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: 4. A student may not receive credit for this course after taking CSCI 1156 or its equivalent.

CSCI 1156. Computer Programming II

A continuation of Computer Science 151. Emphasis on top-down programming using methods. Topics include user-defined classes and advanced data types, arrays, recursion, algorithms for sorting, searching, exception handling, advanced GUIs and graphics, and embedding Java applets into HTML documents.
Credit hours: 4. Prerequisite: CSCI 1151 or the equivalent.

CSCI 2225. Matlab and Labview

This course covers beginning and intermediate programing in the Matlab and Labview computer languages. Students will learn the basics of computer programming as well as the specifics of programing in Matlab and Labview including data input/output, code structuring, coding best practices and limitations, data acquisition and beginning GUI development. This course is project based with projects taken from real world computing problems.
Credit hours: 4. Prerequisite: MATH 1149. Alternate years: offered Fall 2021.

CSCI 2251. Algorithms and Data Structures

Structures for the representation of data are considered: vectors, lists, queues, trees, heaps, hash tables, maps, and graphs. This course presents the logic behind choosing a particular structure, and the associated algorithms for using each structure. Fundamental algorithms for solving problems, including sorting, searching and graph algorithms are developed. General design, analysis and the study of complexity are emphasized.
Credit hours: 4.Prerequisite: CSCI 1156.

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: 4. Pre- or co-requisites: CSCI 2251 and MATH 1149 or equivalent. Alternate years: offered Spring.

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. Alternate years.

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. Alternate years: offered Spring.

CSCI 4492 Professional Development Seminar

– Computer Science 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 251.

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. Alternate years; offered Spring.

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.

MATH 1109. Introduction to Quantitative Reasoning

This course presents mathematical ideas in a real world context. Topics covered include critical thinking and problem solving, the mathematics of finance, basic statistical principles, mathematics and the arts, and the theory of voting.
Credit hours: 4. Offered as needed. (QR)

MATH 1117, 1118. Precalculus with Elementary Modeling

Relations defined algebraically, graphically, and numerically. Functions, including polynomial, rational, trigonometric, exponential, and logarithmic. Applications, including modeling. Algebraic techniques, and a review of basic geometric relationships.
Credit hours: 4, 4. Not open to students who have been placed into MATH 1119 or above, except by permission of the Department. (QR)

MATH 1119. Precalculus

A study of the properties of various functions, including polynomial, trigonometric, exponential, and logarithmic. Analytic geometry of conic sections.
Credit hours: 4. Not open to students who have been placed into MATH 1149 or above, except by permission of the Department. (QR)

MATH 1149. Calculus I

Limits, continuity, and differentiation of algebraic functions of one variable. Applications to curve sketching, optimization, and rates of change. The definite integral applied to finding the area under a curve.
Credit hours: 4. Prerequisite: MATH 1118 or MATH 1119 or the equivalent. (QR)

MATH 1150. Calculus II

A continuation of Mathematics 1149. Volumes and surface area of solids of revolution. Lengths of curves. The logarithm and exponential functions. Techniques of integration. Areas in polar coordinates. Improper integrals, infinite series, and power series.
Credit hours: 4. Prerequisite: MATH 1149 or permission of the Department. (QR)

MATH 2208. Concepts of Elementary and Middle School Mathematics

Introduces elementary problem solving with emphasis on the nature of numbers and the structure of the real number system. Topics studied include the structure and properties of number systems and of Euclidean Geometry applicable in elementary and middle school classrooms.
This course is open to all students and required of students seeking elementary education licensure. Credit hours: 4. (QR)

MATH 2227. Elementary Applied Statistics

An introduction to statistics, including probability, binomial distributions, normal distributions, sampling theory, testing hypotheses, chi-square tests, and linear regression.
Credit hours: 4. Not open to students who have satisfactorily completed MATH 3343. A student may receive credit for two of these courses: ECON 2227, MATH 2227, POL 2231, PSYC 2227, or SOC 3395. Offered Spring. (QR)

MATH 2229. Advanced Mathematical Problem Solving

In this course, students will be expected to solve and present solutions to a collection of problems gathered from various mathematics competitions. Problem solutions may involve the techniques of classical algebra, geometry, calculus, and combinatorics.
Credit hours: 1. Prerequisite: permission of instructor. May be repeated for credit up to a maximum of 4 hours.

