools. - Apply modern Python practices, including type hints, to write clean and reproducible research scripts. - Extract specific grammatical patterns and statistical insights from unstructured text. - Save and export processed linguistic datasets into clean formats for academic or professional research. This course begins with core definitions and basic Python concepts before progressing to practical text-manipulation techniques. You will read through clear explanations of linguistic algorithms and practice constructing your own text-analysis workflows step-by-step. This course is specifically designed for linguists, humanities researchers, and language enthusiasts who want to learn programming from scratch. No prior coding experience or advanced mathematics background is required. Begin your journey into computational linguistics and transform how you analyze language data today.