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Other Courses |
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EMA 4614 - Production of Electronic Materials
Credits: 3
Prerequisites: EGN 3365 - Structure and Properties of Materials and PHZ 3442 - Semiconductor Physics
Course Description: The course provides students with an up-to-date review of modern semiconductor chip fabrication. Topics include modern techniques for growth and characterization of crystalline silicon and semiconductor alloys, their characterization, processes for materials doping, such as diffusion and implantation, thin film deposition and wire bonding, wet and dry etching. Fabrication of electronic devices through photo-lithography and X-ray lithography techniques will be discussed. Students will be introduced to software for the design of multi-layer, lithography masks and mask alignment.
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Accounting |
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ACG 2020 - Accounting for Managers
Credits: 3
Prerequisites: None
Course Description: This course is designed to enable the student to understand and apply the fundamental concepts and procedures of both financial and managerial accounting. Topics include basic accounting terminology, financial statement analysis and interpretation, internal control, cost behavior, cost-volume-profit analysis, budgeting, and the use of accounting data in making informed, ethical decisions..
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ACG 2021 - Principles of Financial Accounting
Credits: 3
Prerequisites: None
Course Description: This course is an introduction to the principles of financial accounting and focuses on wealth and income measurement and the preparation and interpretation of financial statements. The recording and reporting of financial activity, balance sheets, income statements, changes in equity, cash flows, underlying assets, liabilities, and equities are also presented.
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ACG 2071 - Principles of Managerial Accounting
Credits: 3
Prerequisites: ACG 2021 - Principles of Financial Accounting
Course Description: This course covers tools used by management for cost reporting and control including statements, analytical tools, and reports.
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American History |
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AMH 2010 - American History to 1877
Credits: 3
Prerequisites: None
Course Description: This course will survey American history from just prior to the initial exploration and settlement of the Americas to the period of Reconstruction. The course will discuss the English colonies in North America; the American Revolution; the United States Constitution; Antebellum America; the American Civil War; and Reconstruction. This course meets communication/writing-intensive requirements (W).
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AMH 2020 - American History Since 1877
Credits: 3
Prerequisites: None
Course Description: This course presents a survey of the emergence of modern America as an industrial and world power; the Progressive Era; WWI; the Great Depression and the New Deal; WWII; and the Cold War era. This course meets communication/writing-intensive requirements (W).
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Art History |
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ARH 2000 - Art Appreciation
Credits: 3
Prerequisites: None
Course Description: Introduction to the artistic experience through the examination of different ideas, approaches and purposes of art. This course meets communication/writing-intensive requirements (W).
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Astronomy |
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AST 3222 - Introduction to Astrophysics
Credits: 3
Prerequisites: PHY 2048 - Physics 1 with a C or better
Co-requisite or Prerequisite: PHY 2049 - Physics 2 or None
Course Description: Comprehensive survey of the universe and its appearance from earth seasons, tides, eclipses. The solar system, stellar evolution and galaxies, quasars, pulsars, black holes.
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AST 3271 - Astrophysics Laboratory
Credits: 1
Prerequisites: PHY 3101 - Introduction to Modern Physics and PHY 3101L - Modern Physics Laboratory
Course Description: An introduction to experiments methodology, data analysis and interpretation, calibration techniques, scientific model validation, data presentation and communication of results. The experiments are chosen for astrophysical relevance and include magnetic fields, optical interference and diffraction, wave polarization, line spectroscopy, photoelectric effect and radioactive decay.
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AST 4220 - Astrophysics 1
Credits: 3
Prerequisites: PHY 2049 - Physics 2 and PHY 2049L - Physics 2 Laboratory and AST 3222 - Introduction to Astrophysics
Course Description: This course introduces concepts and theories describing the physical and mathematical treatment of the properties of the Universe and the bodies within it, including the formation, structure, and evolution of stars, binary stars, stellar nucleosynthesis, white dwarfs, neutron stars, and black holes.
