M.S. in Data Analytics
Mission
Flowing from the mission of Saint Elizabeth University (SEU), the mission of the M.S. in Data Analytics Program is to strive for excellence in engaged teaching and learning by training students to acquire analytical skills a
The program seeks to emphasize the provision of educational opportunities to students with diverse backgrounds and experienc<source-footnote ng-version="0.0.0-PLACEHOLDER"></source-footnote>EM fields and aspires to engender in all of its students the requisite knowledge and skill sets needed to apply statistical and computing methods and tools for large-scale data processing and modeling.
Goals
- Professional Readiness: To equip students with the skill sets necessary to become data analytics professionals.
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Methodological Competency: To develop competencies in selecting appropriate analytical methods and computing tools for large-scale data processing and analysis.
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Technical Training: To offer training in data collection, preparation, processing, manipulation, management, and visualization.
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Communication Skills: To develop competencies in problem-solving skills and effective verbal and written communication of results to diverse audiences.
Student Learning Outcomes
Graduates of the M.S. in Data Analytics Program will:
- Theoretical Mastery: Develop an in-depth understanding of the mathematics, statistics, and computing of data analytics techniques and technologies used to solve crucial data-driven problems and assist with analytics-driven decision-making.
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Tool Application: Be able to choose and a
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Strategic Integration: Be able to integrate computing technology and data science to maximize the value of data.
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Effective Communication: Be able to communicate the analytics results clearly and effectively to a variety of audiences.
Degree Requirements
The program requires the successful completion of 28-31 credit hours. All students must take the following courses:
Required Courses (28 Credits)
| CS601 | Foundations of Analytics | 3 |
| CS603 | Database Design and Management | 3 |
| CS613 | Cryptography and Data Security | 3 |
| CS617 | Data Analysis and Visualization | 3 |
| CS625 | Data Mining | 3 |
| CS631 | Statistical Methods | 3 |
| CS637 | Time Series and Forecasting | 3 |
| CS657 | Machine Learning: Principles and Techniques | 3 |
| MC626 | Ethical Issues | 3 |
| CS697 | Capstone | 1 |
Optional Open Elective Course (3 Credits)