![]() In-person: G17 CL (Language Media Center) (We are also available to meet by appointment.) Additional setup and software requirements are found on this Checklist page. Mobile or cloud-based machines such as Android/Apple tablets or Chromebooks are not suited. It should be running Windows (10 or 11), Mac OS-X, or Linux (any distribution). Please send any questions/inquiries to are required to bring their own laptop to class. Note that this option is not meant for students who have never taken a college-level programming course. Proof of successful completion must be submitted. They are part of the popular Python for Everybody Specialization, offered year-round, and require paid subscription. Online course substitution: Under limited circumstances, the instructor may allow a sequence of three Coursera courses as a CS 12 stand-in: Getting Started with Python, Python Data Structures, and Proof of basic Python competency (Python code samples due at enrollment, or proof of online course completion due one week before the semester's start).CS 401 "Intermediate Programming Using Java" (grade B or above).Students with formal CS training (majors, minors, etc.) can have the CS 12 prereq waived with the following qualifications: Substitution: CS 12 can be substituted with CS 8 or any similar CS course that uses Python as the programming language of instruction. Linguistics majors and grad students very much remain as the target audience of this course. Having Python programming as a prerequisite, instead of learning in-class, frees up valuable class time to explore more computational linguistic topics and to focus more on linguistic motivations. ![]() Intro-level linguistics and basic Python knowledge are required: LING 1000 "Introduction to Linguistics" and CS 0012 "Introduction to Computing for the Humanities" (or an equivalent class, grade B or above). This course is designed specifically for students in the humanities computer science majors (who are not linguists) are encouraged to take CS 1671 or CS 1571 instead. Students will be given hands-on training on the basics of text processing using Python and will have a chance to work with NLTK, a popular natural language processing application suite. The topics include: spell-checking, machine translation, part-of-speech tagging, parsing, document classification, and corpus building and exploration. They will then be introduced to the challenges of real-world language engineering problems and learn how they are handled with the latest language technologies. The students will first learn the fundamentals of how computers are used to represent and process textual and spoken information. This is a course designed to introduce students who have been exposed to linguistics to real-world applications of computational linguistics. LING 1330/2330 Introduction to Computational Linguistics Fall 2022, University of Pittsburgh
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