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University of Michigan School of Information


630 - Natural Language Processing: Algorithms and People

Natural Language Processing: Algorithms and People --- This course focuses on how to use machine learning techniques to understand, annotate, and generate the language we see in everyday situations. The techniques learned in this course can be applied to any kind of text and enable turning qualitative evaluation of text in a precise quantitative measurement. Students will learn the linguistics fundamentals of natural language processing (NLP), with specific topics of part of speech tagging, syntax and parsing, lexical semantics, topic models, and machine translation. Additional advanced topics will include sentiment analysis, crowdsourcing, and deep learning for NLP.
Credit Hours 3


  • [(SI 507 or waiver or 508) and (SI 544 or waiver or BIOSTAT 501 or 521 or 601)]; (C- or better) or Graduate standing in Applied Statistics, Master's in Data Science, or Computer Science & Engineering
  • [Co-requisite: SI 507;(C- or better) or waiver or 508; (C- or better)] or Prerequisite: SI 330; (C- or better)