Intro to Natural Langauge Processing (NLP)

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.

Course Learning Outcomes (LO):

By the end of this course, learners will be able to:
• LO1: Describe Natural Language Processing (NLP) and its applications (w1)
• LO2: Apply Python programming to Natural Language Processing tasks (w1-6)
• LO3: Implement text analysis to extract information from text data (w2, 3, 5)
• LO4: Create solutions for sentiment analysis problems (w4)
• LO5: Build solutions for topic modeling tasks (w6)
• LO6: Describe generative AI and Large Language Models (LLMs) and their use cases (w7, 8)