Data Analytics, Master of Science
*Note: the curriculum for MS Data Analytics will go into effect with students commencing study on or after Term 2, 2021.
The Master of Science in Data Analytics program's mission is to provide graduate learners with the skills needed to be successful data analysts, operational analysts, and leaders in a competitive global Information Technology arena. Learners will develop a complete and thorough understanding of key technologies that constitute data science, statistics, data mining, problem analysis, big data, and decision making. Students will be provided with theoretical foundations and hands-on experience in Data Analytics. The program will enable students to develop technical skills, including quantitative analysis and data analysis techniques, by participating in competency-based projects focused on developing, integrating, deploying, and managing data to solve real-world problems. The program uses sound practices, current, and emerging tools and technologies, and effective teamwork approaches. Most importantly, these topic areas are integrated throughout the curriculum. The concepts and theories learned in the program are applied to the capstone that combines academic and professional development.
At the end of the program, students are able to:
- Define and identify problems that can be addressed through data analysis
- Gather data from a variety of public and private sources, including web-mining and database interrogation
- Analyze data for patterns and trends
- Find and test predictive models that describe data
This program typically takes 28 months to complete for part-time enrollment and 14 months to complete for students enrolled full-time.
Additional Admissions Requirements for MS Data Analytics:
Students with an undergraduate degree in an unrelated field are required to demonstrate competency in IT core areas. Competency can be demonstrated by completing approved coursework prior to beginning graduate studies at Stratford University, or by completing appropriate bridge or equivalent courses as determined through academic advisement (when prerequisites may be waived). Courses are to be completed at Stratford University, or through Prior Learning Assessment. Example equivalent courses for advisement are as follows: CIS 144 or CIS 201 or CIS 253, CIS 256 or CIS 258, and CIS 146 or CIS 225. Total bridge course requirement for non-IT students is 3.
Student must have taken college level math. If no math has been taken, student must take MAT111 as a bridge course.
Required courses for MS in Data Analytics (12 core) = 12 courses or 54 credit hours
Core Requirements (12 courses or 54 credits)
| CIS 630 | Security Analytics | 4.5 |
| CIS 644 | Cyber Security Method of Analysis | 4.5 |
| CIS 648 | Enterprise Data Architecture | 4.5 |
| CIS 646 | Data Analytics Capstone | 4.5 |
| CIS 598 | Current Topics in Machine Learning | 4.5 |
| CIS 642 | Big Data Analysis | 4.5 |
| ISM 510 | Information Management Analysis and Design | 4.5 |
| ISM 521 | Database Systems Technology | 4.5 |
| CIS 565 | Theory of Machine Learning | 4.5 |
| SOF 510 | Data Structures and Algorithms | 4.5 |
| CIS 553 | Python Programming | 4.5 |
| MAT 610 | Statistics | 4.5 |
| Total Credit Hours: | 54.0 |
*Note: the curriculum for MS Data Analytics will go into effect with students commencing study on or after Term 2, 2021.