# Computer Science Major & Minor

The effects of computer science on the world are hardly hidden. The advent of the computer has brought sweeping changes to business, economics, science and technology. It has also revolutionized daily life—from how we bank, cook and shop to how we work and interact with family and friends. Computer science students aren’t just learning about the computer systems that will allow us to maintain our current lifestyle; they are learning the fundamentals of the field so they can push boundaries and develop the breaking technologies that will continue to improve how we live.

The computer science program prepare students exceptionally well for careers or graduate study. Students who have interests in other science programs find that both the mathematics and computer science degrees dovetail nicely to other scientific disciplines. The department offers academic contests, a colloquium series, summer research, independent study projects and study abroad opportunities that round out the degrees, preparing students for some of the fastest growing and highest paying occupations in the United States.

Beginning fall 2020:

Computer Science majors may choose to add a concentration in Data Science and Statistics. Data Science is an emerging interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge from data. The Data Science and Statistics (DSS) Concentration for Computer Science majors at University of Richmond is designed to supplement the major, grounding the student with a solid theoretical foundation while building the strong analytic skills that are needed to work with large and/or complex data sets. The DSS concentration prepares students for graduate study in the statistical sciences and supports students who aim for careers in any emerging area of data science.

# The Computer Science Major

**Note:** The grade point average of the coursework comprising the major must be no less than 2.00 with no computer science course grade below C- (1.70). Students are strongly advised to consult with faculty in planning their major curriculum.

#### For the Bachelor of Arts degree

11.5 units, including:

CMSC 150 Introduction to Computing

CMSC 221 Data Structures with Lab

CMSC 222 Discrete Structures for Computing

CMSC 240 Software Systems Development

CMSC 301 Computer Organization

CMSC 315 Algorithms

CMSC 323 Design and Implementation of Programming Languages

Three additional 1-unit CMSC electives at the 300 level. Without departmental approval, no more than one of these courses can be an Independent Study course.

MATH 211 Calculus I

MATH 245 Linear Algebra

#### For the Bachelor of Science degree

14.5 units, including:

CMSC 150 Introduction to Computing

CMSC 221 Data Structures with Lab

CMSC 222 Discrete Structures for Computing

CMSC 240 Software Systems Development

CMSC 301 Computer Organization

CMSC 315 Algorithms

CMSC 323 Design and Implementation of Programming Languages

Three additional 1-unit CMSC electives at the 300 level. Without departmental approval, no more than one of these courses can be an Independent Study course.

MATH 211 Calculus I

MATH 212 Calculus II

MATH 245 Linear Algebra

Two units at the 300 level or above in mathematics or two units (or more) beyond the introductory level in one of the following fields: physics (200 level or above), chemistry (200 level or above), or biology (beyond 205).

MATH 300 may not be used to meet the 300-level MATH option for the BS degree

**Note:** Any MATH and CMSC double-major, or MATH major with CMSC minor, having earned at least an A- in MATH 300 may exempt from CMSC 222 but is required to complete an additional CMSC 300-level elective to complete the CMSC major or minor.

# The Computer Science Minor

**Note:** The grade point average of the coursework comprising the minor must be no less than 2.00 with no computer science course grade below C- (1.70). Students are strongly advised to consult with faculty in planning their minor curriculum.

Five and a half units, including:

CMSC 150 Introduction to Computing

CMSC 221 Data Structures with Lab

CMSC 222 Discrete Structures for Computing

CMSC 240 Software Systems Development

CMSC 301 Computer Organization or CMSC 315 Algorithms

One elective unit chosen from:

A 1-unit 300-level Computer Science elective or

A 1-unit computationally intensive upper level course from another department approved by the computer science faculty.

# The Data Science and Statistics Concentration

The concentration in data science and statistics with a major in computer science requires six units (where applicable, these may also count for major requirements).

CMSC 327 Machine Learning (may replace with MATH 389 Statistical Learning)

MATH 235 Multivariate Calculus

MATH 289 Introduction to Data Science

MATH 329 Probability

Two units, chosen from:

CMSC 325 Database Systems

CMSC 326 Simulation

CMSC 395 Selected Topics (with approval)

ECON 270 Introductory Econometrics

MATH 330 Mathematical Statistics

MATH 396 Selected Topics in Mathematics

**Note:** Students completing a concentration in data science and statistics may not minor in mathematics or computer science.