Departmental Advisors
Undergraduate Studies Office
Vicki Jackson
MEB 3190
Graduate Studies Office
Jill Wilson
MEB 3190
Departmental Notes

For course descriptions and pre-requisite information click on the subject column next to the appropriate catalog number.

THIS DEPARTMENT ENFORCES UNDERGRADUATE PREREQUISITES. Please note that the registration system may not factor in transfer work when determining if prerequisites have been met. If you are unable to register for a course and think you have met the prerequisite(s), please contact an advisor from this department to inquire about obtaining a permission code. You may be administratively dropped from a course if the prerequisite has not been met.

CS 1400 - 001 Intro Comp Programming


This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 1400 - 001 Intro Comp Programming

  • Class Number:
  • Instructor: KOPTA, DANIEL
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 177

This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 1400 - 002 Intro Comp Programming

CS 1400 - 002 Intro Comp Programming

  • Class Number: 14029
  • Instructor: KOPTA, DANIEL
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 23

CS 1400 - 003 Intro Comp Programming

CS 1400 - 003 Intro Comp Programming

  • Class Number: 13487
  • Instructor: KOPTA, DANIEL
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 11

CS 1400 - 004 Intro Comp Programming

CS 1400 - 004 Intro Comp Programming

  • Class Number: 13488
  • Instructor: KOPTA, DANIEL
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 16

CS 1400 - 005 Intro Comp Programming

CS 1400 - 005 Intro Comp Programming

  • Class Number: 13489
  • Instructor: KOPTA, DANIEL
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 21

CS 1400 - 006 Intro Comp Programming

CS 1400 - 006 Intro Comp Programming

  • Class Number: 13993
  • Instructor: KOPTA, DANIEL
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 12

CS 1400 - 020 Intro Comp Programming


This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 1400 - 020 Intro Comp Programming

  • Class Number:
  • Instructor: DE ST GERMAIN, H. JAMES 'JIM'
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 241

This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 1400 - 022 Intro Comp Programming

CS 1400 - 022 Intro Comp Programming

  • Class Number: 15690
  • Instructor: DE ST GERMAIN, H. JAMES 'JIM'
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 29

CS 1400 - 023 Intro Comp Programming

CS 1400 - 023 Intro Comp Programming

  • Class Number: 16783
  • Instructor: DE ST GERMAIN, H. JAMES 'JIM'
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 31

CS 1400 - 024 Intro Comp Programming

CS 1400 - 024 Intro Comp Programming

  • Class Number: 18438
  • Instructor: DE ST GERMAIN, H. JAMES 'JIM'
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 28

CS 1400 - 025 Intro Comp Programming

CS 1400 - 025 Intro Comp Programming

  • Class Number: 18439
  • Instructor: DE ST GERMAIN, H. JAMES 'JIM'
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 29

CS 1400 - 026 Intro Comp Programming

CS 1400 - 026 Intro Comp Programming

  • Class Number: 18440
  • Instructor: DE ST GERMAIN, H. JAMES 'JIM'
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 29

CS 1410 - 001 Object-Oriented Prog


This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 1410 - 001 Object-Oriented Prog

  • Class Number:
  • Instructor: MARTIN, TRAVIS B
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 28

This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 1410 - 003 Object-Oriented Prog

CS 1410 - 003 Object-Oriented Prog

  • Class Number: 15339
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 1

CS 1410 - 004 Object-Oriented Prog

CS 1410 - 004 Object-Oriented Prog

  • Class Number: 15340
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 1410 - 005 Object-Oriented Prog

CS 1410 - 005 Object-Oriented Prog

  • Class Number: 15341
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 1410 - 006 Object-Oriented Prog

CS 1410 - 006 Object-Oriented Prog

  • Class Number: 15342
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 1

CS 1410 - 007 Object-Oriented Prog

CS 1410 - 007 Object-Oriented Prog

  • Class Number: 15343
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 25

CS 1420 - 001 Accel Obj-Orient Prog


This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 1420 - 001 Accel Obj-Orient Prog

  • Class Number:
  • Instructor: HEISLER, ERIC
  • Instructor: PARKER, ERIN
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 303

This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 1420 - 002 Accel Obj-Orient Prog

CS 1420 - 002 Accel Obj-Orient Prog

  • Class Number: 14767
  • Instructor: HEISLER, ERIC
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 26

CS 1420 - 003 Accel Obj-Orient Prog

CS 1420 - 003 Accel Obj-Orient Prog

  • Class Number: 14768
  • Instructor: HEISLER, ERIC
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 24

CS 1420 - 004 Accel Obj-Orient Prog

CS 1420 - 004 Accel Obj-Orient Prog

  • Class Number: 14769
  • Instructor: HEISLER, ERIC
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 17

CS 1420 - 005 Accel Obj-Orient Prog

CS 1420 - 005 Accel Obj-Orient Prog

  • Class Number: 14770
  • Instructor: HEISLER, ERIC
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 20

CS 1420 - 006 Accel Obj-Orient Prog

CS 1420 - 006 Accel Obj-Orient Prog

  • Class Number: 14771
  • Instructor: HEISLER, ERIC
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 24

CS 1420 - 007 Accel Obj-Orient Prog

CS 1420 - 007 Accel Obj-Orient Prog

  • Class Number: 14772
  • Instructor: HEISLER, ERIC
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 23

CS 1420 - 008 Accel Obj-Orient Prog

CS 1420 - 008 Accel Obj-Orient Prog

  • Class Number: 14773
  • Instructor: HEISLER, ERIC
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 18

