Computational Linguistics

Linguistic knowledge. Know the core areas of theoretical and empirical linguistics and how the discoveries of these fields are critical to the technology behind search engines, digital libraries, speech recognition, speech synthesis, part-of-speech taggers, syntactic parsers, machine translation, text classification, linguistic data mining, and other forms of Natural Language Processing (NLP)

Computational knowledge. Know the core data structures and computational algorithms used in NLP

Application of knowledge. Apply existing NLP tools in order to perform phonological, morphological, lexical, syntactic, semantic, and/or pragmatic data mining of natural language (i.e., of any natural human language)

Analysis. Use NLP tools to analyze large corpora (or document collections) by classifying texts according to characteristics of the texts (e.g., topic, genre, readability, whether the text is original or translated text) or characteristics of the writers of the texts (e.g., gender, age, level of education, country of origin, native language, author's sentiment toward the topic)