The goal of this program is for you to learn the intellectual concepts and skills that are essential for advanced work in computer science and beneficial for computing work in support of other disciplines. You will achieve a deeper understanding of increasingly complex computing systems by acquiring knowledge and skills in mathematical abstraction, problem solving, and the organization and analysis of hardware and software systems. The program covers material such as algorithms, data structures, computer organization and architecture, logic, discrete mathematics, and programming in the context of the liberal arts. The program is compatible with the model curriculum developed by the Association for Computing Machinery's Liberal Arts Computer Science Consortium.
Program content will be organized around four interwoven themes. The computational organization theme covers concepts and structures of computing systems, from digital logic to the computer architecture and assembly language supporting high-level languages and operating systems. The programming theme concentrates on learning how to design and code programs to solve problems. The mathematical theme helps develop mathematical reasoning, theoretical abstractions, and problem-solving skills needed for computer scientists. A technology and society theme explores social, historical, or philosophical topics related to science and technology. Students will participate in faculty-guided enrichment opportunities in science and mathematics, including community-based learning.
We will explore these themes throughout the program by way of lectures, programming labs, workshops, and seminars.
To successfully participate in the program students need access to a computer and reliable internet service. Students should expect up to 16 hours of synchronous meeting time per week using Zoom and Canvas. Students will have access to alternatives to synchronous participation if conditions require and can work with faculty to pursue these alternatives to earn related credit.
Course Reference Numbers
Students must have completed the equivalent of at least one quarter of computer programming and must demonstrate strong mathematical skills in precalculus or calculus. Contact Richard Weiss at firstname.lastname@example.org with evidence of prior course work that demonstrates these skills.
Course Reference Numbers
Computer Science, Cybersecurity, Data Science, Mathematics Education