This Natural Language Processing (NLP) course, inspired by Coursera lecture content from Coursera, provides a structured introduction to the key concepts and methods used in processing human language with artificial intelligence. The course is designed to guide learners step by step from basic ideas to practical NLP applications.
It begins with an introduction to NLP and explains the main approaches used in the field, helping learners understand how machines interpret and analyze text. The course also provides an overview of the learning structure and what topics will be covered in later weeks, giving a clear roadmap for progression.
You will explore important foundational topics such as linguistic knowledge in NLP and how language structure affects computational models. The course then moves into practical techniques like text preprocessing, where raw text is cleaned and prepared for analysis.
A key focus is feature extraction from text, where methods are used to convert language into numerical representations that machine learning models can process. Finally, the course introduces linear models for sentiment analysis, showing how AI can classify and understand opinions in text data.
This course is ideal for beginners who want a clear and organized introduction to NLP concepts combined with practical machine learning a
