Computational and Data-Enabled Science & Engineering (M.S.)
Overview
The Master of Science (M.S.) in Computational and Data-Enabled Science & Engineering (CDS&E) program is an interdisciplinary program, which includes the disciplines of Biology, Chemistry, Computer Science, Engineering, Physical Sciences, and Mathematics & Statistical Sciences. Jackson State University already has strong undergraduate and graduate degree programs in these traditional areas. A PhD program in CDS&E started in the Fall of 2014. The M.S. program in Computational and Data-Enabled Science & Engineering requires a minimum of 36 credit hours beyond the bachelor’s degree. The M.S. program in CDS&E serves as a feeder program for the PhD program in CDS&E and will provide a foundation for students to successfully pursue the doctoral program and employment outside of the academy. The program shares resources with the existing STEM programs and operates under the College of Science, Engineering, and Technology (CSET). The M.S. in CDS&E can be completed with a thesis or project.
Curriculum
Project Option
| Code | Title | Hours |
|---|---|---|
| Core Courses | ||
| CSC 620 | DATABASE MANAGEMENT SYSTEMS | 3 |
| CSC 552 | APPLIED PROGRAMMING | 3 |
| CSC 601 | COMPUTER ALGORITHMS | 3 |
| STAT 661 | PROBABILITY AND STATISTICS | 3 |
| or STAT 672 | COMPUTATIONAL STATISTICS | |
| Required Courses | ||
| Select one of the following tracks: 1 | 9 | |
| Track 1: Computational Biology and Bioinformatics | ||
BIO 605 | ||
BIO 619 | ||
BIO 679 | ||
| Track 2: Computational Mathematics and Statistical Sciences | ||
| COMPUTATIONAL METHODS N MATH I | ||
| COMPUTATIONAL STATISTICS | ||
| QUANTITATIVE EXPLORATN OF DATA | ||
| Track 3: Computational Physical Science | ||
PHY 522 | ||
PHY 533 | ||
PHY 561 | ||
| Track 4: Computational Science and Engineering | ||
| PARALLEL & DISTRIBUTED COMPUTI | ||
| PROGRAMMING FOR BIG DATA | ||
| MACHINE LEARNING | ||
| Elective Courses | ||
| 12 credit hours of Elective courses 2 | 12 | |
| Project | ||
| Select one of the following from the following disciplines: | 3 | |
BIO 600 | ||
CHEM 579 | ||
| INFO SYST & DEVELOP PROJ | ||
MATH 598 | ||
SCI 587 | ||
| Total Hours | 36 | |
- 1
A student will choose a particular track for the required courses after consultation with the graduate advisor.
- 2
Elective Courses will be approved by the student's graduate committee.
Thesis Option
| Code | Title | Hours |
|---|---|---|
| Core Courses | ||
| CSC 520 | 3 | |
| CSC 552 | APPLIED PROGRAMMING | 3 |
| CSC 601 | COMPUTER ALGORITHMS | 3 |
| STAT 661 | PROBABILITY AND STATISTICS | 3 |
| or STAT 672 | COMPUTATIONAL STATISTICS | |
| Required Courses | ||
| Select one of the following tracks: 1 | 9 | |
| Track 1: Computational Biology and Bioinformatics | ||
BIO 605 | ||
BIO 619 | ||
BIO 679 | ||
| Track 2: Computational Mathematics and Statistical Sciences | ||
| COMPUTATIONAL METHODS N MATH I | ||
| COMPUTATIONAL STATISTICS | ||
| QUANTITATIVE EXPLORATN OF DATA | ||
| Track 3: Computational Physical Science | ||
PHY 522 | ||
PHY 533 | ||
PHY 561 | ||
| Track 4: Computational Science and Engineering | ||
| PARALLEL & DISTRIBUTED COMPUTI | ||
| PROGRAMMING FOR BIG DATA | ||
| MACHINE LEARNING | ||
| Elective Courses | ||
| 9 credit hours of Elective courses 2 | 9 | |
| Thesis | ||
| Select one of the following from one of the following disciplines | 6 | |
| THESIS RESEARCH | ||
| THESIS RESEARCH | ||
| THESIS RESEARCH | ||
| THESIS | ||
SCI 599 | ||
| Total Hours | 36 | |
- 1
A student will choose a particular track for the required courses after consultation with the graduate advisor.
- 2
Elective Courses will be approved by the student's graduate committee.
Elective Courses
Elective Courses will be approved by the student's graduate committee. A list of elective courses is given below (the elective courses can be taken from one or more tracks):
| Code | Title | Hours |
|---|---|---|
| BIO 623 | SYSMS BIO & SIGNALING NETWORKS | 3 |
| BIO 689 | ADVD TPCS IN COMPUTATIONAL BIO | 3 |
| MATH 543 | NUMERICAL ANALYSIS | 3 |
| MATH 628 | ADVD PARTIAL DIFF EQUATIONS I | 3 |
| MATH 629 | ADVND PARTIAL DIF EQUATIONS II | 3 |
| MATH 671 | COMPUTATNL METHODS IN MATH II | 3 |
| MATH 700 | TPCS N MATH & STATS A N CDS&E | 3-6 |
| STAT 661 | PROBABILITY AND STATISTICS | 3 |
| STAT 680 | CMPTNL DATA ANLYSIS & VISUAL I | 3 |
| CHEM 531 | BIOCHEMISTRY | 3 |
| CHEM 558 | QUANTUM CHEMISTRY | 3 |
| CSC 511 | OBJECT-ORIENTED PROGRAMMING | 3 |
| CSC 537 | CLOUD COMPUTING | 3 |
| CSC 582 | SOCIAL NETWORK ANALYSIS | 3 |
| CSC 634 | BIG DATA MINING | 3 |
| CSC 641 | NETWORK SCIENCE | 3 |
| CPE 505 | ANALYSIS OF ALGORITHMS | 3 |
Special Requirements
To become a candidate for the Master of Science in Computational and Data Enabled Sciences and Engineering, student will have to:
-
Take and pass the Graduate Area Comprehensive Examination (GACE) on the 4 core courses. The eligibility criteria for taking the GACE will be the same as that set by the Graduate School (This requirement is waived for CDS & E Ph.D. students who have passed the Comprehensive Qualifying Examinations). A student will have two chances of passing the GACE exam on the 4 core courses.
-
Additionally, the student will need to present and defend his/her master’s Project or Thesis to a committee comprised of the student advisor and committee members.