CHM229H1

Data Analysis in Chemistry

Modern chemistry is increasingly data-driven, with large and complex datasets emerging from high-throughput experimentation, spectroscopy, computational chemistry, and laboratory automation. This course introduces chemistry students to the fundamental concepts and practical skills of data analysis, with a focus on chemical applications. Course content includes descriptive and inferential statistics, data visualization, linear and nonlinear regression, multivariable analysis, dimensionality reduction, and an introduction to predictive modelling and machine learning. These topics are introduced through a chemistry-centred lens and with a continuous focus on ethical data handling. Emphasis is placed on hands-on experience through weekly computer labs using real datasets. Students will develop programming skills using modern, open-source programming tools and libraries that are widely used in scientific research.