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AST 4221 - Astrophysics II
Credits: 3
Prerequisites: AST 4220 - Astrophysics 1
Course Description: The Physics of stellar objects: Classification of stars, nature of stellar spectra, Physics of stellar structure. The Sun, evolution of stars, neutron stars, black holes, binary systems. Galactic Astrophysics: Physics of the milky way, galactic structure, galactic evolution, large scale structure of the universe, active galaxies, cosmology, origin of the universe.
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Aviation Management |
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EAS 3101 - Fundamentals of Aerodynamics
Credits: 3
Prerequisites: EAS 4010 - Flight Performance Mechanics
Course Description: This course is an introductory course in to aerodynamics, which will apply the fundamental concepts of fluid mechanic to aerodynamic applications with both differential and control volume analysis. Topics covered include inviscid, incompressible flow over airfoils and finite wings, including boundary layer theory and two dimensional airfoil theory, as well as inviscid compressible flowing including normal, oblique and expansion shock waves.
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EAS 4010 - Flight Performance Mechanics
Credits: 3
Prerequisites: EGN 3321 - Dynamics and EGN 3331 - Strength of Materials
Course Description: This course is an introductory course into aircraft flight mechanics. Topics include introduction to airfoil theory, aircraft performance measures, wing design, lift/drag on wing performance, and an introduction to jet propulsion systems.
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EAS 4200 - Introduction to Aero Structures
Credits: 3
Prerequisites: EGN 3331 - Strength of Materials
Course Description: This course will apply the theories of mechanics introduced in EGN 3331 - Strength of Materials to aerospace structures. Topics covered will include stress analysis of aircraft components (i.e., wing spars/box beams, fuselages, wings), introduction to aero elasticity and the phenomena of wing flutter, structural/loading discontinuities in closed and open section beams, and bending, shear and torsion analysis in thin-walled beams.
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Biological Sciences |
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BSC 1010 - Biology 1
Credits: 3
Prerequisites: None
Co-requisite: BSC 1010L - Biology 1 Laboratory
Course Description: In this course students will study the chemistry of life, cell structure and function, photosynthesis, cellular respiration genetics, evolution, and the diversity of life. This course meets communication/writing-intensive requirements (W).
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BSC 1010L - Biology 1 Laboratory
Credits: 1
Prerequisites: None
Co-requisite: BSC 1010 - Biology 1
Course Description: Students will participate in laboratory experiments designed to reflect the topics presented in BSC 1010 - Biology 1 . This course meets communication/ writing-intensive requirements (W).
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BSC 1011 - Biology 2
Credits: 3
Prerequisites: BSC 1010 - Biology 1 and BSC 1010L - Biology 1 Laboratory
Co-requisite: BSC 1011L - Biology 2 Laboratory
Course Description:
In this course, students will study an introduction to ecology, evolution, biodiversity, and environmental science, history of life, forces that have shaped the diversity of life, changes in the biosphere due to human activity and how detrimental the impact of these changes may be.
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BSC 1011L - Biology 2 Laboratory
Credits: 1
Co-requisite: BSC 1011 - Biology 2
Course Description: Students will participate in laboratory experiments designed to reflect the topics presented in BSC 1011. This course meets communication/writing-intensive requirements (W).
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Biomedical Engineering |
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BME 4422 - The Biophysics of Neural Computation
Credits: 3
Prerequisites: MAP 4484 - Mathematical Modeling in Biology I
Course Description:
This course will discuss the biophysics of neuronal computation for both biological and artificial neural networks. It will provide a detailed introduction to: i) the anatomy/physiology of excitable cells, ii) the major brain architectures and principles, and iii) the most relevant mathematical models for neural computation from single neurons to circuits. Therefore, this course will prepare the students to understand the main principles by means of which our brains work and computers recognize patterns, learn/plan actions, and interact with humans
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Business Law |
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BUL 2241 - Law, Public Policy, Negotiation and Business
Credits: 3
Prerequisites: ENC 1101 - English Composition 1: Expository and Argumentative Writing
Course Description: The Structure of the legal system; administrative law and government regulation of business; and the legal environment of business including constitutional law, torts, contracts, and product liability are presented.