CS 1420 - 009 Accel Obj-Orient Prog

CS 1420 - 009 Accel Obj-Orient Prog

  • Class Number: 14774
  • Instructor: HEISLER, ERIC
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 18

CS 2100 - 001 Discrete Structures


Sections 002-005 belong to this lecture. This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 2100 - 001 Discrete Structures

  • Class Number:
  • Instructor: Elhabian, Shireen
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 58

Sections 002-005 belong to this lecture. This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 2100 - 002 Discrete Structures

CS 2100 - 002 Discrete Structures

  • Class Number: 13490
  • Instructor: Elhabian, Shireen
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 6

CS 2100 - 003 Discrete Structures

CS 2100 - 003 Discrete Structures

  • Class Number: 13099
  • Instructor: Elhabian, Shireen
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 0

CS 2100 - 004 Discrete Structures

CS 2100 - 004 Discrete Structures

  • Class Number: 13098
  • Instructor: Elhabian, Shireen
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 0

CS 2100 - 005 Discrete Structures

CS 2100 - 005 Discrete Structures

  • Class Number: 13491
  • Instructor: Elhabian, Shireen
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 52

CS 2420 - 001 Intro Alg & Data Struct


This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 2420 - 001 Intro Alg & Data Struct

  • Class Number:
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 64

This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 2420 - 002 Intro Alg & Data Struct

CS 2420 - 002 Intro Alg & Data Struct

  • Class Number: 13101
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 2420 - 003 Intro Alg & Data Struct

CS 2420 - 003 Intro Alg & Data Struct

  • Class Number: 13102
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 2420 - 004 Intro Alg & Data Struct

CS 2420 - 004 Intro Alg & Data Struct

  • Class Number: 13103
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 2420 - 005 Intro Alg & Data Struct

CS 2420 - 005 Intro Alg & Data Struct

  • Class Number: 13104
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 1

CS 2420 - 006 Intro Alg & Data Struct

CS 2420 - 006 Intro Alg & Data Struct

  • Class Number: 13995
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 2420 - 007 Intro Alg & Data Struct

CS 2420 - 007 Intro Alg & Data Struct

  • Class Number: 13996
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 2420 - 020 Intro Alg & Data Struct

CS 2420 - 020 Intro Alg & Data Struct

  • Class Number:
  • Instructor: PARKER, ERIN
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 170

CS 2420 - 022 Intro Alg & Data Struct

CS 2420 - 022 Intro Alg & Data Struct

  • Class Number: 18446
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 13

CS 2420 - 023 Intro Alg & Data Struct

CS 2420 - 023 Intro Alg & Data Struct

  • Class Number: 18447
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 12

CS 2420 - 024 Intro Alg & Data Struct

CS 2420 - 024 Intro Alg & Data Struct

  • Class Number: 18455
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 8

CS 2420 - 025 Intro Alg & Data Struct

CS 2420 - 025 Intro Alg & Data Struct

  • Class Number: 18456
  • Instructor: PARKER, ERIN
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 13

CS 3020 - 001 Research Forum

CS 3020 - 001 Research Forum

  • Class Number: 7185
  • Component: Seminar
  • Type: In Person
  • Units: 1.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 35

CS 3100 - 001 Models Of Computation

CS 3100 - 001 Models Of Computation

  • Class Number: 4369
  • Instructor: WANG, HAITAO
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Fees: $39.82
  • Seats Available: 68

CS 3130 - 002 Eng Prob Stats


The course fee covers digital course materials through the Inclusive Access program. Students may request to opt out here: https://portal.verba.io/utah/login

CS 3130 - 002 Eng Prob Stats

  • Class Number: 12063
  • Instructor: XIANG, YU
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: Yes
  • Fees: $32.94
  • Seats Available: 29

The course fee covers digital course materials through the Inclusive Access program. Students may request to opt out here: https://portal.verba.io/utah/login

CS 3130 - 003 Eng Prob Stats

CS 3130 - 003 Eng Prob Stats

  • Class Number: 14166
  • Instructor: CHEN, RONG-RONG
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 3190 - 001 Found. of Data Analysis

CS 3190 - 001 Found. of Data Analysis

  • Class Number: 10846
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 22

CS 3390 - 001 Ethics in Data Science

CS 3390 - 001 Ethics in Data Science

  • Class Number: 13492
  • Instructor: PATIL, SAMEER
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 15

CS 3500 - 001 Software Practice


This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 3500 - 001 Software Practice

  • Class Number:
  • Instructor: MARTIN, TRAVIS B
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 183

This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 3500 - 002 Software Practice

CS 3500 - 002 Software Practice

  • Class Number: 13106
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 20

CS 3500 - 003 Software Practice

CS 3500 - 003 Software Practice

  • Class Number: 13107
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 2

CS 3500 - 004 Software Practice

CS 3500 - 004 Software Practice

  • Class Number: 13108
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 3500 - 005 Software Practice

CS 3500 - 005 Software Practice

  • Class Number: 14000
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 3500 - 006 Software Practice

CS 3500 - 006 Software Practice

  • Class Number: 14001
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 20

CS 3500 - 007 Software Practice

CS 3500 - 007 Software Practice

  • Class Number: 14002
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: -1

CS 3500 - 008 Software Practice

CS 3500 - 008 Software Practice

  • Class Number: 14003
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 3500 - 009 Software Practice

CS 3500 - 009 Software Practice

  • Class Number: 14004
  • Instructor: MARTIN, TRAVIS B
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 15

CS 3505 - 001 Software Practice II


This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 3505 - 001 Software Practice II

