7 courses with the subject CMPS, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
An introduction to the basics of personal computers and applications using Microsoft Office, including word processing, spreadsheets, presentations, email, and database management. Course is offered online and requires students to work independently.
This introduction to computer science, developed by Google and their university partners, emphasizes problem solving and data analysis skills along with computer programming skills. Using Python, students will learn design, implementation, testing, and analysis of algorithms and programs. Within the context of programming, students will learn to formulate problems, think creatively about solutions, and express those solutions clearly and accurately. Problems will be chosen from real-world examples such as graphics, image processing, cryptography, data analysis, and video games. Open to first year students. Prerequisite: q. (Q) Hollins University 2026–27 Undergraduate Catalog Page 320
Students will study fundamental data structures and their applications to problem solving. Object-oriented programming (OOP) is introduced, and OOP techniques are explored, including inheritance, polymorphism, interfaces, and abstract classes. Software engineering concepts of design principles and testing methods are also covered.
Introduces students to the importance of gathering, cleaning, normalizing, visualizing and analyzing data to drive informed decision-making, no matter the field of study. Real-world datasets will be analyzed using a combination of tools and techniques, including spreadsheets, Python, and SQL. Students will learn to ask good, exploratory questions and develop metrics for designing a well-thought-out analysis. Presenting and discussing an analysis of datasets will be an important component of the course. Open to first year students.
Independent study conducted below the advanced level. Application must be made with faculty prior to registration.
An introduction to machine learning with a focus on understanding the mathematics of learning and optimization. Topics include gradient descent, linear and logistic regression, and neural network learning. Prerequisite/Corequisite: MATH 241 and CMPS 260 or permission. Offered Term 1, alternating years.
Students will study supervised and unsupervised strategies for data analysis and predictive modeling. Topics include decision trees, clustering, principal components analysis, and association rule learning. Prerequisite/Corequisite: MATH 241 and CMPS 260 or permission. Offered Term 1, alternating years. Hollins University 2026–27 Undergraduate Catalog Page 321
Source: Hollins University's catalog, linked per course · table learning_unit · CourseShelf publish 59
