On-Campus Summer Undergraduate Courses

Differential and integral calculus. Includes analytic geometry, functions, limits, integrals and derivatives, polar coordinates, parametric equations, Taylor's theorem and applications, infinite sequences and series. Some applications to the physical sciences and engineering will be discussed, and the courses are designed to meet the needs of students in these disciplines.

Calculus of Several Variables. Calculus of functions of more than one variable: partial derivatives, and applications; multiple integrals, line and surface integrals; Green's Theorem, Stokes' Theorem, and Gauss' Divergence Theorem.

Prerequisite: Grade of C- or better in AS.110.107 (Calculus II For Biological and Social Science) or AS.110.109 (Calculus II For Physical Sciences and Engineering) or AS.110.113 (Honors Single Variable Calculus) or AS.110.201 (Linear Algebra) or AS.110.212 (Honors Linear Algebra) or AS.110.302 (Differential Equations and Applications), or a 5 on the AP BC exam.

This course introduces fundamental programming concepts and techniques, and is intended for all who plan to develop computational artifacts or intelligently deploy computational tools in their studies and careers. Topics covered include the design and implementation of algorithms using variables, control structures, arrays, functions, files, testing, debugging, and structured program design. Elements of object-oriented programming. algorithmic efficiency and data visualization are also introduced. Students deploy programming to develop working solutions that address problems in engineering, science and other areas of contemporary interest that vary from section to section. Course homework involves significant programming. Attendance and participation in class sessions are expected.

Prerequisite: Students may not have earned credit in the following courses: EN.500.113 (Gateway Computing: Python), EN.500.114 (Gateway Computing: Matlab), EN.500.202 (Computation and Programming for Materials Scientists and Engineers), EN.500.132 (Bootcamp: JAVA), EN.500.133 (Bootcamp: Python), or EN.500.134 (Bootcamp: Matlab).

This course introduces fundamental programming concepts and techniques, and is intended for all who plan to develop computational artifacts or intelligently deploy computational tools in their studies and careers. Topics covered include the design and implementation of algorithms using variables, control structures, arrays, functions, files, testing, debugging, and structured program design. Elements of object-oriented programming. algorithmic efficiency and data visualization are also introduced. Students deploy programming to develop working solutions that address problems in engineering, science and other areas of contemporary interest that vary from section to section. Course homework involves significant programming. Attendance and participation in class sessions are expected.

This course is scheduled to run Monday, Wednesday, and Friday between 12 p.m. and 3 p.m.

Prerequisite: Students may not have earned credit in the following courses: EN.500.112 (Gateway Computing: JAVA), EN.500.114 (Gateway Computing: Matlab), EN.500.202 (Computation and Programming for Materials Scientists and Engineers), EN.500.132 (Bootcamp: JAVA), EN.500.132 (Bootcamp: JAVA), or EN.500.134 (Bootcamp: Matlab).

Vector spaces, matrices, and linear transformations. Solutions of systems of linear equations. Eigenvalues, eigenvectors, and diagonalization of matrices. Applications to differential equations.

This course is scheduled to run Monday, Tuesday, Wednesday, and Thursday, between 9 a.m. and 11:30 a.m.

Prerequisite: Grade of C- or better in AS.110.107 (Calculus II For Biological and Social Science) or AS.110.109 (Calculus II For Physical Sciences and Engineering) or AS.110.113 (Honors Single Variable Calculus) or AS.110.202 (Calculus II) or AS.110.302 (Differential Equations and Applications), or a 5 on the AP BC exam.

Mathematics for Sustainability covers topics in measurement, probability, statistics, dynamics, and data analysis. In this course, students will analyze, visually represent, and interpret large, real data sets from a variety of government, corporate, and non-profit sources. Through local and global case studies, students will engage in the mathematics behind environmental sustainability issues and the debates centered on them. Topics include climate change, natural resource use, waste production, air and water pollution, water scarcity, and decreasing biodiversity. The software package R is used throughout the course.

Prerequisites: Comfort with algebraic expressions and functions. No prior experience in coding is required.

Is the mind identical to the brain? Is the mind (or brain) a computer? Could a computer reason, have emotions, or be morally responsible? This course examines such questions philosophically and historically. Topics include the history of AI research from 1940s to present; debates in cognitive science related to AI (computationalism, connectionism, and 4E cognition); and AI ethics.

This course provides students with the background necessary for the study of calculus. It begins with a review of the coordinate plane, linear equations, and inequalities, and moves purposefully into the study of functions. Students will explore the nature of graphs and deepen their understanding of polynomial, rational, trigonometric, exponential, and logarithmic functions, and will be introduced to complex numbers, parametric equations, and the difference quotient.