  • Class Number:
  • Instructor: JOHNSON, DAVID
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 7

This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 3505 - 003 Software Practice II

CS 3505 - 003 Software Practice II

  • Class Number: 8748
  • Instructor: JOHNSON, DAVID
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 1

CS 3505 - 004 Software Practice II

CS 3505 - 004 Software Practice II

  • Class Number: 8749
  • Instructor: JOHNSON, DAVID
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 3505 - 005 Software Practice II

CS 3505 - 005 Software Practice II

  • Class Number: 9497
  • Instructor: JOHNSON, DAVID
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 3505 - 006 Software Practice II

CS 3505 - 006 Software Practice II

  • Class Number: 14016
  • Instructor: JOHNSON, DAVID
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 4

CS 3505 - 007 Software Practice II

CS 3505 - 007 Software Practice II

  • Class Number: 14017
  • Instructor: JOHNSON, DAVID
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 3

CS 3505 - 008 Software Practice II

CS 3505 - 008 Software Practice II

  • Class Number: 14018
  • Instructor: JOHNSON, DAVID
  • Component: Discussion
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Seats Available: -1

CS 3520 - 001 Programming Languages

CS 3520 - 001 Programming Languages

  • Class Number: 18453
  • Instructor: FLATT, Matthew
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 24

CS 3540 - 001 Design Human Center Exp

CS 3540 - 001 Design Human Center Exp

  • Class Number: 9486
  • Instructor: WIESE, JASON
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 0

CS 3550 - 001 Web Software Dev I


Students who have completed CS 4540: Web Software Architecture should not enroll in CS 3550 due to significant overlap in the course material. CS 4540 satisfies the pre-requisite for CS 4550: Web Software Development II (to be offered in Spring 2024).

CS 3550 - 001 Web Software Dev I

  • Class Number: 18443
  • Instructor: PANCHEKHA, PAVEL
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 0

Students who have completed CS 4540: Web Software Architecture should not enroll in CS 3550 due to significant overlap in the course material. CS 4540 satisfies the pre-requisite for CS 4550: Web Software Development II (to be offered in Spring 2024).

CS 3700 - 001 Digital System Design

CS 3700 - 001 Digital System Design

  • Class Number:
  • Instructor: Yu, Cunxi
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Fees: $105.90
  • Seats Available: 12

CS 3700 - 002 Digital System Design

CS 3700 - 002 Digital System Design

  • Class Number: 12609
  • Instructor: Yu, Cunxi
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Fees: $105.90
  • Seats Available: 1

CS 3700 - 004 Digital System Design

CS 3700 - 004 Digital System Design

  • Class Number: 14308
  • Instructor: Yu, Cunxi
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Fees: $105.90
  • Seats Available: 2

CS 3700 - 005 Digital System Design

CS 3700 - 005 Digital System Design

  • Class Number: 14309
  • Instructor: Yu, Cunxi
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: No
  • Fees: $105.90
  • Seats Available: 3

CS 3710 - 001 Computer Design Lab


Laboratories scheduled during first week of classes.

CS 3710 - 001 Computer Design Lab

  • Class Number: 3360
  • Component: Laboratory
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Fees: $60.00
  • Seats Available: 15

Laboratories scheduled during first week of classes.

CS 3810 - 001 Computer Organization

CS 3810 - 001 Computer Organization

  • Class Number: 13109
  • Instructor: KOPTA, DANIEL
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 83

CS 3991 - 001 CE Junior Seminar

CS 3991 - 001 CE Junior Seminar

  • Class Number: 4209
  • Instructor: BERZINS, MARTIN
  • Component: Seminar
  • Type: In Person
  • Units: 1.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 31

CS 4000 - 001 Senior Capstone Design

CS 4000 - 001 Senior Capstone Design

  • Class Number: 7934
  • Instructor: DE ST GERMAIN, H. JAMES 'JIM'
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 13

CS 4150 - 001 Algorithms

CS 4150 - 001 Algorithms

  • Class Number: 9356
  • Instructor: BHASKARA, ADITYA
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 8

CS 4230 - 001 Parallel Programming

CS 4230 - 001 Parallel Programming

  • Class Number: 10843
  • Instructor: SADAYAPPAN, SADAY
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 38

CS 4300 - 001 Artificial Intelligence

CS 4300 - 001 Artificial Intelligence

  • Class Number: 15349
  • Instructor: KUNTZ, ALAN
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 11

CS 4400 - 001 Computer Systems


This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 4400 - 001 Computer Systems

  • Class Number:
  • Instructor: Zhang, Mu
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: Yes
  • Fees: $32.94
  • Seats Available: 86

This course requires registration for a lab and/or discussion section. Students will be automatically registered for this lecture section when registering for the pertinent lab and/or discussion section.

