Practical Natural Language Processing with Python

Text data is everywhere, but turning raw language into structured, actionable insights requires the right toolkit. This text-based course guides you step-by-step through the essentials of processing and analyzing human language using Python. You will transition from understanding basic text manipulation to implementing modern Natural Language Processing (NLP) workflows. By the end of this course, you will have the confidence to clean messy text, extract critical patterns, and prepare textual data for machine learning models. What you'll learn: - Understand foundational NLP concepts, key terminology, and the text processing pipeline - Clean and preprocess raw text using tokenization, lemmatization, and stop-word removal - Extract key insights and patterns using regular expressions and feature engineering - Represent text numerically using vectorization techniques like TF-IDF and word embeddings - Explore modern NLP paradigms, including basic transformer concepts and prompt-based text classification - Build and evaluate foundational text classification models using Python libraries The course begins with core definitions and terminology before guiding you through hands-on text preprocessing workflows, feature extraction, and modern model implementation. This program is designed for beginners who have a basic understanding of Python programming, with no prior machine learning or NLP experience required. Start learning today and unlock the power of text analytics.