3 credits
Spring 2026 Distance Learning
This course provides a comprehensive overview of the fundamental concepts, techniques, and applications in the field of natural language processing. Using Python programming, students will 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, students will 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.
Learning Outcomes1Describe Natural Language Processing (NLP) and its applications.
2Apply Python programming to Natural Language Processing tasks.
3Implement text analysis to extract information from text data.
4Create solutions for sentiment analysis problems.
5Build solutions for topic modeling tasks.
6Describe generative AI and Large Language Models (LLMs) and their use cases.
Restrictions
made by Purdue students.