CLASIC Curriculum
Requirements
Students must complete at least 32 hours of approved graduate study, including a 2-credit capstone course focused on a publishable research project, which will run in conjunction with an internship or a CU-based research project. As part of the capstone, students will be evaluated by their employer or industry project manager. Students will also prepare a technical report on the completed project that the program directors and project leader will jointly evaluate. TheA minimum course grade is a B and the minimum GPA for graduation is a 3.0.
CLASIC Curriculum
Total of 32 credits; PDF of curriculum with requisites and recommendations (Aug 2024)
Required Courses and Credits
Core Linguistics Courses - 2 of these 3 + one other advisor approved LING course (9 credits)
LING 5030 Linguistics Phonetics
LING 5420 Morphology and Syntax (alt: LING 6450)
LING 5430 Semantics and Pragmatics
An advisor approved LING course; LING 5000-, LING 6000- or LING 7000-level
Core Computer Science Courses - 2 courses (6 credits)
Choose from graduate breadth courses offered in 3 different breadth bins.
One course from Bin 3 is required; another course can be from any Bin, advisor approved.
The list of courses in the Breadth bins is updated every two years.
Bin 1 Recommendations:
CSCI 5454 Design and Analysis of Algorithms (alt: CSCI 5444, or CSCI 5714)
CSCI 5606 Principles of Numerical Computation (alt: CSCI 5646)
Bin 3 (choose one)
Recommendations:
CSCI 5253 Datacenter Scale Computing – Methods, Systems and Techniques
CSCI 5448 Object-Oriented Analysis and Design
CSCI 5535 Fundamental Concepts of Programming Languages
Core CLASIC Courses – 5 total; 3 required & 2 electives (15 credits)
Required for all students:
CSCI/LING 5832 Natural Language Processing (from CS Bin 2)
Choose two of the following:
CSCI/LING 7565 Computational Phonology and Morphology
CSCI/LING 7575 Computational Lexical Semantics
CSCI/LING 7585 Computational Models of Discourse and Dialog
Electives - choose two of the following, advisor approved.
Recommendations:
CSCI 5352 Network Analysis and Modeling
CSCI 5502 Data Mining
CSCI 5622 Machine Learning
CSCI 5922 Neural Networks and Deep Learning
CSCI 6622 Advanced Machine Learning
CSCI 7000 Current Topics in Computer Science
CSCI 7222 Topics in Nonsymbolic Artificial Intelligence
LING 5200 Introduction to Computational Corpus Linguistics
LING 5800 Open Topics in Linguistics (Machine Learning and Linguistics)
LING 6300/3800 Topics in Language Use (Formal Models of Linguistics)
LING 6520 Topics in Comparative Linguistics (Computational Grammars)
PHIL 5440 Topics in Logic
PHIL 5460 Modal Logic
Any other CSCI or LING course at the 5000-, 6000- or 7000-level
Any Core course listed above (not already taken)
CLASIC Capstone Course - 1 course (2 credits)
LING/CSCI 5140 Capstone Project