All Courses(A-Z)
Course Code
THEA 101
Credit
3.0 - 3.0
Course Name
Introduction to Theatre Arts
Introduction
Introduction to the arts of theater for non-majors, including acting, design, directing, dramaturgy, and playwriting, together with a survey of theatrical history, minority theater, and plays by women. Attendance at Department of Theater productions (ticket fee required). Credit not given for both THEA 101 and THEA 102. This course satisfies the General Education Criteria for: Humanities – Lit & Arts
Course Code
MUS 133
Credit
3.0 - 3.0
Course Name
Introduction to World Music
Introduction
A survey of various musical traditions from different regions and peoples of the world. For music and non-music majors. Students must register for one discussion and one lecture section. This course satisfies the General Education Criteria for: Cultural Studies - Non-West Humanities – Lit & Arts
Course Code
ECE 498ICC
Credit
4.0 - 4.0
Course Name
IoT and Cognitive computing
Introduction
Subject offerings of new and developing areas of knowledge in electrical and computer engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites.
Course Code
CWL 240
Credit
3.0 - 3.0
Course Name
Italy Middle Ages and Renaissa
Introduction
The development of Medieval Italian civilization in a literary context from the Sicilian School of love poetry to the early Renaissance in Florence; lectures and readings are in English. This course satisfies the General Education Criteria for: Humanities – Lit & Arts
Course Code
LING 250
Credit
3.0 - 3.0
Course Name
Language Diversity in the USA
Introduction
The United States has a vast and varied linguistic landscape that has been shaped by a unique medley of peoples and cultural practices. From the colonization of North America to contemporary politics and popular culture, language has helped to connect us in many ways, and has also served as a tool for making and maintaining difference.
Course Code
MATH 257
Credit
3.0 - 3.0
Course Name
Linear Algebra with Computatio
Introduction
Introductory course incorporating linear algebra concepts with computational tools, with real world applications to science, engineering and data science. Topics include linear equations, matrix operations, vector spaces, linear transformations, eigenvalues, eigenvectors, inner products and norms, orthogonality, linear regression, equilibrium, linear dynamical systems and the singular value decomposition. Credit is not given for both MATH 257 and any of MATH 125, MATH 225, MATH 227, MATH 415 or ASRM 406. Prerequisite: MATH 220 or MATH 221; CS 101 or equivalent programming experience.
Course Code
CWL 202
Credit
3.0 - 3.0
Course Name
Literature and Ideas
Introduction
<p>Analysis of several important world-views in Western civilization (such as classical, Romantic, modern, and so forth), studied comparatively and in relation to selected figures in Western literature. Prerequisite: CWL 241 and CWL 242; or one year of college literature; or consent of instructor. This course satisfies the General Education Criteria for: Cultural Studies - Western Humanities – Lit &amp; Arts</p>
Course Code
PHIL 102
Credit
3.0 - 3.0
Course Name
Logic and Reasoning
Introduction
Practical study of logical reasoning; techniques for analyzing and criticizing arguments, with emphasis on assessing the logical coherence of what we read and write. Students registering in Lecture AL1 must also register in a lecture-discussion section (AD_).
Course Code
CS 446
Credit
3.0 - 3.0
Course Name
Machine Learning
Introduction
Principles and applications of machine learning. Main paradigms and techniques, including discriminative and generative methods, reinforcement learning: linear regression, logistic regression, support vector machines, deep nets, structured methods, dimensionality reduction, k-means, Gaussian mixtures, expectation maximization, Markov decision processes, and Q-learning. Application areas such as natural language and text understanding, speech recognition, computer vision, data mining, and adaptive computer systems, among others.
Course Code
ECE 449
Credit
4.0 - 3.0
Course Name
Machine Learning
Introduction
<p>Principles and applications of machine learning. Main paradigms and techniques, including discriminative and generative methods, reinforcement learning: linear regression, logistic regression, support vector machines, deep nets, structured methods, dimensionality reduction, k-means, Gaussian mixtures, expectation maximization, Markov decision processes, and Q-learning. Application areas such as natural language and text understanding, speech recognition, computer vision, data mining, and adaptive computer systems, among others. Same as ECE 449. 3 undergraduate hours.