The MSc CODS program consists of a minimum of 30 credit hours distributed as follows: 12 credit hours of Program Core courses, 9 credit hours of Program Elective courses, 9 credit hours of Master’s Thesis and a zero credit Research Methods course. The components of the program are summarized in the table below.
Students seeking the degree of MSc in Computational Data Science must successfully complete a minimum 30 credit hours as specified in the program requirements detailed below, with a minimum CGPA of 3.0. Course selection should be made in consultation with the student’s Main Advisor. All courses have a credit rating of three credits each, except the Seminar in Research Methods and the Master’s Thesis.
Program Core (12 credit hours)
Students must complete the core courses listed below.
Core Courses
Program Electives and Concentrations (9 credit hours)
Students must select three courses from the list below. Subject to approval of the Main Advisor and the Associate Dean for Graduate Studies, students can select one elective course (3 credit hours) from the MSc in Computer Science or the MSc in Electrical and Computer Engineering programs at KU.
Program Elective Courses
| CODS 612 | Computational Methods and Optimization in Finance | 3 |
| CODS 623 | Health Data Science | 3 |
| CODS 624 | Space-Time Data Science | 3 |
| CODS 626 | Financial Derivatives and Risk Management | 3 |
| CODS 630 | Advanced Computer Networks | 3 |
| CODS 631 | Blockchain Fundamentals and Applications | 3 |
| CODS 634 | Artificial Intelligence | 3 |
| CODS 635 | Deep Learning Systems Design | 3 |
| CODS 636 | Introduction to High Performance Computing | 3 |
| CODS 637 | GPU Programming | 3 |
| CODS 640 | Financial Cyber Security | 3 |
| CODS 641 | Natural Language Proc. & Info. Retrieval | 3 |
| CODS 642 | Database Systems Concepts and Design | 3 |
| CODS 643 | Mobile and Pervasive Computing | 3 |
| CODS 644 | Data Science for Business Applications | 3 |
| CODS 645 | Financial Machine Learning | 3 |
| CODS 650 | Data Processing and Visualization | 3 |
| CODS 694 | Selected Topics in Computational Data Science | 3 |
Concentration in Computational Systems
The MSc CODS program offers an optional concentration in Computational Systems. Students choosing this concentration are expected to attain the following concentration specific learning outcomes:
- Demonstrate proficiency in analysis and design of major aspects of computational systems for data science applications.
In addition to program specific core courses, students who opt for the concentration in Computational Systems must complete a minimum of three courses (9 credit hours) from the list below and a thesis within the domain of the concentration. The concentration will be specified on the student’s official transcript.
Concentration Courses
| CODS 630 | Advanced Computer Networks | 3 |
| CODS 631 | Blockchain Fundamentals and Applications | 3 |
| CODS 635 | Deep Learning Systems Design | 3 |
| CODS 636 | Introduction to High Performance Computing | 3 |
| CODS 637 | GPU Programming | 3 |
| CODS 642 | Database Systems Concepts and Design | 3 |
| CODS 643 | Mobile and Pervasive Computing | 3 |
Concentration in Data Analytics
The MSc CODS program offers an optional concentration in Data Analytics. Students choosing this concentration are expected to attain the following concentration specific learning outcomes:
- Apply advanced data analytic techniques to a range of application domains.
In addition to program specific core courses, students who opt for the concentration in Data Analytics must complete a minimum of three courses (9 credit hours) from the list below and a thesis within the domain of the concentration. The concentration will be specified on the student’s official transcript.
Concentration Courses
Master’s Thesis (minimum 9 credit hours)
Students must complete a Master’s Thesis that involves creative, research-oriented work within the field of computational data science, under direct supervision of a faculty advisor from the Electrical Engineering Department or Computer & Information Engineering Department or the Mathematics Department, and at least one other full-time faculty who acts as a co-advisor. The outcome of research should demonstrate the synthesis of information into knowledge in a form that may be used by others. The research findings must be documented in a formal thesis and defended successfully in a viva voce examination. Furthermore, the research should lead to publishable quality scholarly articles.
Thesis