Johns Hopkins University 3 credits Computer Science
This is the second course of a two-course accelerated advanced engineering math excursion that provides a comprehensive foundation in mathematical techniques essential for engineering and applied sciences. Students will study core topics in linear algebra, multivariate calculus, probability, and statistics, with emphasis on practical applications. The linear algebra portion covers matrices, systems of linear equations, determinants, matrix inverses, and eigenvalues/eigenvectors. In multivariate calculus, students will learn vector differential calculus (gradient, divergence, curl) and vector integral calculus, including line, surface, and volume integrals, as well as Green’s theorem, Stokes’ theorem, and the divergence theorem. The probability and statistics modules introduce combinatorics, random variables, probability distributions, Bayesian inference, hypothesis testing, confidence intervals, and linear regression. Students will also gain hands-on experience using Excel for statistical analysis. Prerequisite(s): EN.605.156 Calculus for Engineers
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