School of Computing Graduate Handbook – 2015-2016

**MS IN COMPUTING: **

DATA MANAGEMENT & ANALYSIS

A student may pursue an MS with a (1) thesis option, or (2) a project option, or (3) a course-only option. The minimum number of

credits for any of the three options is 30 from graduate level classes. A maximum of 6 project hours or 9 thesis hours is allowed to be

included in the program of study for students in the project or the thesis option. A minimum of 6 hours of thesis research is required

for the thesis option.

**TRACK FACULTY**

Tom Fletcher, Chris Johnson, Sneha Kumar Kasera, Mike Kirby, Feifei Li,** **Miriah Meyer, Valerio Pascucci, **Jeff Phillips **

**(Track Director)**, Vivek Srikumar, Hari Sundar, Suresh Venkatasubramanian

**COURSE CLASSES**

Required courses: must take 4 required courses.

CS 6150

Advanced Algorithms

CS 6530

Database Systems

CS 6140

Data Mining /or/ CS 6350 Machine Learning

CS 6630

Visualization

A minimum of a B or greater is required for any of the required courses.

Students may substitute other SoC graduate-level courses for elective requirements with approval of the Track Director (especially

those taught by track faculty). With approval of the supervisory committee, a student may take two elective courses (6 credit hours)

at the graduate level or higher from other departments, excluding independent study, seminars and research credit. Students may

place out of the above requirements by substituting or transferring courses from other institutions at the discretion of the Track

Director.

In all three options, seminar hours cannot be included to fulfill the 30 graduate level credits requirement. Independent study credit

hours can only be used on the Program of Study for students who pursue the project based degree. However, once a student enters

the project or the thesis option, his/her prior independent study or thesis research hours can be converted into project or thesis

hours whichever is applicable, if the student’s advisor deems these hours relevant to the student’s project or thesis.

**13**

**ELECTIVES**

:

Three courses from the following list are required: ( /or/ CS 6140/CS 6350 if not counted above)

CS 7960

Models of Computation for Massive Data

CS 6210

Advanced Scientific Computing

CS 6230

High-Performance Computing and Parallelization

CS 6300

Artificial Intelligence

CS 6390

Probabilistic Modeling

CS 6640

Image Processing

CS 6340

Natural Language Processing

CS 6170

Computational Topology

CS 6160

Computational Geometry

CS 6235

Parallel Programming for GPUs/Many Course/Multi-Cores

CS 6480

Advanced Computer Networks

**ALGORITHMICS**

**ANALYTICS**

**MANAGEMENT**

CS 6490

Network Security

School of Computing Graduate Handbook – 2015-2016

**PHD IN COMPUTING: **

DATA MANAGEMENT & ANALYSIS

Course work listed on the approved Program of Study form must comprise at least 50 semester hours of graduate course

work and dissertation research, exclusive of independent study. At least 14 semester hours of dissertation research (CS 7970)

and 24 semester hours of graduate course work must be included. Up to 12 hours of graduate level course work already ap-

plied to other degrees may be used in the program of study as approved by the track director. Students may place out of the

following requirements by substituting or transferring courses from other institutions at the discretion of the track director.

**TRACK FACULTY**

Tom Fletcher, Chris Johnson, Sneha Kumar Kasera, Mike Kirby, Feifei Li, Miriah Meyer, Valerio Pascucci, **Jeff **

**Phillips (Track Director),** Vivek Srikumar, Hari Sundar, Suresh Venkatasubramanian

**30**

**COURSE CLASSES**

Required courses: must take 4 required courses.

CS 6150

Advanced Algorithms

CS 6530

Database Systems

CS 6140

Data Mining /or/ CS 6350 Machine Learning

CS 6630

Visualization

A student must take four elective courses (twelve hours) which involve the areas related to data, or are directly applicable

to the student’s dissertation research. Up to three courses (nine hours) may be taken from other departments at the Univer-

sity of Utah. All elective courses on the Program of Study must be taught at the graduate level. For those classes taken within

the School of Computing, the students needs to take 6000 level courses and above when available/appropriate. In addition

to the following electives, other 6000 level and above classes taught by track faculty are also typically allowed as electives.

All courses taken by a track student to fulfill the elective requirements must be approved by the student’s committee and the

track director.

**ELECTIVES**

Three courses from the following list are required: (or CS 6140/CS 6350 if not counted above, or appropriate classes by

track

faculty)

CS 7960

Models of Computation for Massive Data

CS 6210

Advanced Scientific Computing

CS 6230

High-Performance Computing and Parallelization

CS 6300

Artificial Intelligence

CS 6390

Probabilistic Modeling

CS 6640

Image Processing

CS 6340

Natural Language Processing

CS 6170

Computational Topology

CS 6160

Computational Geometry

CS 6235

Parallel Programming for GPUs/Many Course/Multi-Cores

CS 6480

Advanced Computer Networks

CS 6490

Network Security

**ALGORITHMICS**

**MANAGEMENT**

**ANALYTICS**

School of Computing Graduate Handbook – 2015-2016

**MS IN COMPUTING:**

DATA MANAGEMENT & ANALYSIS

**POTENTIAL OUT-OF-DEPARTMENT ELECTIVES**

• MATH 5080 Statistical Inference I

• MATH 5090 Statistical Inference II

• MATH 5250 Matrix Analysis

• MATH 6010 Linear Models

• MATH 6020 Multilinear Models

• MATH 6070 Mathematical Statistics

• MATH 6210 Real Analysis

• MATH 7870 Methods of Optimization

• ECE 5510 Random Processes

• ECE 6540 Estimation Theory

• ECE 6520 Information Theory and Coding

• BMI 6020 Foundations of Bioinformatics

• BMI 6105 Statistics for Biomedical Informatics

• BMI 6470 Biomedical Infomation Retrieval