COURSE CURRICULUM

The Data Science program at Waterloo blends core courses in computer science, statistics, and mathematics to equip students with the technical expertise required to extract insights from complex datasets. Students begin by building foundational programming skills through courses such as CS135 or CS145 and progress through data structures, algorithms, operating systems, and database management. They explore advanced topics like distributed computing (CS451), machine learning (CS480), and artificial intelligence (CS486), and apply statistical methods through courses including STAT330, STAT331, STAT341, and STAT440. Mathematics courses such as calculus, algebra, linear algebra, combinatorics, and probability provide the theoretical foundation to support computational approaches. Students also take specialized electives in areas like data visualization, forecasting, statistical learning, and generalized linear models. With options to pursue advanced studies, such as an honours thesis (CS499T) or 600/700-level courses, students tailor their learning to specific interests. A breadth requirement ensures exposure to non-math disciplines, helping graduates apply their skills across domains. Whether working with medical imaging, financial data, or cloud-based analytics, graduates of the program are well-prepared for careers in data science, software development, AI, and analytics across diverse industries such as healthcare, tech, business, and government.