Master of Science in Informatics (Data Science/Data Analytics)
Website: https://twu.edu/informatics/graduate-program/
The M.S. in Informatics program provides graduate students with a flexible, adaptable, interprofessional, and interdisciplinary approach to the study of informatics, delivered in a hybrid learning environment. Majors in this program will build upon a set of foundational courses and choose discipline-specific courses within an approved Application Area (Clinical Applications, Cybersecurity, Data Science/Data Analytics, Health Studies, Sports Informatics, or Community Informatics) to complete the major. The program is delivered collaboratively by Academic Components, including Computer Science, Nursing, Health Studies, Kinesiology, and Library and Information Studies.
Course content for the degree provides a central set of knowledge and skills that all informatics students will possess and then allows students to explore and refine their understanding of informatics as it is applied to high-demand professions and careers.
Majors will learn to use technology and data analytics to derive meaningful information from data for data and decision-driven practice in user-centered systems.
Informatics is the interprofessional study and application of information science, computer science, cognitive science, and organizational science to the arts, sciences, and professions.
Informatics includes a formal study of information, including:
- its structure, properties, uses, and function in society
- the people who use the information and the technologies that are developed to record, organize, store, retrieve, and disseminate the information
Marketable Skills
Defined by the Texas Higher Education Coordinating Board's 60x30 Strategic Plan as, "Those skills valued by employers that can be applied in a variety of work settings, including interpersonal, cognitive, and applied skills areas. These skills can be either primary or complementary to a major and are acquired by students through education, including curricular, co-curricular, and extracurricular activities."
- Work as a member of a project team to coordinate database and project development and determine project scope and limitations.
- Develop and implement procedures for data management, data storage and retrieval, distributed systems, evaluating data quality, data security, data transfer, data analysis, modeling, and visualization.
- Plan, coordinate, and implement security measures to safeguard information in computer files against accidental or unauthorized damage, modification, or disclosure.
- Disseminate research by writing reports, publishing papers, or presenting at professional conferences.
- Design, create, and administer a computer network.
- Demonstrate personal accountability and work habits, integrity, and ethical behavior.
- Proficient in the software tools to achieve the skills listed, including but not limited to Java, Python, Perl, SQL, NoSQL, R, Microsoft Project, Microsoft Visio, Tableau, SAS, or SPSS.
Admissions
All students must meet the University requirements as outlined in the Admission to the TWU Graduate School section of the catalog.
This academic program may have additional admission criteria that must also be completed as outlined on the program's website.
Degree Requirements
Total Semester Credit Hours Required
The degree program consists of a minimum of 36 semester credit hours (SCH) of graduate coursework comprised of 15 SCH of foundations in computer science, 15 SCH of discipline-specific coursework in one of the application areas below, and 3 SCH in software/statistical tools. The program is completed with an interprofessional, interdisciplinary capstone project.
Recommended course sequence
CSCI 5103 should be taken in the first semester of study.
CSCI 5203 should be taken in the first year of study.
Capstone in Informatics should be taken in the last year of study.
All other courses may be taken in any sequence unless a required prerequisite is noted. Contact the advisor if you have any questions.
| Code | Title | SCHs |
|---|---|---|
| Computer Science Core | ||
| Required Courses | ||
| CSCI 5103 | Fundamentals of Informatics | 3 |
| CSCI 5203 | Database Systems | 3 |
| CSCI 5673 | Big Data: Management, Access, and Use | 3 |
| Select two of the following | 6 | |
| Foundations of Information Systems Security | ||
| Data Communication Networks | ||
| Human-Computer Interface | ||
| Data and Information Visualization | ||
| Foundations of Data Science | ||
| Data Warehousing | ||
| Modeling Machine Learning | ||
| Data Mining and Analysis | ||
| Software/Statistical Tools | 3 | |
| Select one of the following (in consultation with advisor) | ||
| Statistical Programming | ||
| Applied Statistics in Health Promotion | ||
| Applied Statistical Principles | ||
| Statistical Methods I | ||
| Statistical Methods II | ||
| Research Methods in Business | ||
| Analysis of Nurse-Generated Data | ||
| Advanced Psychological Statistics I | ||
| Application Area (see options below) | 15 | |
| Interprofessional Capstone | 3 | |
| Select one of the following in consultation with advisor | ||
| Capstone in Informatics | ||
| Capstone in Informatics | ||
| Capstone in Informatics | ||
| Capstone in Informatics | ||
| Capstone in Informatics | ||
| Total SCHs | 36 | |
Application Area: Data Science/Data Analytics Option
| Code | Title | SCHs |
|---|---|---|
| Select five of the following | 15 | |
| Data Communication Networks | ||
| Human-Computer Interface | ||
| Data and Information Visualization | ||
| Foundations of Data Science | ||
| Data Warehousing | ||
| Modeling Machine Learning | ||
| Data Mining and Analysis | ||
| Theory of Probability and Statistics I | ||
| Theory of Probability and Statistics II | ||
| Computer-Aided Mathematical Modeling | ||
| Statistical Methods II | ||
| Applied Statistics and Convex Optimization | ||
| Project Management | ||
| Total SCHs | 15 | |
Cooperative Education
In order for coursework in Cooperative Education to be counted as degree credit, department and advisory committee approval must be received during the semester in which the course is taken. This approval is in addition to approval to enroll in Cooperative Education coursework. Only three semester credit hours of Cooperative Education may be counted toward the Master’s degree.
