COURSE CURRICULUM

The Bachelor of Science in Data Science is a 120-unit program designed to prepare students for careers in data-driven industries by combining strong foundations in mathematics, statistics, and computer science with advanced training in data analysis, machine learning, and computational methods. The program begins with major preparation coursework in calculus, linear algebra, discrete mathematics, probability, statistical programming in R, technical writing, and ethics in science, ensuring students develop both quantitative reasoning and professional communication skills. These foundational courses support the more advanced study of computational and analytical techniques used throughout the major.The core of the program includes training in programming and data structures, database systems, big data processing, data visualization, artificial intelligence, machine learning, and algorithms. Students gain hands-on experience working with real-world datasets and modern computing tools, preparing them to design and implement solutions for complex data-centric problems. A senior project course allows students to integrate their knowledge in a practical, real-world setting, often involving collaborative or applied research work.In addition to core requirements, students complete a set of electives that allow them to specialize in areas such as computer vision, cybersecurity, networks, bioinformatics, algorithms, or advanced programming topics. They also take domain field electives from another discipline to develop interdisciplinary expertise, which is essential for applying data science techniques in fields like business, healthcare, engineering, or social sciences.The program emphasizes not only technical proficiency but also ethical awareness and responsible use of data, ensuring graduates understand the societal implications of data-driven decision-making. Overall, the BS in Data Science equips students with the analytical, computational, and problem-solving skills needed for careers as data scientists, data analysts, machine learning engineers, and research professionals in both industry and government sectors.