Course Atlas
The Course Atlas lists all courses offered in a given semester.
The Course Catalog lists all possible courses that can be offered. There is no guarantee that all listed classes will be offered in a given semester.
This page lists all of the classes offered for CS in a given semester.
Courses
Undergraduate CS Courses
| CS130R |
Selected Programming Languages: Programming in Python |
Credits: 2 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
MSC E208 |
TuTh 1:00PM - 2:15PM |
Vishwanath Seshagiri |
20 |
| CS171 |
Introduction to Computer Science II |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
W 8:00AM - 9:15AM |
Nosayba El-Sayed |
35 |
| 2 |
ONLINE |
W 9:40AM - 10:55AM |
Nosayba El-Sayed |
35 |
| 3 |
ONLINE |
TuTh 9:40AM - 10:55AM |
Vaidy Sunderam |
55 |
| CS224 |
Foundations of Comp.Science |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
MW 8:00AM - 9:15AM |
Sahar Voghoei |
85 |
| CS253 |
Data Structures and Algorithms |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
MW 2:40PM - 3:55PM |
Carl Yang |
50 |
| 2 |
ONLINE |
TuTh 9:40AM - 10:55AM |
Michelangelo Grigni |
50 |
| CS255 |
Computer Organization and Assembly Programming |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
TuTh 11:20AM - 12:35PM |
Shun Yan Cheung |
65 |
| CS325 |
Artificial Intelligence |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
Th 8:00AM - 9:15AM |
Steven La Fleur |
80 |
| CS326 |
Analysis of Algorithms |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
TuTh 4:20PM - 5:35PM |
Avani Wildani |
50 |
| CS329 |
Computational Linguistics |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
MW 2:40PM - 3:55PM |
Jinho Choi |
40 |
| CS350 |
Systems Programming |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
MW 9:40AM - 10:55AM |
Dorian Arnold |
40 |
| CS355 |
Advanced Computer Architecture |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
TuTh 1:00PM - 2:15PM |
Shun Yan Cheung |
45 |
| CS377 |
Database Systems |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
MW 1:00PM - 2:15PM |
Nosayba El-Sayed |
60 |
| CS424 |
Theory of Computing |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
TuTh 1:00PM - 2:15PM |
Michelangelo Grigni |
30 |
| CS452 |
Operating Systems |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
TuTh 2:40PM - 3:55PM |
Ken Mandelberg |
20 |
| CS453 |
Computer Security |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
TuTh 11:20AM - 12:35PM |
Ymir Vigfusson |
20 |
| CS470 |
Data Mining |
Credits: 3 |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment |
| 1 |
ONLINE |
MW 4:20PM - 5:35PM |
Liang Zhao |
55 |
Graduate CS Courses
| CS524 |
Theory Of Computing |
Credits: 3 |
| Content: This course gives mathematical methods to classify the complexity of computational problems. Topics include regular languages, grammars, decidability, NP-completeness, and corresponding models of computation. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: CS 124 and 253. |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
ONLINE |
TuTh 1:00PM - 2:15PM |
Michelangelo Grigni |
10 |
| CS553 |
Info.and Computer Security |
Credits: 3 |
| Content: This course adheres to software vulnerabilities and hacking at technical and broader societal levels, taking a deep technical exploration into hands-on binary exploitation. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: CS 450 or CS 551 Systems Programming |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
ONLINE |
TuTh 11:20AM - 12:35PM |
Ymir Vigfusson |
10 |
| CS554 |
Database Systems |
Credits: 3 |
| Content: This course covers recent advances in data management systems and their applications to biomedical problems. Topics include advanced database design, complex queries, data storage and indexing, XML data management, spatial data management, temporal data management, ontologies and semantics, parallel data management and MapReduce. Biomedical use cases will be used for course discussion and projects. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: Basic data structures and database background (CS 377 or equivalent), familiar with a programming language preferred, or permission of the instructor. |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
ONLINE |
MW 11:20AM - 12:35PM |
James Lu |
30 |
| CS562 |
Advanced Computer Systems |
Credits: 3 |
| Content: TBA |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: TBA |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
ONLINE |
TuTh 6:00PM - 7:15PM |
Avani Wildani |
20 |
| CS570 |
Data Mining |
Credits: 3 |
| Content: This course offers an introduction to data mining concepts and techniques. The goal is for the students to have a solid foundation in data mining that allows them to apply data mining techniques to real-world problems and to conduct research and development in new data mining methods. Topics include data processing, design and implementation of data warehouse and OLAP systems, data mining algorithms and methods including association analysis, classification, cluster analysis, as well as emerging applications and trends in data mining. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: TBA |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
ONLINE |
MW 1:00PM - 2:15PM |
Li Xiong |
20 |
| CS571 |
Natural Language Processing |
Credits: 3 |
| Content: This course introduces the fundamental concepts and ideas in natural language processing (NLP). It develops an understanding of algorithms for processing linguistic information and the underlying computational properties of text.
The focus is on modern quantitative techniques in NLP. Advanced topics will include introduction to information retrieval, text mining and knowledge discovery from text data, as well as applications of NLP to bioinformatics and medical informatics. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: TBA |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
ONLINE |
MW 4:20PM - 5:35PM |
Jinho Choi |
30 |
| CS580 |
Operating Systems |
Credits: 3 |
| Content: The structure and organization of computer operating systems. Process, memory, and I/O management; device drivers, inter-machine communication, introduction to multiprocessor systems.
An important portion of the course is a course long programming project that implements a simple operating system in stages. Each stage takes about three weeks, and is used as a basis for the next stage. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: TBA |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
ONLINE |
TuTh 2:40PM - 3:55PM |
Ken Mandelberg |
10 |
| CS584 |
Topics in Computer Science: Adaptive Machine Learning |
Credits: 3 |
| Content: This course focuses on adaptive machine learning methods, including domain adaptation and non-convex optimization. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: TBA |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
ONLINE |
TuTh 4:20PM - 5:35PM |
Rishi Kamaleswaran |
30 |
| CS584 |
Topics in Computer Science: Biomedical Image Analysis |
Credits: 3 |
| Content: This course focuses on computational analytic and interpretive approaches to optimize extraction and use of biological and clinical imaging data for diagnostic and therapeutic translational medical applications. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: TBA |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 2 |
ONLINE |
MW 2:40PM - 3:55PM |
Imon Banerjee |
30 |
| CS596R |
Computer Science Master's Practicum |
Credits: 1 |
| Content: This course aims to expose Master’s students to real life problems that Computer Science and Informatics professionals face in their working environment, and to help students to acquire crucial skills and experience in applying their Computer Science and Informatics skills in solving practical problems. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: TBA |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
|
|
Shun Yan Cheung |
5 |
| CS597R |
Directed Study: Professional Development |
Credits: 1 |
| Content: The purpose of this course is to provide CS Masters students with the necessary career management skills to effectively identify, compete, and secure relevant career-launching internships and full-time professional career opportunities. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: TBA |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
|
|
Paul Fowler |
10 |
| CS700R |
Graduate Seminar |
Credits: 1 |
| Content: This is a required course for all students in the PhD program. It comprises seminars given by faculty, invited guests, and students. |
| Texts: TBA |
| Assessments: TBA |
| Prerequisites: TBA |
| Section |
Location |
Meeting Time |
Instructor |
Enrollment (max) |
| 1 |
ONLINE |
F 1:00PM - 2:15PM |
Vaidy Sunderam |
60 |
