Computer Science M.S.: Data Science

The CPSC-DS M.S. program requires a student to complete a minimum of 33 semester hours in graduate work including the thesis, or 36 semester hours in graduate work including a graduate project. Students admitted to the program who lack academic experience in certain areas will be required to complete up to 18 hours of additional course work of the foundation courses listed below in order to gain needed competencies. All students admitted to the M.S. program must complete 15 semester hours of required computer science core courses and 6 semester hours of required DS core courses listed below. The program also includes 6 hours of DS elective courses in one of five areas. Students may elect to undertake a project in lieu of a thesis. The student in consultation with his/her major adviser and the program graduate coordinator can select an additional 6 hours of elective coursework in an area of interest within or outside of computer science of they choose project option. In this case, 6 additional hours of DS elective coursework and 6 additional hours of elective course in the student’s interest area, for a minimum total of 36 hours of graduate credit, are required. The courses used for these additional 6 elective hours are subject to the approval of the major adviser and the Graduate Coordinator. With either the thesis or project option, a minimum of 21 hours of credit must be from UTC computer science courses at the 5000 level. Students must maintain a minimum 3.0 grade point average and are subject to all general regulations of The Graduate School, such as those regulating admission to candidacy, transfer of credits, time limitations, thesis, and degree conferral.

Project Option (36 credit hours)

Computer Science Core Courses
CPSC 5100 Computer Programming Languages 3
CPSC 5550 Client-Server Systems 3
CPSC 5800 Advanced Topics in Systems Software 3
CPSC 5700 Advanced Computer Architecture 3
CPSC 5210 Design and Analysis of Computer Algorithms 3

At least 6 hours Data Science Core Courses

CPSC 5440 Introduction to Machine Learning 3
CPSC 5240 Principles of Data Analytics 3
CPSC 5180 Programming Languages for Advanced Data 3
CPSC 5530 Data Visualization and Exploration 3

Plus at least 6 hours chosen from one of five data science areas:

Math Area
MATH 5130 Introduction to Probability and Statistics 3
MATH 5140 Mathematical Statistics 3
MATH 5150 Introduction to Biostatistics 3
MATH 5160 Applied Statistical Methods 3
MATH 5300 Mathematics of Interest 3
MATH 5350 Mathematics of Finance 3

Business Area

MGT 5200 Advanced Data Analytics 3
MGT 5190 Data Mining and Analytics 3
MGT 5180 Advanced Queries and Business Reports 3

Biology and Environmental Science Area

ESC 5120 Applied Statistics for Environmental Scientists 3
ESC 5610 Advanced Applications of Remote Sensing and Geographic Information Systems 3-4
ESC 5610L Advanced Applications of Remote Sensing & Geographic Information Systems Laboratory 0
ESC 5660 Geographic Information Systems 3-4
ESC 5660L Geographic Information Systems Laboratory 0

Engineering Management Area

ENGM 5040 Decision Making and Optimization Techniques 3
ENGM 5580 Advanced Engineering Economy 3
ENGM 5520 Reliability Engineering 3
ENGM 5850 Technical Innovation 3

Information Security and Assurance Area

CPSC 5600 Advanced Biometrics and Cryptography 3
CPSC 5610 Advanced Information Security Management 3
CPSC 5620 Computer Network Security 3
CPSC 5660 System Vulnerability Analysis and Auditing 3
CPSC 5670 Database Security and Auditing 3
CPSC 5680 Computer Forensics 3

Unrestricted Electives

Courses related to the student’s degree objectives may be chosen from the Computer Science Electives or from an area(s) other than computer science in consultation with the adviser and Graduate Coordinator. 6 credits.

Project

CPSC 5900 Project 3

Total 36 Credit Hours

Thesis Option (36 credit hours)

Computer Science Core Courses
CPSC 5100 Computer Programming Languages 3
CPSC 5550 Client-Server Systems 3
CPSC 5800 Advanced Topics in Systems Software 3
CPSC 5700 Advanced Computer Architecture 3
CPSC 5210 Design and Analysis of Computer Algorithms 3

At least 6 hours Data Science Core Courses

CPSC 5440 Introduction to Machine Learning 3
CPSC 5240 Principles of Data Analytics 3
CPSC 5180 Programming Languages for Advanced Data 3
CPSC 5530 Data Visualization and Exploration 3

Plus at least 6 hours chosen from one of five data science areas:

Math Area
MATH 5130 Introduction to Probability and Statistics 3
MATH 5140 Mathematical Statistics 3
MATH 5150 Introduction to Biostatistics 3
MATH 5160 Applied Statistical Methods 3
MATH 5300 Mathematics of Interest 3
MATH 5350 Mathematics of Finance 3

Business Area

MGT 5200 Advanced Data Analytics 3
MGT 5190 Data Mining and Analytics 3
MGT 5180 Advanced Queries and Business Reports 3

Biology and Environmental Science Area

ESC 5120 Applied Statistics for Environmental Scientists 3
ESC 5610 Advanced Applications of Remote Sensing and Geographic Information Systems 3-4
ESC 5610L Advanced Applications of Remote Sensing & Geographic Information Systems Laboratory 0
ESC 5660 Geographic Information Systems 3-4
ESC 5660L Geographic Information Systems Laboratory 0

Engineering Management Area

ENGM 5040 Decision Making and Optimization Techniques 3
ENGM 5580 Advanced Engineering Economy 3
ENGM 5520 Reliability Engineering 3
ENGM 5850 Technical Innovation 3

Information Security and Assurance Area

CPSC 5600 Advanced Biometrics and Cryptography 3
CPSC 5610 Advanced Information Security Management 3
CPSC 5620 Computer Network Security 3
CPSC 5660 System Vulnerability Analysis and Auditing 3
CPSC 5670 Database Security and Auditing 3
CPSC 5680 Computer Forensics 3

Thesis

CPSC 5999r Thesis 6

Total 33 Credit Hours