Program Overview
The Master of Science in Computational and Data Sciences prepares students for leadership roles in computational and data-driven fields, providing a strong foundation in the theory and application of algorithms, quantitative methods, and artificial intelligence.
The program emphasizes advanced computational skills and enables students to apply computational methods and data-driven approaches to theoretical and applied challenges across disciplines rooted in AUB’s longstanding strengths in the natural, social, and medical sciences, as well as the arts and humanities.
Students from different quantitative backgrounds are brought to a common foundation through the program’s core courses and then develop depth and breadth through field-specific and other electives, allowing them to pursue computational and data science methods within a range of disciplinary contexts and research directions.
The program caters to both theoretical and practical interests, with opportunities to study scientific or social phenomena, address questions in engineering and industry, conduct original research, and explore complex, data-rich problems using computational tools. It is also committed to preparing students for careers in computational and data sciences and to building local and regional expertise in these fields.
Program Learning Outcome
Students who complete the proposed MS program successfully are expected to have achieved the following learning outcomes:
- Apply algorithms, quantitative methods, and AI solutions to data and to problems in science, engineering, society, or industry;
- Assess the limitations of data, methods and algorithms;
- Communicate findings of research or problem solutions to the research community or to the industry.
- Account for the ethical and societal consequences, and privacy concerns in the practice of computational data sciences.