Data Analytics - Master of Data Analytics (Online)
The admission requirements for the degree program requires incoming students to have a minimum mathematical preparation at the level of Linear Algebra (MATH 2415 Introduction to Linear Algebra or equivalent course, such as E E 200 Linear Algebra, Probability and Statistics Applications).
The curriculum for the degree program is composed of 34 graduate credits.
| Prefix | Title | Credits |
|---|---|---|
| Foundation | ||
| C S 453 | Python Programming I | 3 |
| or C S 454 | Python Programming II | |
| A ST 511 | Statistical Methods for Data Analytics can be replaced by (A ST 505 and A ST 507) | 3 |
| Select one of the following courses | 3 | |
| R Programming I | 3 | |
| Statistical Analysis with R | 3 | |
| Methodologies | ||
| C S 508 | Introduction to Data Mining | 3 |
| C S 519 | Applied Machine Learning I | 3 |
| or E E 565 | Machine Learning I | |
| Select one of the following courses | 3 | |
| Database Management Systems I | 3 | |
| Database Management Systems | 3 | |
| Web Development and Database Applications | 3 | |
| Advanced Topics and Applications | ||
| Choose nine credits from the following: | 9 | |
| Applied Multivariate Analysis | 3 | |
| Computational Statistics | 3 | |
| Python Programming II | 3 | |
| Computer Science I Transition | 3 | |
| Introduction to Data Structures Transition | 3 | |
| Advanced Methods in Astrophysics | 3 | |
| Business Analytics II | 3 | |
| Advanced Bioinformatics and NCBI Database | 3 | |
| Computer Graphics I | 3 | |
or ICT 460 | Advanced Software Development Concepts | |
| Bioinformatics Programming | 3 | |
| Bioinformatics | 3 | |
| Database Management Systems II | 3 | |
| Digital Image Processing | 3 | |
| Characterizing Time-Dependent Engineering Data | 3 | |
or BCIS 561 | Business Analytics I | |
| Stochastic Processes Modeling | 3 | |
or I E 522 | Queuing Systems | |
| Design and Implementation of Discrete-Event Simulation | 3 | |
| Multimedia Theory and Production | 3 | |
or COMM 5220 | Communication Technologies | |
| Fourier Series and Boundary Value Problems | 3 | |
or STAT 5230 | Elementary Stochastic Processes | |
| Seminar in Social Networks | 3 | |
| Seminar in Text Analysis for the Social Sciences | 3 | |
| Seminar in Data Visualization | 3 | |
| Capstone Experience | ||
| Select one of the following courses | 3 | |
| Master's Project | 3 | |
| Master's Thesis | 1-15 | |
| Independent Study | 1-3 | |
| Special Research Problems | 3 | |
| Independent Study | 1-3 | |
| Master's Technical Report | 3 | |
| Master's Thesis | 3 | |
Internship | ||
| Total Credits | 30 | |
A Suggested Plan of Study
Additional classes may be needed based on placement test results and course prerequisites. Visit with an advisor for help with creating a customized plan.
| First Year | ||
|---|---|---|
| Fall | Credits | |
| A ST 511 | Statistical Methods for Data Analytics | 3 |
| C S 453 | Python Programming I | 3 |
| C S 508 | Introduction to Data Mining | 3 |
| Credits | 9 | |
| Spring | ||
| C S 519 | Applied Machine Learning I | 3 |
| C S 458 | R Programming I | 3 |
| One Elective Course from the list of Advanced Topics and Applications courses | 3 | |
| Credits | 9 | |
| Second Year | ||
| Fall | ||
| Two Elective Coures from the list of Advanced Topics and Applications courses | 6 | |
| C S 502 or ICT 458 | Database Management Systems I or Web Development and Database Applications | 3 |
| Credits | 9 | |
| Spring | ||
| Choose one from the capstone experience group | 3 | |
| Credits | 3 | |
| Total Credits | 30 | |