CS 4400 - 002 Computer Systems

CS 4400 - 002 Computer Systems

  • Class Number: 9487
  • Instructor: Zhang, Mu
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 0

CS 4400 - 003 Computer Systems

CS 4400 - 003 Computer Systems

  • Class Number: 9488
  • Instructor: Zhang, Mu
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 0

CS 4400 - 004 Computer Systems

CS 4400 - 004 Computer Systems

  • Class Number: 12606
  • Instructor: Zhang, Mu
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 12

CS 4400 - 005 Computer Systems

CS 4400 - 005 Computer Systems

  • Class Number: 14019
  • Instructor: Zhang, Mu
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 0

CS 4400 - 006 Computer Systems

CS 4400 - 006 Computer Systems

  • Class Number: 14315
  • Instructor: Zhang, Mu
  • Component: Laboratory
  • Type: In Person
  • Units: --
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 15
  • Class Number: 18433
  • Instructor: NAGY, STEFAN
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 62

CS 4500 - 001 Senior Capstone Project

CS 4500 - 001 Senior Capstone Project

  • Class Number: 10054
  • Instructor: DE ST GERMAIN, JOHN
  • Instructor: REGEHR, JOHN
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 13

CS 4600 - 001 Computer Graphics

CS 4600 - 001 Computer Graphics

  • Class Number: 8355
  • Instructor: YANG, YIN
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 63

CS 4710 - 001 Comptr Eng Sr Project

CS 4710 - 001 Comptr Eng Sr Project

  • Class Number: 3660
  • Instructor: BRUNVAND, ERIK
  • Component: Special Projects
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 20

CS 4963 - 001 Alg Foundations of Robotics


Prereqs: CS 3500 AND MATH 1220 AND MATH 2270 AND CS 3130. Algorithmic Foundations of Robotics explores the algorithms that help robots operate in the real world from autonomous cars to manipulators in factories. It covers a range of topics including forward/inverse kinematics, motion planning, simultaneous localization and mapping (SLAM), and optimal control. Students will learn about the algorithms and mathematical principles that enable robots to perceive, reason, and act in the world. By the end of the course, students will have an understanding of the fundamental concepts that drive robotic systems, and will be equipped with the skills to design and implement their own robotic algorithms.

CS 4963 - 001 Alg Foundations of Robotics

  • Class Number: 18431
  • Instructor: HERMANS, TUCKER
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 33

Prereqs: CS 3500 AND MATH 1220 AND MATH 2270 AND CS 3130. Algorithmic Foundations of Robotics explores the algorithms that help robots operate in the real world from autonomous cars to manipulators in factories. It covers a range of topics including forward/inverse kinematics, motion planning, simultaneous localization and mapping (SLAM), and optimal control. Students will learn about the algorithms and mathematical principles that enable robots to perceive, reason, and act in the world. By the end of the course, students will have an understanding of the fundamental concepts that drive robotic systems, and will be equipped with the skills to design and implement their own robotic algorithms.

CS 4991 - 001 CE Senior Thesis I

CS 4991 - 001 CE Senior Thesis I

  • Class Number: 4210
  • Instructor: STEVENS, KENNETH S
  • Component: Special Projects
  • Type: In Person
  • Units: 2.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 15

CS 5150 - 001 Advanced Algorithms

CS 5150 - 001 Advanced Algorithms

  • Class Number: 9354
  • Instructor: PASCUCCI, VALERIO
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 35

CS 5320 - 002 Computer Vision


The course is an introduction to fundamental problems of Computer Vision and main concepts and techniques to solve those. The course starts with the fundamentals of processing and transforming images, extracting features and descriptors, estimating camera pose, and stereo matching. After that, the course covers developing advanced algorithms and machine learning-based techniques, including an introduction to deep neural networks, to address high-level computer vision tasks like 3D reconstruction, detecting and segmenting objects in images, and classifying activities in videos.

CS 5320 - 002 Computer Vision

  • Class Number: 19241
  • Instructor: AL HALAH, ZIAD
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 11

The course is an introduction to fundamental problems of Computer Vision and main concepts and techniques to solve those. The course starts with the fundamentals of processing and transforming images, extracting features and descriptors, estimating camera pose, and stereo matching. After that, the course covers developing advanced algorithms and machine learning-based techniques, including an introduction to deep neural networks, to address high-level computer vision tasks like 3D reconstruction, detecting and segmenting objects in images, and classifying activities in videos.

CS 5350 - 001 Machine Learning

CS 5350 - 001 Machine Learning

  • Class Number: 8744
  • Instructor: Zhe, Shandian
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 55

CS 5353 - 001 Deep Learning

CS 5353 - 001 Deep Learning

  • Class Number: 15346
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 12

CS 5360 - 001 Virtual Reality

CS 5360 - 001 Virtual Reality

  • Class Number: 18437
  • Instructor: Cardona-Rivera, Rogelio E
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 1

CS 5630 - 001 Vis for Data Science

CS 5630 - 001 Vis for Data Science

  • Class Number: 15348
  • Instructor: ROSEN, PAUL
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 29

CS 5710 - 001 Digital VLSI Design


The course fee covers digital course materials through the Inclusive Access program. Students may request to opt out here: https://portal.verba.io/utah/login

CS 5710 - 001 Digital VLSI Design

  • Class Number: 16183
  • Instructor: GAILLARDON, PIERRE-EMMANUEL J
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Fees: $62.94
  • Seats Available: 1

The course fee covers digital course materials through the Inclusive Access program. Students may request to opt out here: https://portal.verba.io/utah/login

CS 5745 - 001 Test/Verif Digital Ckts

CS 5745 - 001 Test/Verif Digital Ckts

  • Class Number: 18706
  • Instructor: KALLA, PRIYANK
  • Component: Activity
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 5960 - 001 Human-AI Alignment


AI systems are becoming increasingly capable and increasingly commonplace in our society. How do we get these AI systems to do what we, as humans, actually want them to do? How do we ensure that increasingly powerful AI systems are safe and beneficial? How can we efficiently leverage human input to improve AI systems and how can we use AI to empower people? We will explore a range of topics including interactive reinforcement learning, shared autonomy, human intent and preference learning, and AI safety and existential risk. Classes will be a mix of lectures covering foundational materials as well as hands-on analysis and exploration of both seminal and recent research papers. Throughout the semester, students will engage in a novel research project, culminating in a final presentation and written technical report. By taking this course, students will develop a broad understanding of the common techniques and unique research challenges involved in building safe and beneficial AI systems that learn from, interact with, and assist humans. Prerequisites: CS 3500 and Calculus II. Full Major Status in Computer Science OR Software Development or Full Minor Status in Computer Science

