Mathematics Curriculum
The Department of Mathematics wishes to share the beauty and usefulness of mathematics and computer science with as many undergraduates as possible; to provide training in analytical thinking; to prepare majors for advanced work in mathematics, computer science, and related fields; and to provide the background for various kinds of employment after graduation.
The faculty adheres to the philosophy that the only way to learn mathematics is to do it. Regular written assignments enable the student and faculty to monitor the student’s progress and to verify the accuracy of the substance and style of the work.
The Department’s emphasis is on strengthening the student’s problem-solving skills.
Degree Requirements
- Mathematics BA
- Mathematics BS
- Mathematics minor
- Computer Science minor
- Data Science interdisciplinary minor
Course Catalog
Computer Science
The study of computer science offers students the opportunity to develop problem solving facility and helps develop skills which have broad utility in theory and application and are amongst the most sought-after by employers. The abstraction of real-world problems, the construction of algorithms to display and transform data, and the theory of computation are all central concerns of computer science.
The department offers several Computer Science degrees including game development and cybersecurity. Learn more at www.randolphcollege.edu/computer-science.
Independent Study for Non-Majors
The Department is pleased to offer independent study courses for one semester hour each on the application of mathematics to such fields as economics and business, political science, psychology, biology, chemistry, cryptology, linguistics, and physics. These courses are intended primarily for students in other disciplines who have done well in mathematics but do not wish to take additional three-hour mathematics courses.
Interested students should contact the Department.
Course Offerings
Below is a list of available courses offered by the mathematics department. Consult the Registrar’s Office and the College Catalog for official course listings.
CSCI 1131 - Introduction to Computer Science With Python
Open to students with little or no programming experience. Basics of computation and the role it can play in problem solving. By the end of the course, students will be able to write programs in Python that allow them to accomplish useful goals. Credit hours: 4. Offered every year.
CSCI 1151 - Computer Programming I
An introduction to computers and computer programming. Emphasis will be placed on problem-solving with examples and exercises from social, natural, and mathematical sciences. Techniques of flowcharting and structured programming, development of algorithms, and types of computer hardware will also be discussed. Intended for students with no previous programming experience. Credit hours: 3. A student may not receive credit for this course after taking CSCI 1156 or its equivalent.
CSCI 1151L - Computer Programming I Laboratory
Hands-on application of the topics studied in CSCI 1151. Credit hours: 1. Prerequisite or Corequisite: CSCI 1151 or the equivalent.
CSCI 1156 - Computer Programming II
A continuation of Computer Science 1151. Emphasis on top-down programming using methods. Topics include user-defined classes and advanced data types, arrays, recursion, algorithms for sorting and searching, exception handling, advanced GUIs and graphics, and embedding Java applets into HTML documents. Credit hours: 4. Prerequisite: CSCI 1151 or the equivalent.
CSCI 1156L - Computer Programming II Laboratory
Hands-on application of the topics studied in CSCI 1156. Credit hours: 1. Prerequisite or Corequisite: CSCI 1156 or the equivalent.
CSCI 2252 - Data Structures
Students will study abstract data types and their implementation. Arrays, lists, stacks, queues, trees, heaps, hash tables, maps, and graphs are considered. Fundamental algorithms including list manipulation, sorting, graph searches and tree traversals are also covered. Credit hours: 4. Prerequisite: CSCI 1156 or the equivalent.
CSCI 2256 - Algorithms
Students will study techniques for designing and analyzing algorithms. The design techniques including divide-and-conquer, dynamic programming, greediness and probabilistic approaches will be covered. An analysis of best/average/worst case complexity in both time and space will be covered. Credit hours: 4. Prerequisite or Corequisite: MATH 2236 or the equivalent.
CSCI 2290 - Independent Study
CSCI 3326 - Computer Architecture and Assembly Language
Introduction to internal computer architecture including the instruction cycle, parts of the CPU, memory hierarchy including caching, pipelining, exception handling, and issues of multiprocessing. Implementation of assembly language programs using sample architectures. Principles of translating high-level languages. Credit hours: 3. Pre- or co-requisites: CSCI 2251 and MATH 1149 or equivalent.