MATH 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 DSCI 2232. Alternate years.

MATH 2234. Techniques of Mathematical Proof

An introduction to formal mathematical proof. Topics include logical inference, statements involving quantifiers, indirect proof, and mathematical induction. We investigate proofs in a variety of disciplines but with a particular focus on set theory, combinatorics, and graph theory.
Credit hours: 4. Prerequisite: MATH 1149

MATH 2241. Linear Algebra

Systems of linear equations, vector spaces and subspaces, bases and dimension, linear
transformations, eigenvalues and eigenvectors, and inner product spaces.
Credit hours: 4. Prerequisite: MATH 1149 or permission of the Department.

MATH 2250. Calculus III

An introduction to vector calculus. Differential and integral calculus of more than one variable. Vector fields, including Green’s, Stokes’, and the Divergence Theorems.
Credit hours: 4. Prerequisite: MATH 1150 and either MATH 2241 or PHYS 1115 or permission of the Department.

MATH 3320. Introductory Topology An introduction to point-set geometry, including topological spaces, metric spaces, homotopy, the Urysohn lemma, and Tychonoff’s theorem. Students explore topology as the underpinning of modern geometry.
Credit hours: 4. Prerequisite: MATH 2241 or permission of the Department.

MATH 3331. Differential Equations

First order linear and non-linear equations, second and higher order linear equations,
series solutions, Laplace transforms, and systems of linear differential equations. Applications, primarily to mechanics and population dynamics.
Credit hours: 4. Prerequisite: MATH 1150 and 2241 or the course may be taken concurrently with MATH 2241 by permission of the Department.

MATH 3337. Number Theory

Properties of the integers. Unique factorizations, congruences and modular arithmetic.
Diophantine equations, prime numbers, quadratic reciprocity, and integer functions. Applications to cryptology.
Credit hours: 4. Prerequisite: MATH 1150 and MATH 2234 or permission of the Department. Alternate years.

MATH 3343. Mathematical Statistics Probability

Discrete and continuous probability distributions. Sampling and the Central Limit Theorem. Confidence intervals, hypothesis testing, linear regression, and non-parametric tests.
Credit hours: 4. Prerequisite: MATH 2250. Alternate years.

MATH 3353. Mathematical Modeling

The construction and analysis of mathematical models to solve problems in the
physical and social sciences. Dynamical systems are emphasized with a particular concentration on linear and non-linear discrete dynamical systems. Topics may include dimensional analysis, stability, chaos, and fractals.
Credit hours: 4. Prerequisite: MATH 1150 and 2241. Alternate years: offered Fall.

MATH 3360. Abstract Algebra

Groups, rings, integral domains. Homomorphisms and isomorphisms. Elementary number theory. The fields of rational, real, and complex numbers.
Credit hours: 4. Prerequisite: MATH 2234 and MATH 2241 or permission of the Department.

MATH 4426. Complex Variables

The complex number system. Limits, continuity, and differentiability of functions of a
single complex variable. Contour integration and Cauchy’s Theorem. The calculus of residues. Conformal mapping.
Credit hours: 4. Prerequisite: MATH 2250. Alternate years.

MATH 4443. Introduction to Analysis

A rigorous study of limits, continuity, differentiation, and integration of functions of a real variable.
Credit hours: 4. Prerequisite: MATH 2234 and MATH 2250 or permission of the Department.

MATH 4492. Professional Development Seminar

Mathematics 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 mathematics and begin directed readings.
Credit hours:1. Prerequisite: MATH 360.

MATH 4494. Senior Seminar

This course will emphasize the importance of seminal problems in mathematics in
motivating the development of techniques learned over the course of four years. Students will place their accumulated mathematical knowledge in context in the broad world of mathematics. Students will continue to conduct research into their broader world of mathematical knowledge. Students will continue to explore their chosen problem in mathematics or computer science, culminating in a paper and a talk on the topic.
Credit hours: 4. Prerequisite: MATH 4493 or CSCI 4493.