CS 5960 - 001 Human-AI Alignment

  • Class Number: 16547
  • Instructor: BROWN, DANIEL
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 4

AI systems are becoming increasingly capable and increasingly commonplace in our society. How do we get these AI systems to do what we, as humans, actually want them to do? How do we ensure that increasingly powerful AI systems are safe and beneficial? How can we efficiently leverage human input to improve AI systems and how can we use AI to empower people? We will explore a range of topics including interactive reinforcement learning, shared autonomy, human intent and preference learning, and AI safety and existential risk. Classes will be a mix of lectures covering foundational materials as well as hands-on analysis and exploration of both seminal and recent research papers. Throughout the semester, students will engage in a novel research project, culminating in a final presentation and written technical report. By taking this course, students will develop a broad understanding of the common techniques and unique research challenges involved in building safe and beneficial AI systems that learn from, interact with, and assist humans. Prerequisites: CS 3500 and Calculus II. Full Major Status in Computer Science OR Software Development or Full Minor Status in Computer Science

CS 5961 - 001 Modern Cryptography


Prerequisite: CS 4150. Cryptography is used at scale to secure information at rest or in transit and, recently, to secure computations. This course is a graduate-level course on the foundations of modern cryptography. It is also open to advanced undergraduates. We will cover basic cryptographic tools, their applications for building advanced systems, and a formal mathematical framework to argue about security. The course will have two parts: In Part 1, we will cover basic tools like pseudorandom functions, pseudorandom generators, digital signatures, encryption schemes, hash functions, and their instantiations in practice. In Part 2, we will briefly cover advanced topics, including zero-knowledge proofs, multi-party computation, fully-homomorphic encryption, and the role of cryptography in blockchains. The course will not assume any prior background in cryptography. However, basic mathematical maturity is expected; exposure to undergraduate-level probability, elementary number/group theory, proofs by contradiction, and hardness reductions (in complexity theory) is highly recommended.

CS 5961 - 001 Modern Cryptography

  • Class Number: 19139
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 9

Prerequisite: CS 4150. Cryptography is used at scale to secure information at rest or in transit and, recently, to secure computations. This course is a graduate-level course on the foundations of modern cryptography. It is also open to advanced undergraduates. We will cover basic cryptographic tools, their applications for building advanced systems, and a formal mathematical framework to argue about security. The course will have two parts: In Part 1, we will cover basic tools like pseudorandom functions, pseudorandom generators, digital signatures, encryption schemes, hash functions, and their instantiations in practice. In Part 2, we will briefly cover advanced topics, including zero-knowledge proofs, multi-party computation, fully-homomorphic encryption, and the role of cryptography in blockchains. The course will not assume any prior background in cryptography. However, basic mathematical maturity is expected; exposure to undergraduate-level probability, elementary number/group theory, proofs by contradiction, and hardness reductions (in complexity theory) is highly recommended.

CS 5963 - 001 Cyber-phys Sys & loT Security


Cyber-physical Systems and Internet of Things Security.The widespread deployment of Cyber-physical Systems (CPS) and Internet of Things (IoT) systems has revolutionized the way we interact with the physical world, from smart homes to self-driving cars. However, these systems are also susceptible to cyber attacks, posing a threat to the safety, security, and privacy of users across safety-critical applications. This course provides an introduction to the fundamentals of IoT-CPS security, privacy, and safety, covering real-world attacks and defenses, embedded systems security, cryptography, safety verification, sensors and perception security, and more. Knowledge of Software Practice and C++ (CS 3505) is required. Knowledge of Computer Security (CS 4440) is strongly recommended.

CS 5963 - 001 Cyber-phys Sys & loT Security

  • Class Number: 19545
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 30

Cyber-physical Systems and Internet of Things Security.The widespread deployment of Cyber-physical Systems (CPS) and Internet of Things (IoT) systems has revolutionized the way we interact with the physical world, from smart homes to self-driving cars. However, these systems are also susceptible to cyber attacks, posing a threat to the safety, security, and privacy of users across safety-critical applications. This course provides an introduction to the fundamentals of IoT-CPS security, privacy, and safety, covering real-world attacks and defenses, embedded systems security, cryptography, safety verification, sensors and perception security, and more. Knowledge of Software Practice and C++ (CS 3505) is required. Knowledge of Computer Security (CS 4440) is strongly recommended.

CS 5965 - 001 Social Computing

CS 5965 - 001 Social Computing

  • Class Number: 18430
  • Instructor: KOGAN, MARINA
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 1

CS 5966 - 001 Local Exp for Deep Learning


Prerequisites: CS 5350/DS 4350. Local Explanations for Deep Learning Models:This course will cover concepts, techniques, and evaluation of explanations for individual predictions of deep learning models. We’ll first go over explainability methods that aim to address: Which part of the input led to the predicted label? How to change the prediction to another label? In plain English, why is this input assigned this label? Which training examples caused the prediction? In the second part, we’ll revisit evaluations of these methods and focus on how to develop and evaluate explainability methods that best accomplish a concrete, real-world utility. The course is appropriate for graduate and advanced undergraduate students who completed a machine learning course. Methods and examples in this course will focus on NLP and computer vision.

