Semester:
Offered:
Students will learn to code in Python to solve mathematical and statistical problems in science and engineering, using real data such as epidemiological data for predicting the spread of the SARS-Cov-2 virus, financial data for risk assessment, and climate time series for calculating global trends. Students will learn to analyze and fit real data, calculate and propagate uncertainty, extract parameter values from data, and explore how the sampling of data affects inferences and prediction, while being aware of numerical approximation errors, overfitting, and model limitations. Students should be familiar with calculus at the level of Math 1b. No previous experience in programming, data science, or statistics is expected. The course will develop coding skills from a foundational level up through fairly sophisticated concepts and applications.