Course CSE354
Title Natural Language Processing
Credits 3
Course Coordinator Niranjan Balasubramanian

Natural language processing techniques power many intelligent language based applications. This course will introduce basic language analysis tasks such as language modeling and syntactic analysis, as well as core applications such as text classification, information extraction, question answering, and machine translation. The course will cover relevant algorithms, machine learning solutions, and evaluation methodologies.

Prerequisite Prerequisites: CSE 316 or CSE 351; CSE or DAS major
Course Outcomes

1. Know how ambiguity, compositionality, and personal nature of language makes it difficult for computers to precisely represent and understand information in text.

2. Know how representations of smaller units (words) can be composed to form representations of larger units (sentences or documents) using deep learning.

3. Know how to use representations of text to build applications such as question answering, sentiment analysis, and machine translation.

4. Know the fundamentals of supervised machine learning and deep learning as well as how to evaluate, diagnose and fix issues in NLP applications.

Major Topics Covered in Course
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