CS 5966 - 001 Local Exp for Deep Learning

  • Class Number: 16916
  • Instructor: MARASOVIC, ANA
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 17

Prerequisites: CS 5350/DS 4350. Local Explanations for Deep Learning Models:This course will cover concepts, techniques, and evaluation of explanations for individual predictions of deep learning models. We’ll first go over explainability methods that aim to address: Which part of the input led to the predicted label? How to change the prediction to another label? In plain English, why is this input assigned this label? Which training examples caused the prediction? In the second part, we’ll revisit evaluations of these methods and focus on how to develop and evaluate explainability methods that best accomplish a concrete, real-world utility. The course is appropriate for graduate and advanced undergraduate students who completed a machine learning course. Methods and examples in this course will focus on NLP and computer vision.

CS 5969 - 001 Disc Event & Agent Based Sim


Prerequisites: MATH 1220 and CS 3130 and Full Major Status in Computer Science. The course covers fundamental notions of discrete event and agent based modeling and simulation, including: the basics of simulation methodology, useful methods from probability and statistics for characterizing inputs and analyzing results, random number generators, experimental design by developing simulations for a variety of applications (e.g., Unmanned Aircraft Systems Traffic Management) and performing sensitivity, robustness, uncertainty analysis for those simulations.

CS 5969 - 001 Disc Event & Agent Based Sim

  • Class Number: 19420
  • Instructor: HENDERSON, THOMAS
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Wait List: No
  • Seats Available: 25

Prerequisites: MATH 1220 and CS 3130 and Full Major Status in Computer Science. The course covers fundamental notions of discrete event and agent based modeling and simulation, including: the basics of simulation methodology, useful methods from probability and statistics for characterizing inputs and analyzing results, random number generators, experimental design by developing simulations for a variety of applications (e.g., Unmanned Aircraft Systems Traffic Management) and performing sensitivity, robustness, uncertainty analysis for those simulations.

CS 6150 - 001 Graduate Algorithms

CS 6150 - 001 Graduate Algorithms

  • Class Number: 5546
  • Instructor: PASCUCCI, VALERIO
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 10

CS 6210 - 002 Sci. and Data Comp. I

CS 6210 - 002 Sci. and Data Comp. I

  • Class Number: 16243
  • Instructor: BERZINS, MARTIN
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 14

CS 6230 - 001 Parallel Computing HPC

CS 6230 - 001 Parallel Computing HPC

  • Class Number: 12607
  • Instructor: SADAYAPPAN, SADAY
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 29

CS 6310 - 001 Robotics

CS 6310 - 001 Robotics

  • Class Number: 1414
  • Instructor: HOLLERBACH, JOHN
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 37

CS 6320 - 002 Computer Vision


The course is an introduction to fundamental problems of Computer Vision and main concepts and techniques to solve those. The course starts with the fundamentals of processing and transforming images, extracting features and descriptors, estimating camera pose, and stereo matching. After that, the course covers developing advanced algorithms and machine learning-based techniques, including an introduction to deep neural networks, to address high-level computer vision tasks like 3D reconstruction, detecting and segmenting objects in images, and classifying activities in videos.

CS 6320 - 002 Computer Vision

  • Class Number: 19242
  • Instructor: AL HALAH, ZIAD
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 9

The course is an introduction to fundamental problems of Computer Vision and main concepts and techniques to solve those. The course starts with the fundamentals of processing and transforming images, extracting features and descriptors, estimating camera pose, and stereo matching. After that, the course covers developing advanced algorithms and machine learning-based techniques, including an introduction to deep neural networks, to address high-level computer vision tasks like 3D reconstruction, detecting and segmenting objects in images, and classifying activities in videos.

CS 6350 - 001 Machine Learning

CS 6350 - 001 Machine Learning

  • Class Number: 8745
  • Instructor: Zhe, Shandian
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 36

CS 6353 - 001 Deep Learning

CS 6353 - 001 Deep Learning

  • Class Number: 15347
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Wait List: No
  • Seats Available: 1

CS 6360 - 001 Virtual Reality

CS 6360 - 001 Virtual Reality

  • Class Number: 18457
  • Instructor: Cardona-Rivera, Rogelio E
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

CS 6465 - 001 Adv OS Implementation

CS 6465 - 001 Adv OS Implementation

  • Class Number: 18434
  • Instructor: STUTSMAN, RYAN
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: Yes
  • Seats Available: 0

CS 6480 - 001 Adv Computer Networks

CS 6480 - 001 Adv Computer Networks

  • Class Number: 18454
  • Instructor: VAN DER MERWE, JACOBUS
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 5

CS 6520 - 001 Programming Language

CS 6520 - 001 Programming Language

  • Class Number: 18435
  • Instructor: FLATT, Matthew
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: -1

CS 6530 - 001 Adv. Database Systems


This course is a comprehensive study of the internals of the modern database systems and challenges of indexing and querying large-scale data in the context of continuously evolving hardware. It will cover the core concepts and fundamentals of indexing and hashing data structures, concurrency control, storage, file organization, and query processing. The course will study both the in-memory and disk-based database systems and will use examples from modern key-value stores as database systems. All the class projects will be in context of real in-memory and disk-based database systems. The course is appropriate for graduate students in software systems and for advanced undergraduates with systems programming skills. Unofficial pre-requisites: CS 5530 (Undergrad databases), CS 3505 software practice in C/C++

CS 6530 - 001 Adv. Database Systems

  • Class Number: 16532
  • Instructor: PANDEY, PRASHANT
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 17

