Data Science Five-Year Accelerated Degree Bachelor of Arts and Master of Science Program
A five-year degree program is offered in Data Science at Fairfield University's School of Engineering and Computing, leading to a Bachelor of Arts in Computer Science and a Master of Science in Data Science. This program embraces the educational objectives of the BA in Computer Science program, as well as those of the graduate program in Data Science. It emphasizes experiential learning and innovation.
Data science is an interdisciplinary field that uses scientific methods, processes, and systems to extract knowledge or insights from both structured and unstructured data. Building on foundations in statistics and computer science—including machine learning, classification, cluster analysis, uncertainty quantification, computational science, data mining, databases, and visualization—data science also leverages domain-specific knowledge for effective application. Today, the field increasingly integrates advanced AI tools and techniques, such as generative AI, deep learning, and even quantum computing, which are taught as part of our elective coursework. This modern approach provides students with a broader skill set and prepares them for the evolving landscape of data-driven discovery by offering a balanced curriculum that includes introductory data science, cutting-edge AI, and emerging technologies.
Students having achieved a 3.0 GPA, may apply to the Master’s degree program at the end of their third year. Students follow the standard undergraduate curriculum for the first three years, and then complete the BA baccalaureate degree requirements (122 credits) during their fourth year. During this final year, students may enroll in up to two graduate courses that are above and beyond their undergraduate degree requirement. These graduate courses may not be applied towards the undergraduate degree. After receiving the baccalaureate degree, students will take an additional eight courses (for a total of ten courses) to complete the MS degree requirements in the fifth year.
| Code | Title | Credits |
|---|---|---|
| All Requirements for BA in Computer Science 1 | 122 | |
| MATH 5417 | Applied Statistics I | 3 |
| SWEG 5322 | Visual Analytics | 3 |
| SWEG 6508 | Data Warehouse Systems | 3 |
| SWEG 6518 | Data Mining and Business Intelligence | 3 |
| Concentration Courses | ||
| Complete two courses in one of the following concentration areas: 2 | 6 | |
Health Analytics | ||
| Healthcare Economics and Marketing | ||
| Finance and Quality Management in Healthcare Organizations | ||
Computational Analytics | ||
| Database Management Systems | ||
| Pattern Recognition | ||
Social Analytics | ||
| Race, Cities, and Poverty | ||
| American Class Structure | ||
| Sociology of Education | ||
| Graduate Electives | ||
| Select two additional graduate-level electives from the following: 4 | 6 | |
Computing Technical Electives | ||
| Cloud Computing | ||
| Introduction to Data Science | ||
| Artificial Intelligence | ||
| Machine Learning | ||
| Deep Learning | ||
| Quantum Algorithms and Applications | ||
| Generative AI and Applications | ||
| Algorithms | ||
| Advanced Database Concepts | ||
| Applications and Data Security | ||
Mathematics Electives | ||
| Applied Statistics II | ||
| Probability Theory | ||
| Statistics Theory | ||
| Capstone Sequence | ||
| SWEG 6961 | Capstone Professional Project I | 3 |
| SWEG 6962 | Capstone Professional Project II | 3 |
| Total Credits | 152 | |
- 1
Requirements are the same as those for the BA in Computer Science.
- 2
The two graduate concentration courses, to be taken during the final year of undergraduate study, are in addition to the required 122 credits for the BA, and will be applied to the graduate degree.
- 3
Electives may be chosen from courses listed, SWEG 5990 Independent Study, or any other graduate-level course from a concentration or another area, under advisement of the academic advisor and department chair.
- 4
Please consult with program director.
Note: A minimum of 30 credits must be completed at the graduate level.
