Course Atlas

Graduate CS Courses

CS526 Algorithms Credits: 3
Content: This course is a graduate level introduction to the design and analysis of algorithms. Although we will review some undergraduate level material, we will instead emphasize reading and experimentation at a level appropriate for the initiation of research. This course will have both theoretical and practical content. As course highlights, students will be expected to implement and analyze the performance of a fundamental data structure, starting with a close reading of the original research paper.
Texts: TBA
Assessments: TBA
Prerequisites: CS 224 and CS 253.
Section Location Meeting Time Instructor Enrollment (max)
1 MSC N302 TuTh      11:30AM - 12:45PM Michelangelo Grigni 0
CS534 Machine Learning Credits: 3
Content: This course covers fundamental machine learning theory and techniques. The topics include basic theory, classification methods, model generalization, clustering, and dimension reduction. The material will be conveyed by a series of lectures, homeworks, and projects.
Texts: TBA
Assessments: TBA
Prerequisites: Knowledge of linear algebra, multivariate calculus, basic statistics and probability theory. Homework and project will require programming in Python, Matlab, C/C++ or R. Or permission by the instructor.
Section Location Meeting Time Instructor Enrollment (max)
1 MSC W301 MW      1:00PM - 2:15PM Babak Mahmoudi 25
CS551 Systems Programming Credits: 3
Content: Systems programming topics will be illustrated by use of the Unix operating system. Topics include: file i/o, the tty driver, window systems, processes, shared memory, message passing, semaphores, signals, interrupt handlers, network programming and remote procedure calls. Programming examples and assignments will illustrate the system interface on actual computer hardware. All assignments will be in written in C. The department's computing lab will be used in the course to allow students to get hands-on experience with operating system and hardware topics that cannot effectively be pursued on a central timesharing computer.
Texts: TBA
Assessments: TBA
Prerequisites: TBA
Section Location Meeting Time Instructor Enrollment (max)
1 MSC W301 TuTh      2:30PM - 3:45PM Ken Mandelberg 30
CS556 Programming Languages and Compilers Credits: 3
Content: An introduction to the algorithms and data structures used to construct a high level language compiler. Topics include: formal language specification, lexical analysis, parsing, and code generation.
Texts: TBA
Assessments: TBA
Prerequisites: TBA
Section Location Meeting Time Instructor Enrollment (max)
1 MSC W301 MW      11:30AM - 12:45PM James Lu 10
CS557 Artificial Intelligence Credits: 3
Content: This course covers core areas of Artificial Intelligence including perception, optimization, reasoning, learning, planning, decision--making, knowledge representation, vision and robotics.
Texts: TBA
Assessments: TBA
Prerequisites: Undergraduate level of Artificial Intelligence or Machine Learning.
Section Location Meeting Time Instructor Enrollment (max)
1 MSC W303 MW      10:00AM - 11:15AM Eugene Agichtein 30
CS584 Topics in Computer Science: Structure of Information Networks Credits: 3
Content: This course will explore the fundamentals of Quantum Computing. Quantum computers have the potential to efficiently solve certain problems that are intractable for traditional classical computers. Topics include: fundamental models of quantum computing, reversible computing, qubits, entanglement and non-locality, quantum protocols, quantum circuits; simple quantum algorithms, quantum Fourier transform, Shor factoring algorithm, Grover search algorithm, quantum error correction.
Texts: TBA
Assessments: TBA
Prerequisites: Equivalent of CS 326 Analysis of Algorithms and Linear Algebra (such as Math 221)
Section Location Meeting Time Instructor Enrollment (max)
1 MSC W301 TuTh      10:00AM - 11:15AM Ymir Vigfusson 10
CS584 Topics in Computer Science: Information Visualization Credits: 3
Content: TBA
Texts: TBA
Assessments: TBA
Prerequisites: TBA
Section Location Meeting Time Instructor Enrollment (max)
2 ONLINE TuTh      8:30AM - 9:45AM Emily Wall 10
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 10
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: None
Section Location Meeting Time Instructor Enrollment (max)
3 MSC E406 F      2:30PM - 4:00PM Paul Fowler 15
CS598R Rotation Project Credits: 3
Content: Computer Science and Informatics PhD students are required to complete two rotation projects prior to their qualifying exams and dissertation research. Projects often involve interdisciplinary work, and can be co-supervised by a CS faculty and an external faculty member or researcher (e.g., Schools of Medicine and Public Health, the CDC). Students are required to submit a project proposal and a final report.
Texts: TBA
Assessments: TBA
Prerequisites: TBA
Section Location Meeting Time Instructor Enrollment (max)
1        Eugene Agichtein 5
10        James Lu 5
11        Babak Mahmoudi 5
12        Zhaohui "Steve" Qin 5
13        Matthew Reyna 5
14        Reza Sameni 5
15        Abeed Sarker 5
16        Ymir Vigfusson 5
17        Emily Wall 5
18        Li Xiong 5
19        Carl Yang 5
2        Dorian Arnold 5
20        Liang Zhao 5
21        Lars Ruthotto 5
3        Imon Banerjee 5
4        Manoj Bhasin 5
5        Jinho Choi 5
6        Gari Clifford 5
7        Nosayba El-Sayed 5
8        Joyce Ho 5
9        Rishi Kamaleswaran 5
CS599R CS Research Credits: 1-9
Content: Thesis Research (Pre-Candidacy)
Texts: TBA
Assessments: TBA
Prerequisites: TBA
Section Location Meeting Time Instructor Enrollment (max)
1        Eugene Agichtein 5
10        James Lu 5
11        Babak Mahmoudi 5
12        Zhaohui "Steve" Qin 5
13        Matthew Reyna 5
14        Reza Sameni 5
15        Abeed Sarker 5
16        Ymir Vigfusson 5
17        Emily Wall 5
18        Avani Wildani 5
19        Li Xiong 5
2        Dorian Arnold 5
20        Carl Yang 5
21        Liang Zhao 5
3        Imon Banerjee 5
4        Manoj Bhasin 5
5        Jinho Choi 5
6        Gari Clifford 5
7        Nosayba El-Sayed 5
8        Joyce Ho 5
9        Rishi Kamaleswaran 5
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: None
Section Location Meeting Time Instructor Enrollment (max)
1 Online F      1:00PM - 2:15PM Vaidy Sunderam 70
CS799R Dissertation Research Credits: 1-9
Content: Thesis Research
Texts: TBA
Assessments: TBA
Prerequisites: TBA
Section Location Meeting Time Instructor Enrollment (max)
1        Eugene Agichtein 5
10        Babak Mahmoudi 5
11        Zhaohui "Steve" Qin 5
12        Matthew Reyna 5
13        Reza Sameni 5
14        Abeed Sarker 5
15        Vaidy Sunderam 5
16        Ymir Vigfusson 5
17        Lars Ruthotto 5
18        Emily Wall 5
19        Li Xiong 5
2        Dorian Arnold 5
20        Avani Wildani 5
21        Carl Yang 5
22        Liang Zhao 5
3        Imon Banerjee 5
4        Manoj Bhasin 5
5        Jinho Choi 5
6        Gari Clifford 5
7        Joyce Ho 5
8        Rishi Kamaleswaran 5
9        James Lu 5