University of OregonWebsiteAcademic Catalog
Computer ScienceDepartment Website
BS Degree in Computer Sciencesource 1source 2
CS Courses
- Principles of Programming LanguagesCS 425 (4)plsCS 425: Principles of Programming Languages
Syntax and semantics. Scope rules, environments, stores, denoted and expressed values, procedures, and parameters. Definitional interpreters. Types, overloading, parametric polymorphism, and inheritance. Varieties of abstraction.
- One upper-division Math or CS Theory course
Math/Stat Courses
- orCalculus for the Biological Sciences IMATH 246 (4)mathMATH 246: Calculus for the Biological Sciences I
For students in biological science and related fields. Emphasizes modeling and applications to biology. Differential calculus and applications. Sequence. Students cannot receive credit for more than one of MATH 241, MATH 246, MATH 251.
Calculus for the Biological Sciences IIMATH 247 (4)mathMATH 247: Calculus for the Biological Sciences IIFor students in biological science and related fields. Emphasizes modeling and applications to biology. Integral calculus and applications. Students cannot receive credit for more than one of MATH 242, MATH 247, MATH 252.
or - pick 2
Elementary Linear AlgebraMATH 341 (4)mathMATH 341: Elementary Linear AlgebraVector and matrix algebra; n-dimensional vector spaces; systems of linear equations; linear independence and dimension; linear transformations; rank and nullity; determinants; eigenvalues; inner product spaces; theory of a single linear transformation. Sequence.
Probability and Statistics for Data ScienceMATH 345M (4)mathMATH 345M: Probability and Statistics for Data ScienceIntroduction to probability and statistics, with an emphasis upon topics relevant for data science. Multilisted with DSCI 345M. Students cannot get credit for both MATH 343 and DSCI 345M/MATH 345M.
Fundamentals of Number Theory IMATH 347 (4)mathMATH 347: Fundamentals of Number Theory IA study of congruences, the Chinese remainder theorem, the theory of prime numbers and divisors, Diophantine equations, and quadratic reciprocity. Development of mathematical proof in these contexts. Sequence with MATH 348.
Statistical Methods IMATH 425 (4)mathMATH 425: Statistical Methods IStatistical methods for upper-division and graduate students anticipating research in nonmathematical disciplines. Presentation of data, sampling distributions, tests of significance, confidence intervals, linear regression, analysis of variance, correlation, statistical software.
Science Courses
Program Learning Outcomes
Upon successful completion of this program, students will be able to:
- Demonstrate technical competency in the main areas of computer science, including theoretical foundations, computer systems, programming languages, and software development.
- Draw on a broad knowledge of computer science to design, implement, and test software solutions to significant problems in a variety of areas.
- Understand the broad applicability and impacts of computing; be proficient in one or more subareas of computer science or applied computer science.
- Adapt and extend fundamental knowledge and skills to new problem domains and emerging technologies.
- Communicate and collaborate with others as part of a project team, and express ideas orally and in writing.
- Recognize professional responsibilities and make informed judgments in computing practice based on ethical principles.