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Chemistry |
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CHM 2045 - Chemistry 1
Credits: 3
Prerequisites: None
Co-requisite or Prerequisite: Passing grade in CHM 1025
Co-requisite: CHM 2045L - Chemistry 1 Laboratory
Course Description: This course introduces the principles of chemistry and their applications based upon the study of physical and chemical properties of the elements. Topics covered in this class includes: stoichiometry, atomic and molecular structure, the states of matter, chemical bonding, thermochemistry, and gas laws.
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CHM 2045L - Chemistry 1 Laboratory
Credits: 1
Prerequisites: None
Co-requisite: CHM 2045 - Chemistry 1
Course Description: Students will participate in laboratory experiments designed to reflect the topics presented in CHM 2045 - Chemistry 1 . This course meets communication/writing-intensive requirements (W).
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CHM 2046L - Chemistry 2 Laboratory
Credits: 1
Prerequisites: None
Co-requisite: CHM 2046 - Chemistry 2
Course Description: Students will participate in laboratory experiments designed to reflect the topics presented in CHM 2046 - Chemistry 2 . This course meets communication/writing-intensive requirements (W).
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CHM 3217L - Organic Chemistry Laboratory (One Semester)
Credits: 1
Prerequisites: None
Co-requisite: CHM 3217 - Organic Chemistry (One Semester)
Course Description:
Students perform basic organic lab techniques. Synthesis, recrystallization, separations, extraction, chromatography, introduction to Nuclear Magnetic Resonance (NMR) and Infrared (IR) Spectroscopy.
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Computer Applications |
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CAP 1167 - First Year Experience
Credits: 1
Prerequisites: None
Course Description: This course is a weekly seminar designed to support freshman students in their transition to college. We hold meetings in and out of class for students to bring up any personal, academic or administrative concerns they have during their first semester in college. For the more advanced students, this course offers mentorship for those who wish to work on complex problems and projects early in their academic careers.
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CAP 3774 - Data Warehousing
Credits: 3
Prerequisites: COP 3710 - Database 1
Course Description: Fundamentals of building and populating a data mart to support the planning, designing and building of business intelligence applications and data analytics are covered in this course.
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CAP 4034 - Computer Animation
Credits: 3
Prerequisites: Computer Engineering: COP 3530 - Data Structures & Algorithms
Computer Science: COP 4415 - Data Structures and COP 4531 - Algorithm Design & Analysis
Course Description: Computer Animation is an introductory animation course that combines traditional animation principles with software based tools. Students will be introduced to the history and background of computer animation, animating primitive objects using a variety of techniques and tools, including keyframing and automating processes using procedural techniques. Students will also be introduced to behavioral animation processes, such as dynamics and simulation.
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CAP 4052 - Game Design and Development 1
Credits: 3
Prerequisites: CAP 4730 - Computer Graphics
Course Description: This is a technical course introducing the major tools used in game development and programming. Topics include stages of game development; development methodologies; scripting; game engines; game loading; programming input devices; multi-player design; mobile games; distribution and publishing.
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CAP 4056 - Game Design and Development 2
Credits: 3
Prerequisites: CAP 4052 - Game Design and Development 1
Course Description: This course builds upon CAP 4052 - Game Design and Development 1 . It is a hands-on, group- and project-based course. Students will use several game design aspects, different game engines, and a variety of software development kits. The focus of this course will be mainly on the technical aspects of game development with non-trivial programming projects employing different computer interaction technologies and digital media sources.
