Master of Science in Analytics
Curriculum
The M.S. in Analytics curriculum comprises 21 credit hours of required courses and nine credit hours of approved elective course work. The standard program is a three-semester, lock-step, cohorted offering. However, working professionals can complete the program on a part time basis, can extend the length of the program, and also take courses in the summer. Full time students also have the option of completing the program in 12 months by taking their electives in the summer.
Course Sequence
Summer
- MSA 8005 Mathematical Foundations for Analytics(Not a required course, offered to students who want to refresh math skills or lack advanced calculus and linear algebra knowledge)
Fall 1
- MSA 8010
- MSA 8040
- MSA 8100
- MSA 8190
Spring
- MSA 8050
- MSA 8150
- MSA 8200
- MSA 8600
Summer
- Internship (optional)
Fall 2
- Elective 1
- Elective 2
- Elective 3
Fall 1
- MSA 8010
- MSA 8040
Spring
- MSA 8050
- MSA 8150
Summer
- Internship (optional)
- Elective 1
Fall 2
- MSA 8190
- Elective 2
Spring 2
- MSA 8100
- MSA 8200
Required Courses
8 Courses | 21 Hours
- MSA 8010 – Data Programming for Analytics (3 hours)
View a sample syllabus - MSA 8040 – Data Management for Analytics (3 hours)
View a sample syllabus - MSA 8100 – Optimization Methods for Analytics (1.5 hours)
View a sample syllabus - MSA 8150 – Machine Learning for Analytics (3 hours)
View a sample syllabus - MSA 8190 – Statistical Foundations for Analytics (3 hours)
View a sample syllabus - MSA 8200 – Econometric Modeling for Analytics (3 hours)
View a sample syllabus - MSA 8050 Scalable Data Analytics (3 hours)
View a sample syllabus - MSA 8600 Deep Learning Analytics (1.5 hours)
View a sample syllabus
Electives
4 Courses | 12 Hours
- MSA 8770 – Text Analytics (3 hours)
- MSA 8500 – Image Analytics (3 hours)
- MSA 8650 –Image and Text Analytics with Deep Neural Networks (3 hours)
- FI 8460 – Introduction to FinTech (3 hours)
Other Electives
- CIS 8020 – Systems Integration (3 hours)
- CIS 8100 – Management of Information Systems (3 hours)
- CIS 8200 – Information Systems Strategy (3 hours)
- FI 8000 – Valuation of Financial Assets (3 hours)
- FI 8200 – Financial Derivatives (3 hours)
- FI 8260 – Hedge Fund Strategies (3 hours)
- FI 8320 – Corporate Financial Strategy (3 hours)
- HA 8160 – Health Care System (3 hours)
- HA 8550 – Health Planning and Financial Management (3 hours)
- HA 8620 – Operations Management and Quality in Health Care (3 hours)
- HA 8670 – Health Information Systems (3 hours)
- HA 8750 – Data Analytics
- MK 8010 – Marketing Metrics (3 hours)
- MK 8705 – Digital Marketing Analytics (3 hours)
- MK 8715 – Brand and Consumer Analytics (3 hours)
- MK 8730 – Marketing Engineering (3 hours)
- MRM 8610 – Financial Engineering (3 hours)
- MRM 8620 – Quantitative Financial Risk Models (3 hours)
- MGS 8730 – Project Management (3 hours)
- MGS 8740 – Operations Strategy (3 hours)
- RCB 8040 – Competing on Analytics & Organizational Knowledge (3 hours)
- MGS 8110 – Applied Regression Analysis (3 hours)
- RMI 8050 – Risk Management Modeling (3 hours)
- RMI 8300 – Predictive Risk Models (3 hours)
Bootcamps
Besides the eight required and three elective courses, students will participate various bootcamps such as Linear Algebra, R Programming, Data Visualization, Tableau, Advanced R, Big Data Programming, SAS, etc.
Sprint Projects
MSA students normally participate Sprint projects during the study. The Sprint projects are real industry projects with several characteristics:
- Industry partners provide real problems with data for insights and solutions
- Student teams work with faculty from Institute for Insights and other departments at GSU as well as company participants
- Weekly meetings during six to ten weeks period for feedback
- Skill and methodology trainings if needed