Two-week course for Stanford Pre-Collegiate Studies Summer Institutes. Overview of methods in modern artificial intelligence; development of mathematical and programming proficiency in machine learning and optimization, including supervised learning, unsupervised learning, and reinforcement learning techniques.
Spring 2018 Fall 2018 Spring 2019
Numerical and analytical simulation of physical problems in sciences and engineering using applied methods; developing and using numerical techniques for physical problems described by nonlinear algebraic equations, ordinary and partial differential equations.
Differentiation and integration techniques and their applications (area, volumes, work), improper integrals, approximate integration, analytic geometry, vectors, infinite series, power series, Taylor series, computer algebra.
Study of functions, graphs of polynomial and rational functions, radical functions, exponential and logarithmic functions, inequalities, trigonometric functions, fundamental identities, right triangles, trigonometric equations.