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CAP 4122 - Virtual Reality
Credits: 3
Prerequisites: CAP 4730 - Computer Graphics
Course Description: This course is to introduce students to the fundamentals of Virtual Reality (VR). The course topics include bird’s eye view, VR geometry, lights and optics, psychology of human vision, visual perception, visual rendering, motion, tracking, interaction, audio, and evaluation and experience.
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CAP 4410 - Computer Vision
Credits: 3
Prerequisites: (MAS 3114 - Computational Linear Algebra or MAS 3105 Linear Algebra ) and COP 3809C - Advanced Topics in Programming and
((COP 4415 - Data Structures and COP 4531 - Algorithm Design & Analysis ) or COP 3530 Data Structures & Algorithms )
Course Description: The course introduces how computers see and interpret the visual world and how this interpretation can be used to enhance game play experience. Topics covered: projections and coordinate systems, camera modeling, stereo vision, edge detection, filtering, segmentation, optical flow, motion vision, color vision, object representation, face recognition, object recognition.
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CAP 4630 - Artificial Intelligence
Credits: 3
Prerequisites: (STA 2023 - Statistics 1 or STA 3032 Probability and Statistics ) and (COP 3530 - Data Structures & Algorithms or COP 4415 - Data Structures ) and COP 4531 - Algorithm Design & Analysis .
Course Description: This course covers fundamental concepts such as search and knowledge representation and applied work in areas such as planning, game playing, and vision. Topics included: logical reasoning, constraint satisfaction problems, graph search algorithms, Bayes rule, Bayesian networks, multi-agent system, neural networks, decision trees, and natural language processing.
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CAP 4730 - Computer Graphics
Credits: 3
Prerequisites: Computer Engineering majors: COP 3530 - Data Structures & Algorithms
Computer Science and Data Analytics majors: COP 4415 Data Structures and COP 4531 Algorithm Design & Analysis
Course Description: The objective of this course is to establish a foundation in two- and three-dimensional computer rendering algorithms and display devices. Topics included: Geometric transformations, homogeneous coordinates, anti-aliasing, color vision, ray tracing, surface modeling, texture mapping, polyhedral representations, and reflectance models.
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CAP 4770 - Data Mining & Text Mining
Credits: 3
Prerequisites: (COP 3337C or COP 2034) and COP 3710 and (STA 3036 or MAS 3114)
Course Description: This course addresses the knowledge discovery process and the use of data mining concepts and tools as part of that process. In depth analysis of processes for automatically extracting valid, useful, and previously unknown information from data sources and using the information to make decisions is also covered.
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CAP 4786 - Topics in Big Data Analytics
Credits: 3
Prerequisites: COP 3710 - Database 1 and MAS 3114 - Computational Linear Algebra
Course Description: This course provides the fundamental knowledge to capture and analyze all sorts of large-scale data from a variety of fields, such as people behavior, sensors, biological signals, finance, and more. Platforms for data storage system and distributed processing of large data sets, Hadoop HDFS and MapReduce, Spark, and others, and different ways of handling analytics algorithms on different platforms will be introduced.
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CAP 4793 - Advanced Data Science
Credits: 3
Prerequisites: CAP 4770 - Data Mining & Text Mining and COP 3710 - Database 1
Course Description: This course introduces advanced concepts, methodologies and techniques in relation to data science including novel learning approaches, deep learning, reinforcement learning, novel data mining methodologies and emerging modes of data acquisition and aggregation. The course will develop students’ understanding of data mining concepts and their ability to carry out advanced data science projects.
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CAP 4830 - Modeling and Simulation
Credits: 3
Prerequisites: STA 2023 - Statistics 1 and COP 3809C - Advanced Topics in Programming
Course Description: The course will introduce the concepts of continuous and discrete event system simulation. The focus of the course will be discrete event simulation. In this course, the students will learn the basic definitions, Modeling and Simulation paradigms, design techniques, and applications.
