Applied NLP and Generative AI Applications in Python

In a world driven by textual data, understanding how to extract meaning and generate human-like text is a critical skill for modern developers. This course provides a clear pathway to mastering natural language processing and generative AI using Python. You will transition from understanding basic text processing to deploying intelligent, AI-powered applications. Through written explanations and clear code examples, you will learn how to clean text, vectorize data, classify documents, and leverage generative models to solve real-world problems. What you'll learn: Understand foundational NLP concepts, text preprocessing, and tokenization techniques. Vectorize text data using modern embedding models to capture semantic meaning. Classify, summarize, and extract key information from unstructured text documents. Implement generative AI patterns, including basic retrieval-augmented generation (RAG). Apply prompt engineering principles to guide large language models effectively. Deploy your NLP applications as functional APIs for real-world integration. The course starts with key terminology and foundational text processing concepts before moving into advanced vectorization, classification, and generative AI patterns. You will follow a structured learning path that builds your confidence step-by-step through practical written exercises. This course is designed for beginners, Python developers, and data enthusiasts looking to enter the field of AI without needing prior background in machine learning. Start reading today to build your own intelligent text applications and harness the power of generative AI.