CS 461 - Computational Linguistics

5 CR

This course offers a thorough introduction to both the theoretical and practical aspects of natural language processing (NLP). Students will explore crucial topics such as text preprocessing and semantic analysis while applying machine learning to real-world NLP challenges. Overall, the course is designed to prepare students for advanced computer science studies and careers in tech-driven sectors.

Prerequisite(s): CS 300 with C or above

Course Outcomes

Explain fundamental principles and theories of natural language processing.
Demonstrate understanding of text preprocessing techniques like tokenization, stemming, and lemmatization
Apply statistical language models (e.g., n-gram, Markov models) to real-world datasets.
Critically analyze text data using methods such as sentiment analysis, named entity recognition, and topic modeling.
Evaluate and select appropriate machine learning algorithms for various NLP tasks.
Design and build NLP applications, integrating knowledge of algorithms, models, and tools.

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