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CAP 5320 - Data Wrangling and Exploratory Data Analysis
Credits: 3
Prerequisites: COP 5090 - Scientific Computation and Programming or an equivalent programming course
Course Description: Preprocessing tasks often consume a large fraction of time in computational projects, and all downstream analyses depend on them. In this course, students will develop practical skills for working with large datasets. Topics will include common methods for gathering, organizing, and reshaping structured and unstructured data. We will also cover methods of exploratory data analysis that are useful to guide more focused questions and models. These include principles of information display, simple model forms and data reduction, common visualization methods, and reporting tools.
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CAP 5410 - Advanced Computer Vision
Credits: 3
Prerequisites: Graduate Standing
Course Description: The course focuses on advance computer vision topics (image filtering, edge detection, interest point detectors, segmentation, optical flow, motion vision, color vision, object representation, face recognition, object recognition). This course will expose graduate students to innovative research.
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CAP 5634 - Advanced Artificial Intelligence
Credits: 3
Prerequisites: Graduate Standing
Course Description: This course expands on fundamental concepts such as search and knowledge representation and applied work in areas such as planning, game playing, and vision. Topics included: logical reasoning, constraint satisfaction problems, graph search algorithms, Bayes rule, Bayesian networks, multi-agent system, neural networks, decision trees, and natural language processing.
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CAP 5734 - Systems Acquisition, Integration and Implementation
Credits: 3
Prerequisites: None
Course Description: This course provides a study of the software acquisition process. The following subjects are discussed: SDLC, CMM, Cost Estimation, Risk Assessment and Management, Quality, Testing, Traceability, ERP, and Business Process Modeling. The course emphasizes methods and techniques for analyzing alternative software solutions to meet organizational needs. This course is part of the COIT core for all graduate students.
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CAP 5735 - Data Visualization and Reproducible Research
Credits: 3
Prerequisites: None
Course Description: A project-centered introduction to the visual display of quantitative information for both knowledge discovery and the communication of results. Fundamentals of reproducible research with attention to best practices and modern frameworks for data science project collaborations.
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CAP 5765 - Computational Data Analysis
Credits: 3
Prerequisites: STA 2023 - Statistics 1
Course Description: This course explores advanced topics in statistical data analysis and computability. It prepares students to perform big data analysis and organization using machine learning and data mining techniques and algorithms. Topics include: multivariate statistical methods, computational statistics, classification, clustering, prediction, regression analysis, and principal components analysis.
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CAP 5770 - Data Mining & Text Mining
Credits: 3
Course Description: This advanced course addresses the knowledge discovery process and the use of data mining concepts and tools as part of that process. In depth analysis of processes for automatically extracting valid, useful, and previously unknown information from data sources and using the information to make decisions is also covered.
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CAP 5771 - Data Mining & Text Mining
Credits: 3
Prerequisites: None
Course Description: This advanced course addresses the knowledge discovery process and the use of data mining concepts and tools as part of that process. In depth analysis of processes for automatically extracting valid, useful, and previously unknown information from data sources and using the information to make decisions is also covered.
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CAP 5775 - Data Warehousing
Credits: 3
Prerequisites: None
Course Description: Advanced techniques for building and populating a data mart to support the planning, designing and building of business intelligence applications and data analytics are covered in this course, along with data governance, stewardship, and security.
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CAP 5830 - Modeling and Simulation
Credits: 3
Prerequisites: Graduate Standing. Strong Programming (e.g. Programming 2) and Statistics 1 background.
Course Description: The course will introduce the concepts of continuous and discrete event system simulation. The focus of the course will be discrete event simulation. In this course, the students will learn the basic definitions, Modeling and Simulation paradigms, design techniques, and applications. The students will read and critique state of the art research papers about the covered topics.
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Computer Design/Architecture |
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CDA 2108 - Introduction to Computer Systems
Credits: 3
Prerequisites: COP 3337 - Object Oriented Programming
Course Description: This course provides an introduction to logic design and the basic building blocks of digital computers. The course will cover logic gates, some minimization techniques, arithmetic circuits, flip-flops, synthesis of sequential circuits, finite state machines, counters, registers, Random Access Memory (RAM), and Arithmetic Logic Unit (ALU).