CSCI 3328 - Computer Networks
Introduction to the design and analysis of computer networks. Topics include application layer protocols, Internet protocols, network interfaces, local and wide area networks, wireless networks, bridging and routing. Credit hours: 4. Prerequisites: CSCI 1156 and MATH 2236.
CSCI 3336 - Operating Systems
Design and implementation of operating systems. Mutual exclusion, concurrency, deadlock, process scheduling, memory management, and files systems. Credit hours: 4. Prerequisite CSCI 1156.
CSCI 3344 - Computer Graphics
Techniques for the display of graphical information. 2D and 3D geometry and transformations. Interactive graphics, shading, hidden surface elimination, perspective, and depth. Modeling and realism. Credit hours: 4. Prerequisites: CSCI 2256 and MATH 2241.
CSCI 3346 - Software Development
This course provides an in-depth study of steps in the software-development process: user requirements, specifications, design, implementation, testing, maintenance, documentation, and management. Students will develop the facility to apply the general principles to new problems. Credit hours: 4. Prerequisite CSCI 2251.
CSCI 3364 - Game Development
Design and development of interactive games. Principles of game development will be illustrated with 2D games, while students with the appropriate graphics background may develop 3D games. This is a hands-on course. Credit hours: 4. Prerequisite: CSCI 2256.
CSCI 3366 - Computer Security
Introduction to the field of computer security as it relates to other areas of information technology. Topics include security threats, hardening systems, securing networks, and cryptography. Credit hours: 4. Prerequisites: CSCI 1156 and MATH 3337.
CSCI 3368 - AI & Large Language Models
This course explores artificial intelligence fundamentals with a focus on large language models (LLMs). Topics include machine learning, natural language processing, and ethical considerations. Credit hours: 4. Prerequisite: CSCI 2256. Offered alternate years.
CSCI 4490 - Independent Study
CSCI 4492 - Professional Development Seminar
Students will explore how the skills they have accumulated over the course of their degree may be applied both to solve problems in the real world and to extend the limits of human knowledge. They will select a research advisor and a research topic in computer science and begin directed readings. Credit hours:1. Prerequisite: CSCI 2251.
CYBR 2250 - Introduction to Cybersecurity
Provides a foundational understanding of the principles and practices used to protect computer systems and networks from cyber threats. Covering topics like common attack vectors, security measures, cryptography, network security, user awareness, ethical considerations, and basic threat analysis. Credit hours: 4. Prerequisite: MATH 1118 or MATH 1119 and CSCI 1151. Offered every year.
CYBR 4492 - Professional Development Seminar
Students will prepare for continued studies or work in Cybersecurity. They will select a research topic and begin directed readings. Credit hours: 1. Prerequisite: Senior standing in Cybersecurity or permission of the Department. Offered alternate years.
DSCI 2232 - Introduction to Data Science
Data science is an interdisciplinary field incorporating statistical techniques with algorithms to collect and to process large data sets, in order to extract meaning and make decisions. Students will explore the collection and filtering of data, machine learning algorithms, and methods for drawing conclusions. Credit hours: 4. Prerequisite: ECON 2227 or EVST 2205 or MATH 2227 or MATH 3343 or POL 2231 or PSYC 2227 or SOC 3395. Identical with MATH 2232.
DSCI 2233 - Machine Learning
A broad introduction to machine learning and statistical pattern recognition. Unsupervised and supervised learning algorithms including dimensionality reduction (PCA and variants), clustering (simple clustering, agglomerative and non-agglomerative), probabilistic models, neural networks, and support vector machines. Credit hours: 4. Prerequisite: ECON 2227 or EVST 2205 or MATH 2227 or MATH 3343 or POL 2231 or PSYC 2227 or SOC 3395.
DSCI 4495 - Data Science Seminar
The seminar requires students to explore the areas of their personal interest in data science in order to inform their choice of research topics, graduate school, and employment. Students will review the major ideas in data science and will prepare for the rigorous data science-related job interview. Credit hours: 1.
