Introduction
The BS Data Science program is designed to shape forward-thinking professionals capable of driving innovation through data. With a strong foundation in statistical methods, programming, and big data technologies, students are prepared to extract actionable insights from both structured and unstructured data.
The curriculum integrates rigorous academic content with applied learning, ensuring students develop the technical skills and critical thinking needed to solve complex, real-world problems. Courses span mathematics, machine learning, data engineering, and visualization, building a versatile skill set aligned with modern industry demands.
Students learn to manage large datasets efficiently and uncover insights through mining, cleaning, and visualization. Through hands-on projects, exposure to cutting-edge tools, and industry collaborations, graduates emerge well-equipped for competitive roles in data science and analytics or for pursuing advanced studies in the field.
PEOs
The DS Graduates will be able to:
- Demonstrate the ability to apply and design DS acquired skills in data-driven, data analysis, data modeling, and providing holistic solutions to meet organizational needs across a variety of industries, both domestically and globally.
- Develop lofty professional standards, ethics, communication skills, and societal concerns which will lead a graduate to work as member or team leader for their professional pursuits and communities.
- Improve professional growth through lifelong learning activities such as research, advancement updates and learning, and continuing higher education.
PLOs
Drawing from the Seoul Accord’s internationally recognized standards, the program focuses on:
- PLO1: Academic Education
- PLO2: Knowledge for Solving Computing Problems
- PLO3: Problem Analysis
- PLO4: Design/Development of Solutions
- PLO5: Modern Tool Usage
- PLO6: Individual and Team Work
- PLO7: Communication
- PLO8: Computing Professionalism and Society
- PLO9: Ethics
- PLO10: Life-long Learning
Career Prospects
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Business Intelligence Analyst
- Data Engineer
- AI Engineer
- Big Data Analyst
- Quantitative Analyst