COURSE CURRICULUM

Applied Data Science at Thompson Rivers University is a 60-credit, two-year program designed for students who already hold a bachelor’s degree and want to build strong skills in data science, analytics, and computing. The curriculum is structured to combine statistics, programming, databases, and machine learning with practical, real-world applications. In the early part of the program, students are introduced to data science fundamentals such as programming tools (commonly Python and R), data manipulation, data visualization, and introductory statistical analysis. Courses also cover database systems, data collection methods, and data cleaning techniques so you can work with structured and unstructured datasets. As the program progresses, students study advanced topics including multivariate statistics, regression analysis, statistical learning, optimization methods, and predictive modeling. Machine learning is a key component, where you learn algorithms such as classification models, clustering methods, neural networks, and model evaluation techniques. The curriculum also includes integrated practice courses and project-based learning where you apply skills to real datasets and industry problems. Capstone project courses in the final stage require you to work on a supervised, real-world data science project, often in collaboration with external clients. Throughout the program, emphasis is placed on ethical data use, communication of insights, and decision-making through analytics, preparing you for careers in data analysis and data science.