ClassInfo

CSC 594 Topics in Artificial Intelligence

Noriko Tomuro

Office: CDM 648
Spring 2017-2018
Class number: 34592
Section number: 910
-
Online Campus

Summary

This course introduces the fundamental concepts and theory of Natural Language Processing (NLP; a.k.a. computational linguistics) and its practical tasks. NLP is a field in Artificial Intelligence (AI) devoted to creating computer systems which understand and produce human languages. Traditional NLP tasks include part-of-speech tagging, parsing, information extraction, machine translation, text categorization, question-answering and conversation agents. Within the last several years, the use of NLP in computing machines/devices has surged dramatically, with the advancement of human-language technologies (NLP and speech) as well as people's general interest in language-based interaction with digital devices. Recent NLP applications include sentiment analysis, opinion mining, chatbots and voice-assisted digital personal assistants.

The primary focus of this course is on the fundamental concepts and algorithms/techniques of NLP. The theoretical side is complemented by case studies, practical implementations/programming and projects. Topics to be covered include language models, sentiment analysis, parsing, information extraction and neural language models.



Texts

There is no required textbook. We will use materials that are publicly available on the internet, in particular:
  • "Speech and Language Processing (3rd ed)" by Jurafsky and Martin, 2017 (draft).
  • "Natural Language Processing with Python", by Steven Bird, Ewan Klein, and Edward Loper, 2009.


Grading

The grade breakdown will be as follows:
  • Assignments 70%
  • Final Project 30%


Prerequisites

(CSC 478 or CSC 480) and (CSC 529 or CSC 578), or consent of the instructor.

Students should have prior knowledge of the concepts of Artificial Intelligence, Machine Learning or Data Mining. Also students must be fluent in at least one programming language (e.g. Python, Java, C++) or data analytic tool (e.g. SAS, SPSS, MatLab, R). Python (3) will be used as the primary programming language in the class, but students are free to use any programming language/tool for assignments and projects.



Coursework

  1. Assignments. Assignments will consist of programming (3-4 of them), written problems (2-4 of them) and a small project (1 of them). Code has to be written in Python 3.
  2. Final Project. Final project will be an individual project. Students will choose their own topic (which have to be approved by the instructor). Details will be announced during the course.


School policies:

Changes to Syllabus

This syllabus is subject to change as necessary during the quarter. If a change occurs, it will be thoroughly addressed during class, posted under Announcements in D2L and sent via email.

Online Course Evaluations

Evaluations are a way for students to provide valuable feedback regarding their instructor and the course. Detailed feedback will enable the instructor to continuously tailor teaching methods and course content to meet the learning goals of the course and the academic needs of the students. They are a requirement of the course and are key to continue to provide you with the highest quality of teaching. The evaluations are anonymous; the instructor and administration do not track who entered what responses. A program is used to check if the student completed the evaluations, but the evaluation is completely separate from the student’s identity. Since 100% participation is our goal, students are sent periodic reminders over three weeks. Students do not receive reminders once they complete the evaluation. Students complete the evaluation online in CampusConnect.

Academic Integrity and Plagiarism

This course will be subject to the university's academic integrity policy. More information can be found at http://academicintegrity.depaul.edu/ If you have any questions be sure to consult with your professor.

All students are expected to abide by the University's Academic Integrity Policy which prohibits cheating and other misconduct in student coursework. Publicly sharing or posting online any prior or current materials from this course (including exam questions or answers), is considered to be providing unauthorized assistance prohibited by the policy. Both students who share/post and students who access or use such materials are considered to be cheating under the Policy and will be subject to sanctions for violations of Academic Integrity.

Academic Policies

All students are required to manage their class schedules each term in accordance with the deadlines for enrolling and withdrawing as indicated in the University Academic Calendar. Information on enrollment, withdrawal, grading and incompletes can be found at http://www.cdm.depaul.edu/Current%20Students/Pages/PoliciesandProcedures.aspx.

Students with Disabilities

Students who feel they may need an accommodation based on the impact of a disability should contact the instructor privately to discuss their specific needs. All discussions will remain confidential.
To ensure that you receive the most appropriate accommodation based on your needs, contact the instructor as early as possible in the quarter (preferably within the first week of class), and make sure that you have contacted the Center for Students with Disabilities (CSD) at:
Lewis Center 1420, 25 East Jackson Blvd.
Phone number: (312)362-8002
Fax: (312)362-6544
TTY: (773)325.7296