This course is a comprehensive study of the internals of the modern database systems and challenges of indexing and querying large-scale data in the context of continuously evolving hardware. It will cover the core concepts and fundamentals of indexing and hashing data structures, concurrency control, storage, file organization, and query processing. The course will study both the in-memory and disk-based database systems and will use examples from modern key-value stores as database systems. All the class projects will be in context of real in-memory and disk-based database systems. The course is appropriate for graduate students in software systems and for advanced undergraduates with systems programming skills. Unofficial pre-requisites: CS 5530 (Undergrad databases), CS 3505 software practice in C/C++

CS 6540 - 001 Human/Computer Interact

CS 6540 - 001 Human/Computer Interact

  • Class Number: 13495
  • Instructor: ISAACS, KATE E
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 8

CS 6630 - 001 Vis for Data Science

CS 6630 - 001 Vis for Data Science

  • Class Number: 15350
  • Instructor: ROSEN, PAUL
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 54

CS 6640 - 001 Image Processing


The course fee covers digital course materials through the Inclusive Access program. Students may request to opt out here: https://portal.verba.io/utah/login

CS 6640 - 001 Image Processing

  • Class Number: 6232
  • Instructor: WHITAKER, ROSS
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Fees: $32.94
  • Seats Available: 30

The course fee covers digital course materials through the Inclusive Access program. Students may request to opt out here: https://portal.verba.io/utah/login

CS 6710 - 001 Digital VLSI Design


The course fee covers digital course materials through the Inclusive Access program. Students may request to opt out here: https://portal.verba.io/utah/login

CS 6710 - 001 Digital VLSI Design

  • Class Number: 16181
  • Instructor: GAILLARDON, PIERRE-EMMANUEL J
  • Component: Lecture
  • Type: In Person
  • Units: 4.0
  • Requisites: Yes
  • Wait List: No
  • Fees: $62.94
  • Seats Available: 12

The course fee covers digital course materials through the Inclusive Access program. Students may request to opt out here: https://portal.verba.io/utah/login

CS 6745 - 001 Test/Verif Digital Ckts

CS 6745 - 001 Test/Verif Digital Ckts

  • Class Number: 18707
  • Instructor: KALLA, PRIYANK
  • Component: Activity
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 4

CS 6810 - 001 Computer Architecture

CS 6810 - 001 Computer Architecture

  • Class Number: 10859
  • Component: Lecture
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 42

CS 6960 - 001 Human-AI Alignment


AI systems are becoming increasingly capable and increasingly commonplace in our society. How do we get these AI systems to do what we, as humans, actually want them to do? How do we ensure that increasingly powerful AI systems are safe and beneficial? How can we efficiently leverage human input to improve AI systems and how can we use AI to empower people? We will explore a range of topics including interactive reinforcement learning, shared autonomy, human intent and preference learning, and AI safety and existential risk. Classes will be a mix of lectures covering foundational materials as well as hands-on analysis and exploration of both seminal and recent research papers. Throughout the semester, students will engage in a novel research project, culminating in a final presentation and written technical report. By taking this course, students will develop a broad understanding of the common techniques and unique research challenges involved in building safe and beneficial AI systems that learn from, interact with, and assist humans.

CS 6960 - 001 Human-AI Alignment

  • Class Number: 16555
  • Instructor: BROWN, DANIEL
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Wait List: No
  • Seats Available: 10

AI systems are becoming increasingly capable and increasingly commonplace in our society. How do we get these AI systems to do what we, as humans, actually want them to do? How do we ensure that increasingly powerful AI systems are safe and beneficial? How can we efficiently leverage human input to improve AI systems and how can we use AI to empower people? We will explore a range of topics including interactive reinforcement learning, shared autonomy, human intent and preference learning, and AI safety and existential risk. Classes will be a mix of lectures covering foundational materials as well as hands-on analysis and exploration of both seminal and recent research papers. Throughout the semester, students will engage in a novel research project, culminating in a final presentation and written technical report. By taking this course, students will develop a broad understanding of the common techniques and unique research challenges involved in building safe and beneficial AI systems that learn from, interact with, and assist humans.

CS 6961 - 001 Modern Cryptography


Cryptography is used at scale to secure information at rest or in transit and, recently, to secure computations. This course is a graduate-level course on the foundations of modern cryptography. It is also open to advanced undergraduates. We will cover basic cryptographic tools, their applications for building advanced systems, and a formal mathematical framework to argue about security. The course will have two parts: In Part 1, we will cover basic tools like pseudorandom functions, pseudorandom generators, digital signatures, encryption schemes, hash functions, and their instantiations in practice. In Part 2, we will briefly cover advanced topics, including zero-knowledge proofs, multi-party computation, fully-homomorphic encryption, and the role of cryptography in blockchains. The course will not assume any prior background in cryptography. However, basic mathematical maturity is expected; exposure to undergraduate-level probability, elementary number/group theory, proofs by contradiction, and hardness reductions (in complexity theory) is highly recommended. CS 6150 is a prerequisite.

CS 6961 - 001 Modern Cryptography

  • Class Number: 19144
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 6

Cryptography is used at scale to secure information at rest or in transit and, recently, to secure computations. This course is a graduate-level course on the foundations of modern cryptography. It is also open to advanced undergraduates. We will cover basic cryptographic tools, their applications for building advanced systems, and a formal mathematical framework to argue about security. The course will have two parts: In Part 1, we will cover basic tools like pseudorandom functions, pseudorandom generators, digital signatures, encryption schemes, hash functions, and their instantiations in practice. In Part 2, we will briefly cover advanced topics, including zero-knowledge proofs, multi-party computation, fully-homomorphic encryption, and the role of cryptography in blockchains. The course will not assume any prior background in cryptography. However, basic mathematical maturity is expected; exposure to undergraduate-level probability, elementary number/group theory, proofs by contradiction, and hardness reductions (in complexity theory) is highly recommended. CS 6150 is a prerequisite.

