In recent years, data science skills have become essential for those pursuing careers in business consulting and data-driven organisations. This course develops quantitative models and computer codes for business and management problems in descriptive, predictive and prescriptive analytics from an operations research (or management science) perspective and discusses their impact. Topics include linear algebra, numerical computing, orthogonal factorisation, clustering, data fitting, regularisation, cross-validation, and numerical optimisation. Applications include forecasting, control, finance, operations and supply chains, and/or marketing. We explain data science and business analytics from the first principle of constructing different learning models and understanding the role of hyperparameters in these models while building them up from scratch. We offer a concise coverage of the core knowledge needed to build new analytical (numerical linear algebra, convex optimisation, and computer programming) models for developing data-driven products and smart business models.