Carnegie Mellon University

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 courses have numbers below xx-600. Senior-level undergraduate courses (xx-4xx and xx-5xx) count for MLT graduation credit, but not PhD graduation credit.
Graduate courses have numbers of xx-600 and above.
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
Course Title Units Semester
11-711 Advanced Natural Language Processing 12 Fall/Spring

10-601

Machine Learning
(MS students)
(Can only count under one focus area)

12 Fall/Spring

10-701

Machine Learning
(PhD students)
(Can only count under one focus area)

12 Fall/Spring
15-750 Algorithms in the Real World 12 Fall
15-780 Graduate Artificial Intelligence 12 Spring
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
(MS students)
(Can only count under one focus area)

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
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
11-741 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

There are several types of independent studies, as shown below.

Course Title Units Semester
11-910

Directed Research
Your primary research topic

1-48 Both
11-920

Independent Study: Breadth
Not in your main area of research

6-18 Both
11-925

Independent Study: Area of Concentration
In your main area of research, but not your primary topic

6-36 Both
11-929 Masters Thesis 6-18 Both
11-930

Dissertation Research
Ph.D. student research after the thesis proposal is accepted

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.

 

The following courses satisfy lab course requirements.

Course Title Units Semester
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 /
Project Course: Conversational 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 /
Ethics, Social Biases, and Positive Impact in Language Technologies

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