Topics include techniques of integration, applications of integration, differential equations, sequences, series, and Taylor series.

Topics include techniques of integration, applications of integration, differential equations, sequences, series, and Taylor series.

This course is for students who have not studied calculus and who have the necessary precalculus background. It presents rates of change and their applications, integrals, the fundamental theorem, and modeling of phenomena in the natural and social sciences. All students are required to complete the online self assessment of precalculus skills before the course begins.

This course is for students who have not studied calculus and who have the necessary precalculus background. It presents rates of change and their applications, integrals, the fundamental theorem, and modeling of phenomena in the natural and social sciences. All students are required to complete the online self assessment of precalculus skills before the course begins.

This course provides an overview of statistical methods, their conceptual underpinnings, and their use in various settings taken from current news, as well as from the physical, biological, and social sciences. Topics will include exploring distributions and relationships, planning for data production, sampling distributions, basic ideas of inference (confidence intervals and hypothesis tests), inference for distributions, and inference for relationships, including chi-square methods for two-way tables and regression.

This course provides an overview of statistical methods, their conceptual underpinnings, and their use in various settings taken from current news, as well as from the physical, biological, and social sciences. Topics will include exploring distributions and relationships, planning for data production, sampling distributions, basic ideas of inference (confidence intervals and hypothesis tests), inference for distributions, and inference for relationships, including chi-square methods for two-way tables and regression.

Tired of writing programs that nobody ever uses? Then, this is the course for you. Software enables enterprises to carry out previously tedious or impossible tasks, but many organizations lack the resources to develop needed software. You will apply your programming skills to develop and deliver software to meet the requirements of a client from the community. You will learn critical communication skills required to work with a client, work as a team with classmates, and experience the software lifecycle from requirements elicitation through delivery.

How does Mapquest find the best route between two locations? How do computers help to decode the human genome? At the heart of these and other complex computer applications are nontrivial algorithms. While algorithms must be specialized to an application, there are some standard ways of approaching algorithmic problems that tend to be useful in many applications. Among other topics, we will explore graph algorithms, greedy algorithms, divide-and-conquer, dynamic programming, and network flow.