National Science Foundation Research Traineeship

AI Focus*

*Available to the following departments: Applied Math & Statistics, Economics, Linguistics, Neurobiology & Behavior, Political Science, Psychology, and Sociology.

A Focus in Artificial Intelligence
This focus requires 12 credits (four courses), at least one of which must be CSE 512: Machine Learning or CSE 537: Artificial Intelligence. The remaining courses can be chosen from the list below. Please note: an elementary knowledge of programming is preferred.
CSE 505: Computing with Logic CSE 512: Machine Learning CSE 519: Data Science Fundamentals CSE 525: Robotics CSE 527: Computer Vision			CSE 537: Artificial Intelligence CSE 538: Natural Language Processing CSE 544: Probability and Statistics for Data Scientists CSE 545: Big Data Analytics CSE 564: Visualization

Students without formal preparation in Computer Science may count up to two of the following graduate-level preparatory ("bridge") courses toward the focus, and should consult with the admission committee before taking the other graduate CS courses.

CSE 581, Computer Science Fundamentals: Theory

CSE 582, Computer Science Fundamentals: Data Structures and Algorithms

CSE 583, Computer Science Fundamentals: Programming Abstractions

HCDS Focus*

*Available to the following departments: Applied Math & Statitistics, Computer Science, Economics, Linguistics, Neurobiology & Behavior, Political Science, Psychology, and Sociology.

A Focus in Human-Centered Data Science
This focus will require 12 credits (four courses): two core DS/CS courses and two electives. Requires Python knowledge * Instructor Consent Required DS/CS Core: Both of the following Algorithms: CSE 582: Computer Science Fundamentals: Data Structures and Algorithms Alternative: AMS 542 / CSE 548: Analysis of Algorithms or AMS 561/DCS 521: Introduction to Computational and Data Science Machine Learning: AMS 580: Statistical Learning** Alternative: *AMS 520: Machine Learning in Quantitative Finance or CSE 512: Machine Learning
Two electives chosen from the courses below. At least one must be outside of the student's home department and not cross-listed. Note that courses outside of the home department require permission of the instructor. Admission to this focus does not guarantee instructor approval. Courses outside this list may be used to satisfy the electives requirement with prior permission of this focus program’s director. *Requires Python knowledge
AFS 502: Research Methods in Africana Studies AFS 533: Race, Gender and Globalization CSE 564: Visualization (AMS and CS students require approval) ECO 522: Applied Econometrics ECO 612: Computational Economics and Dynamic Modeling ECO 640: Labor Economics I ISE 503: Data Management (AMS and CS students require approval)* LIN 521: Syntax I LIN 523: Phonology I LIN 637: Computational Linguistics 2 NEU 534: Principles of Neurobiology NEU 536: Introduction to Computational Neuroscience	NEU 537: Neurotransmission and Neuromodulation NEU 547: Introduction to Neural Computation POL 633: Social Influence and Group Processes in Political Decision Making POL 676: Advanced Topics: Methods I PSY 507: Meta Analysis PSY 513: Theories of Attention PSY 520: Psycholinguistics PSY 549: Prejudice and Discrimination PSY 620: Bayesian Analysis SOC 504: Logic and Practice of Sociology SOC 556: Political Sociology SOC 561: Cultural Sociology

A Focus in Human-Centered Data Science

This focus will require 12 credits (four courses): two core DS/CS courses and two electives.

*Requires Python knowledge ** Instructor Consent Required

DS/CS Core: Both of the following

Algorithms: CSE 582: Computer Science Fundamentals: Data Structures and Algorithms
- - Alternative: AMS 542 / CSE 548: Analysis of Algorithms or **AMS 561/DCS 521: Introduction to Computational and Data Science
Machine Learning: AMS 580: Statistical Learning
- - Alternative: *AMS 520: Machine Learning in Quantitative Finance or CSE 512: Machine Learning

Two electives chosen from the courses below. At least one must be outside of the student's home department and not cross-listed. Note that courses outside of the home department require permission of the instructor. Admission to this focus does not guarantee instructor approval.

Courses outside this list may be used to satisfy the electives requirement with prior permission of this focus program’s director.

*Requires Python knowledge

AFS 502: Research Methods in Africana Studies

AFS 533: Race, Gender and Globalization

*CSE 564: Visualization (AMS and CS students require approval)

ECO 522: Applied Econometrics

ECO 612: Computational Economics and Dynamic Modeling

ECO 640: Labor Economics I

ISE 503: Data Management (AMS and CS students require approval)

LIN 521: Syntax I

LIN 523: Phonology I

LIN 637: Computational Linguistics 2

NEU 534: Principles of Neurobiology

NEU 536: Introduction to Computational Neuroscience

NEU 537: Neurotransmission and Neuromodulation

NEU 547: Introduction to Neural Computation

POL 633: Social Influence and Group Processes in Political Decision Making

POL 676: Advanced Topics: Methods I

PSY 507: Meta Analysis

PSY 513: Theories of Attention

PSY 520: Psycholinguistics

PSY 549: Prejudice and Discrimination

PSY 620: Bayesian Analysis

SOC 504: Logic and Practice of Sociology

SOC 556: Political Sociology

SOC 561: Cultural Sociology

In addition to the 12-credits, all students enrolled in the HCDS Focus will have to complete the online Citi Training Module, "Human Research," (for 0 credits; students will receive a certificate of completion to document this requirement). https://www.citiprogram.org/