{"id":4,"date":"2025-06-04T19:51:30","date_gmt":"2025-06-04T19:51:30","guid":{"rendered":"https:\/\/courses.cs.colostate.edu\/cs003\/?page_id=4"},"modified":"2025-08-21T15:23:18","modified_gmt":"2025-08-21T21:23:18","slug":"cs-001","status":"publish","type":"page","link":"https:\/\/courses.cs.colostate.edu\/cs542\/","title":{"rendered":"CS542"},"content":{"rendered":"\n

Natural Language Processing<\/h3>\n\n\n\n

With the proliferation of language technologies in use, from smartphones in our pockets to analytic and predictive algorithms in use by individual, institution, private sector, and state actors, it is critical that students in computer science be familiar with the purposes for which linguistic data is used, and the algorithm and techniques used to process linguistic data computationally. This course blends computer science and linguistics to teach students the foundational and cutting-edge techniques in NLP, their various use cases, achievements and pitfalls, and the relationship between language processing techniques and methods within other subdisciplines within machine learning, artificial intelligence, and data science. <\/p>\n\n\n\n

In this course, students will learn to:<\/p>\n\n\n\n

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  1. identify ethical and societal issues present in NLP use cases.<\/li>\n\n\n\n
  2. define NLP use cases and commonly-used methods;<\/li>\n\n\n\n
  3. identify useful NLP techniques based on data and task;<\/li>\n\n\n\n
  4. describe the relationship between raw data, annotated data, and NLP tasks;<\/li>\n\n\n\n
  5. design, implement, and evaluate experiments in NLP use cases;<\/li>\n\n\n\n
  6. critically read and discuss NLP literature;<\/li>\n\n\n\n
  7. connect achievements and failures in NLP to issues in data and algorithmic implementation;<\/li>\n<\/ol>\n\n\n\n

    2025 Fall Semester Details<\/h4>\n\n\n\n
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    Instructor(s)<\/h5>\n\n\n