Data Management and Analytics

Undergraduate

Definition and overview of Big Data. Application of data science and analytics in business and industry to reveal historic patterns and operations insights; and to facilitate data-supported decision-making and strategic planning. Methods of data gathering, cleaning, exploration, visualization, analysis, exploration, and manipulation, including: statistical analysis and modelling, predictive modelling, optimization, and inference. Overview of data challenges: bias, modelling, and threats to validity in generalizations and predictions. Generative AI and Large Language Models, and their applications for business. Use of Python and R programs. (Prerequisites: GENG-2102, GENG-2220, MATH-2780.) (3 hours lecture and 1.5 hours tutorial/lab per week.) (This is an experiential learning course.)