About
Table of contents
About
This introductory course to Natural Language Processing (NLP) provides a comprehensive overview of the fundamental concepts, techniques, and applications in the field. Students will be equipped with essential skills for navigating the world of text data. Through a blend of theory and practical application, students will explore the fundamental concepts of NLP and its wide-ranging applications across industries. Using Python programming, you’ll learn to implement NLP tasks from basic text processing to advanced techniques, including sentiment analysis to discern emotions from text and topic modeling to uncover latent themes within large datasets. Additionally, you’ll explore emerging technologies such as generative AI and Large Language Models (LLMs) and their implications for NLP. By the end of this course, students will emerge with a solid understanding of NLP principles, proficiency in Python programming for NLP tasks, and the ability to apply these skills to address diverse NLP challenges.
Weekly Topic
Week 1: Intro of NLP
Week 2: Text as Data
Week 3: Word Embedding
Week 4: Sentiment Analysis
Week 5: Information Extraction
Week 6: Topic Modeling
Week 7: Large Language Models
Week 8: Generative AI
Resources
Lecture notes are available on this site. Course videos and additional learning resources are available at Purdue Brightspace.
Assignments
Assignments are available at Purdue Brightspace