==== CS 366 Spring 2020 Syllabus ====

== Text ==

  * Dan Jurafsky and James Martin, [[http://www.cs.colorado.edu/%7Emartin/slp.html | Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition  ]], Second Edition, and [[https://web.stanford.edu/~jurafsky/slp3/ | selected chapters online from the upcoming 3rd edition]].
  * We will also use [[http://www.nltk.org/book/ | the online book associated with the Natural Language ToolKit (NLTK)]].

== Other useful books and materials ==
  * Dickinson, Brew, and Meuers. [[https://www.wiley.com/en-us/Language+and+Computers-p-9781405183055 | Language and Computers.]] Wiley Press.
  * Manning, C. and Schütze, H.  [[https://nlp.stanford.edu/fsnlp/ | Foundations of Statistical Natural Language Processing.]] MIT Press.
  * Witten, I. H., Eibe, F., Hall, M.A. [[https://www.elsevier.com/books/data-mining/witten/978-0-12-804291-5 | Data Mining: Practical Machine Learning Tools and Techniques]], Fourth Edition.
  * Lutz and Ascher, [[http://shop.oreilly.com/product/9780596002817.do | Learning Python]], O'Reilly.

== Software ==

In this course we will use Python, together with the Natural Language Toolkit (NLTK). It is assumed that you are either familiar with Python already, or, due to your excellent preparation in the Vassar Computer Science program, you have the ability to learn it quickly.
You can use the computers in the Asprey Lab in the Computer Science Department, which have all of the required software already installed. If you want to use your own computer, you should install the following:

  * The Natural Language Toolkit--NLTK (available [[http://nltk.org/install | here ]]) and the NLTK data (available [[http://nltk.org/data | here ]]). If not already installed on your computer, you will also need to install [[http://www.python.org/download/ | Python]].

== Discussion ==

Messages will on occasion be sent to the class's [[https://groups.google.com/forum/#!forum/cs366-computational-linguistics-2020 | Google Group]], which also serves as a discussion forum for questions, etc. You should rhave received an invitation to join this group in email. NOTE: You are responsible for checking this list for important course information.

== Grades ==

Grades will be determined on the basis of performance on four assignments (40%), a final project and presentation (50%), and homework (10%). The [[https://www.cs.vassar.edu/~cs366/schedule.html |Schedule of Lectures, Readings, and Assignments]] contains links to assignments, homework, lecture slides, etc. Information may also be disseminated via the [[https://groups.google.com/forum/#!forum/cs366-computational-linguistics-2020 | CS366 mailing list]].


== Academic Integrity ==

Read [[http://deanofthecollege.vassar.edu/documents/originality/index.html|Originality and Attribution: A guide for student writers at Vassar College]].  While cooperation is encouraged, attribution must be given, and each student must hand in his or her own work. College policy dictates that instructors must report all suspected incidents of cheating to their department chair, who may in turn refer the situation to the Academic Panel.


== Students with disabilities ==

Academic accommodations are available for students registered with the Office for Accessibility and Educational Opportunity.  Students in need of ADA/504 accommodations should schedule an appointment with me early in the semester to discuss any accommodations for this course that have been approved by the Office for Accessibility and Educational Opportunity, as indicated in your AEO accommodation letter.