JF

Judy Fox

Associate Professor
Department: Data Science School
Office location and address
31 Bonnycastle Dr
Charlottesville, Virginia 22903
Expeditions: Collaborative Research: Global Pervasive Computational Epidemiology
Source: U.S. National Science Foundation (NSF)
November 01, 2021 – April 30, 2025
CS 4993: Independent Study
Credits: 1–3
In-depth study of a computer science or computer engineering problem by an individual student in close consultation with departmental faculty. The study is often either a thorough analysis of an abstract computer science problem or the design, implementation, and analysis of a computer system (software or hardware). Prerequisite: Instructor permission.
CS 4998: Distinguished BA Majors Research
Credits: 3
Required for Distinguished Majors completing the Bachelor of Arts degree in the College of Arts and Sciences. An introduction to computer science research and the writing of a Distinguished Majors thesis. Prerequisites: CS 2150 or CS 2501 topic DSA2 with a grade of C- or higher, and BSCS major
CS 5010: Programming and Systems for Data Science
Credits: 3
The objective of this course is to introduce basic data analysis techniques including data analysis at scale, in the context of real-world domains such as bioinformatics, public health, marketing, security, etc. For the purpose of facilitating data manipulation and analysis, students will be introduced to essential programming techniques in Python, an increasingly prominent language for data science and "big data" manipulation. Prerequisite: CS 1110, Math 1310 or APMA 1110, Math 3351 or APMA 3080, Math 3100, APMA 3010 or APMA 3110
DS 5100: Programming for Data Science
Credits: 3
An introduction to essential programming concepts, structures, and techniques. Students will gain confidence in not only reading code, but learning what it means to write good quality code. Additionally, essential and complementary topics are taught, such as testing and debugging, exception handling, and an introduction to visualization. This course is project based, consisting of a semester project and final project presentations.
DS 6559: New Course in Data Science
Credits: 1–4
This course provides the opportunity to offer a new topic in the subject area of data science.
DS 6999: Independent Study
Credits: 1–12
Graduate-level independent study conducted under the supervision of a specific instructor(s)
CS 7993: Independent Study
Credits: 1–12
Detailed study of graduate course material on an independent basis under the guidance of a faculty member.
CS 8897: Graduate Teaching Instruction
Credits: 1–12
For master's students who are teaching assistants.
CS 8999: Thesis
Credits: 1–12
Formal record of student commitment to thesis research for the Master of Science degree under the guidance of a faculty advisor. May be repeated as necessary.