CS 6962 - 001 Decomp Methods Data & Comp Sci


Researchers in a variety of fields collect measurements, observe data, perform simulations and use a wide range of techniques to describe, classify, analyze and draw conclusions from these data. Selecting appropriate techniques and understanding their advantages and disadvantages is an important component of data analysis. In this class, we will survey several decomposition techniques for data and computational science applications including: Principle component analysis, independent component analysis, singular value decomposition, non-negative matrix factorization, low-rank methods, and probabilistic factorization methods.

CS 6962 - 001 Decomp Methods Data & Comp Sci

  • Class Number: 19418
  • Instructor: JOHNSON, CHRISTOPHER
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 13

Researchers in a variety of fields collect measurements, observe data, perform simulations and use a wide range of techniques to describe, classify, analyze and draw conclusions from these data. Selecting appropriate techniques and understanding their advantages and disadvantages is an important component of data analysis. In this class, we will survey several decomposition techniques for data and computational science applications including: Principle component analysis, independent component analysis, singular value decomposition, non-negative matrix factorization, low-rank methods, and probabilistic factorization methods.

CS 6963 - 001 Cyber-phys Sys & IoT Security


Cyber-physical System and Internet of Things Security. The widespread deployment of Cyber-physical Systems (CPS) and Internet of Things (IoT) systems has revolutionized the way we interact with the physical world, from smart homes to self-driving cars. However, these systems are also susceptible to cyber attacks, posing a threat to the safety, security, and privacy of users across safety-critical applications. This course provides an introduction to the fundamentals of IoT-CPS security, privacy, and safety, covering real-world attacks and defenses, embedded systems security, cryptography, safety verification, sensors and perception security, and more. Knowledge of Software Practice and C++ (CS 3505) is required. Knowledge of Computer Security (CS 4440) is strongly recommended.

CS 6963 - 001 Cyber-phys Sys & IoT Security

  • Class Number: 19552
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 27

Cyber-physical System and Internet of Things Security. The widespread deployment of Cyber-physical Systems (CPS) and Internet of Things (IoT) systems has revolutionized the way we interact with the physical world, from smart homes to self-driving cars. However, these systems are also susceptible to cyber attacks, posing a threat to the safety, security, and privacy of users across safety-critical applications. This course provides an introduction to the fundamentals of IoT-CPS security, privacy, and safety, covering real-world attacks and defenses, embedded systems security, cryptography, safety verification, sensors and perception security, and more. Knowledge of Software Practice and C++ (CS 3505) is required. Knowledge of Computer Security (CS 4440) is strongly recommended.

CS 6965 - 001 Social Computing

CS 6965 - 001 Social Computing

  • Class Number: 18608
  • Instructor: KOGAN, MARINA
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: -1

CS 6966 - 001 Local Exp for Deep Learning


Local Explanations for Deep Learning Models: This course will cover concepts, techniques, and evaluation of explanations for individual predictions of deep learning models. We’ll first go over explainability methods that aim to address: Which part of the input led to the predicted label? How to change the prediction to another label? In plain English, why is this input assigned this label? Which training examples caused the prediction? In the second part, we’ll revisit evaluations of these methods and focus on how to develop and evaluate explainability methods that best accomplish a concrete, real-world utility. The course is appropriate for graduate and advanced undergraduate students who completed a machine learning course. Methods and examples in this course will focus on NLP and computer vision.

CS 6966 - 001 Local Exp for Deep Learning

  • Class Number: 16965
  • Instructor: MARASOVIC, ANA
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 13

Local Explanations for Deep Learning Models: This course will cover concepts, techniques, and evaluation of explanations for individual predictions of deep learning models. We’ll first go over explainability methods that aim to address: Which part of the input led to the predicted label? How to change the prediction to another label? In plain English, why is this input assigned this label? Which training examples caused the prediction? In the second part, we’ll revisit evaluations of these methods and focus on how to develop and evaluate explainability methods that best accomplish a concrete, real-world utility. The course is appropriate for graduate and advanced undergraduate students who completed a machine learning course. Methods and examples in this course will focus on NLP and computer vision.

CS 6967 - 001 Security Operations

CS 6967 - 001 Security Operations

  • Class Number: 15333
  • Instructor: XU, JUN
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Wait List: No
  • Seats Available: -2

CS 6968 - 001 Bus Asp of Sec & Privacy


Business Aspects of Security and Privacy. Successful security programs utilize risk management techniques to make effective security control decisions. Regulations, such as GDPR, force companies into adopting security best practices to protect sensitive data. This course covers many compliance and risk management topics, which are necessary to understand in order to be an effective cybersecurity leader and build an effective cybersecurity program.

CS 6968 - 001 Bus Asp of Sec & Privacy

  • Class Number: 15332
  • Instructor: MOHR, HENNER
  • Component: Special Topics
  • Type: In Person
  • Units: 3.0
  • Requisites: Yes
  • Wait List: No
  • Seats Available: 0

Business Aspects of Security and Privacy. Successful security programs utilize risk management techniques to make effective security control decisions. Regulations, such as GDPR, force companies into adopting security best practices to protect sensitive data. This course covers many compliance and risk management topics, which are necessary to understand in order to be an effective cybersecurity leade