Data Science & Analytics at Â鶹ŮÀÉ is about turning data into insight and action. You’ll learn to collect, analyze, and interpret data to solve real-world problems in business, science, government, and beyond. This field blends mathematics, computer science, and domain knowledge to help organizations make smarter decisions, predict trends, and create new opportunities.
About Data Science & Analytics at Â鶹ŮÀÉ
Florida Atlantic’s programs are truly interdisciplinary, drawing on expertise from the College of Business, College of Science, College of Engineering and Computer Science, College of Arts and Letters, and College of Social Work and Criminal Justice. You’ll work with faculty from multiple fields and choose from several concentrations, including business, engineering, natural sciences, and society. The curriculum is designed for flexibility, so you can tailor your studies to your career goals. You’ll also gain hands-on experience through capstone projects, research, and access to the latest tools and technologies.
Degrees Offered at Florida Atlantic
Undergraduate
- Bachelor of Science in Data Science & Analytics (BSDSA)
- Concentrations: Business, Engineering, Natural Sciences, Society
Graduate
- Master of Science in Data Science & Analytics (MSDSA)
- Concentrations: Business, Engineering, Scientific Inquiry, Society
- Ph.D. with concentration in Information Technology and Operations Management
Certificates
- Big Data Analytics Graduate Certificate
- Undergraduate and graduate certificates in related areas (e.g., Artificial Intelligence, Business Analytics)
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Educational Objectives & Student Outcomes
2. Equip graduates with interdisciplinary skills spanning mathematics, statistics, computer science, and domain-specific knowledge.
3. Foster the ability to communicate data-driven insights to diverse audiences.
4. Encourage ethical and responsible use of data in decision-making.
2. Apply statistical and machine learning techniques to real-world datasets.
3. Design and implement solutions to data-driven challenges in various industries.
4. Work effectively in interdisciplinary teams and communicate findings clearly.
5. Engage in continuous learning to keep pace with advances in data science and analytics.
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