Ph.D. and MLT Course Categories
The Ph.D. and MLT programs organize courses into several different categories. This page explains the courses in each category and provides category-related information.
The course lists below include courses from outside of the LTI that count as LTI courses (as opposed to electives) for satisfying degree requirements. Further information about these courses is available on the web pages of the departments that offer them.
Depending on a student's interests, electives may be taken from the LTI, other departments in the School of Computer Science, or other departments at Carnegie Mellon or the University of Pittsburgh. Students interested in speech should consider speech-oriented electives; other areas of interest include linguistics, statistics, and human-computer interaction (HCI).
Undergraduate course
Graduate course
SCS Course
A small number of courses taught by other CMU colleges can be used to satisfy the SCS course requirement. The courses listed below and any course that satisfies a Focus Area requirement (listed in the following sections) can be counted as an "SCS course".
Course | Title | Units | Semester |
18-691 | Digital Signal Processing | 12 | Spring |
80-816 | Causality and Machine Learning | 12 | Varies |
Linguistic Focus
Course | Title | Units | Semester |
11-722 | Grammar Formalisms | 12 | Spring |
11-723 | Formal Semantics | 12 | Discontinued |
11-724 | Human Language for Artificial Intelligence | 12 | Fall |
11-727 | Computational Semantics for NLP | 12 | Varies |
11-823 | ConLanging: Learning Linguisics & Language Technologies via Construction of Artificial Languages | 12 | Spring |
11-824 | Subword Modeling | 12 | Spring |
80-683 | Language in Use | 12 | Fall |
80-788 | Acoustics of Human Speech: Theory, Data, & Analysis | 12 | Varies |
Computer Science Focus
Course | Title | Units | Semester |
11-711 | Advanced Natural Language Processing | 12 | Fall/Spring |
10-601 |
Machine Learning |
12 | Fall/Spring |
10-701 |
Machine Learning |
12 | Fall/Spring |
15-750 | Algorithms in the Real World | 12 | Fall |
15-780 | Graduate Artificial Intelligence | 12 | Spring |
Statistical/Learning Focus
Course | Title | Units | Semester |
11-685/11-785 |
Introduction to Deep Learning | 12 | Fall/Spring |
11-667 | Large Language Models Methods and Application | 12 | Fall |
11-767 | On-Device Machine Learning | 12 | Fall |
10-601 |
Introduction to Machine Learning |
12 | Fall/Spring |
10-605 | Machine Learing with Large Datasets | 12 | Fall/Spring |
10-618 | Machine Learning for Structured Data | 12 | Fall |
10-701 | Introduction to Machine Learning (PhD students) (Can only count under one focus area) |
12 | Fall/Spring |
10-707 | Advanced Deep Learning | 12 | Spring |
10-708 | Probabilistic Graphical Models | 12 | Spring |
10-715 | Advanced Introduction to Machine Learning | 12 | Fall |
10-725 |
Convex Optimization | 12 | Fall/Spring |
15-883 |
Computational Models of Neural Systems | 12 | Fall |
36-705 |
Intermediate Statistics | 12 | Fall |
Task Orientation Focus
Course | Title | Units | Semester |
10-605/10-805 | Machine Learning with Large Datasets | 12 | Spring |
11-641/11-741 | Machine Learning for Text and Graph-based Mining | 12 | Replaced by 11-741 below |
11-642/11-742 | Search Engines | 12 | Fall/Spring |
11-692 | Speech Processing / Speech Technology for Conversational AI |
12 | Fall/Spring |
11-737 | Multilingual NLP | 12 | Spring |
11-741 | Machine Learning with Graphs | 12 | Fall/Spring |
11-751 | Speech Recognition and Understanding | 12 | Fall |
11-755 | Machine Learning for Signal Processing | 12 | Fall |
11-775 | Large-Scale Multimedia Analysis | 12 | Fall/Spring |
11-776 | Multimodal Affective Computing | 12 | Fall/Spring |
11-777 | Multimodal Machine Learning | 12 | Fall/Spring |
11-685/11-785 | Introduction to Deep Learning | 12 | Fall/Spring |
11-797 | Question Answering | 12 | Spring |
11-851 | Talking to Robots | 12 | Fall |
11-877 | Advanced Topics in Multimodal Machine Learning | 12 | Spring |
11-891 | Neural Code Generation | 12 | Spring |
Independent Studies
There are several types of independent studies, as shown below.
Course | Title | Units | Semester |
11-910 |
Directed Research |
1-48 | Both |
11-920 |
Independent Study: Breadth |
6-18 | Both |
11-925 |
Independent Study: Area of Concentration |
6-36 | Both |
11-929 | Masters Thesis | 6-18 | Both |
11-930 |
Dissertation Research |
5-36 | Both |
Note that the Independent Study courses listed above do not normally count for LTI class credit. The exception is if an Independent Study is used to replace an unavailable LTI course (with prior permission of the chair of the LTI graduate programs).
Masters students: Note that only 12 units of "Independent Study: Project" may normally count towards your total course requirements.
Lab Courses
The following courses satisfy lab course requirements.
Course | Title | Units | Semester |
11-711 | Advanced Natural Language Processing | 12 | Spring |
11-712 | Lab in Natural Language Processing (Self-Paced) | 6 | Fall/Spring |
11-723 | Linguistics Lab (Self-Paced) | 6 | Fall/Spring |
11-726 | Meaning in Language lab (Self-Paced) | 6 | Fall/Spring |
11-727 | Computational Semantics for NLP | 12 | Varies |
11-742 | Self-Paced Lab: IR | 6 | Upon request |
11-754 |
Project Course: Dialogue Systems / |
6 | Spring |
11-767 | On-Device Machine Learning | 12 | Fall |
11-775 | Large-Scale Multimedia Analysis | 12 | Fall/Spring |
11-777 | Multimodal Machine Learning | 12 | Fall/Spring |
11-785 | Introduction to Deep Learning | 12 | Fall/Spring |
11-796 | Question Answering Lab | 6 | Fall/Spring |
11-797 | Question Answering | 12 | Spring |
11-830 |
Computational Ethics in Natural Language Processing / |
12 | Spring |
11-831 |
Computational Ethics Lab (Self-Paced) |
6 | Fall |
11-866 |
Artificial Social Intelligence (Lab if 12 hours) |
6/12 | Discontinued |
11-877 |
Advanced Topics in Multimodal Machine Learning (Lab if 12 hours) |
6/12 | Spring |