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CDA 3100 - Computer Architecture
Credits: 3
Prerequisites: COP 3337 - Object Oriented Programming and STA 2023 - Statistics 1
Course Description: This course discusses the background and principles of computer architecture and assembly language including the following: computer organization, computer performance, assembly language and machine code, computer arithmetic, multi-processor and distributed architectures, ALU design, datapath and control, pipelining, memory hierarchy, I/O devices, graphics, mobile and multi-core processors.
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CDA 3631C - Embedded Operating Systems
Credits: 3
Prerequisites: CDA 3100 - Computer Architecture or EEL 4768C - Computer Architecture and Organization
Course Description: Embedded Operating Systems or Real time operating systems are operating systems are designed to be compact, efficient, and reliable. Topics discussed include embedded architectures, interaction with devices, concurrency, real-time principles, implementation trade-offs, profiling and code optimization, and embedded software.
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CDA 4210 - VLSI Design
Credits: 3
Prerequisites: EEL 4768C Computer Architecture and Organization
Co-requisite or Prerequisite: EEE 3310 Digital Electronics
Course Description: Topics discussed in this course include CMOS technology, MOSFET timing analysis, dynamic clocked logic, and layout design rules. Digital VLSI chip design is introduced. Computer-aided design software tools and elementary circuit design will be used. Cell library construction.
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CDA 4332 - System Architecture
Credits: 3
Prerequisites: CTS 2375 - Cloud Implementation Strategies and Cloud Providers and COP 3710 - Database 1 and (CNT 3502 - Data Communication or CNT 3004C Introduction to Computer Networks )
Course Description: This course covers architecture issues including: Memory hierarchy, I/O subsystems, commercial instruction sets, pipelining, and multiprocessing.
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CDA 5216 - Advanced VLSI Design
Credits: 3
Prerequisites: Graduate Standing
Course Description: Topics discussed in this course include CMOS technology, MOSFET timing analysis, dynamic clocked logic, and layout design rules. Digital VLSI chip design is introduced. Computer-aided design software tools and elementary circuit design will be used. Cell library construction.
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CDA 5430C - Advanced Autonomous Systems
Credits: 3
Prerequisites: Graduate Standing
Course Description: This course will focus on the advanced subject matter of autonomous system control using a publish/subscribe architecture. These subjects include mapping, safe motion planning, and computer vision. The latter portion of the course will deal with multiple robotic systems working in unison and considerations of various problems with human-robotic interactions.
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CDA 5653 - Advanced Concepts in Virtualization 2
Credits: 3
Prerequisites: Permission from VP of Academic Affairs or Designee
Course Description: This is an applied course in the principles, methods, and technologies of Cloud Computing. Upon completion of this course students should be able to create, configure, build, deploy and manage a variety of cloud based solutions.
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Computer General Studies |
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CGS 1100 - Computer Information Technology and Applications
Credits: 2
Prerequisites: None
Co-requisite or Prerequisite: None
Co-requisite: None
Course Description: Using information technology to improve business process performance as well as the creation of value for organizations. Spreadsheets, relational database management and design principles, information systems, and other software applications that are typically used in the workplace are presented. The impact of AI, machine learning, data science, and cloud technologies in business solutions is examined.
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CGS 5096 - Advanced Legal, Ethical and Management Issues in Technology
Credits: 3
Prerequisites: None
Course Description: This course covers legal, ethical and regulatory issues present in the domain of applied technology. Students will learn to apply SWOT, PEST, and SEEC methods to analyze situations based on social, political, environmental, cultural and economic criteria. This course is designed to emphasize moral and ethical training for students to be well prepared for the business environment.
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CGS 5367 - Advanced Applied Information
Credits: 3
Prerequisites: Knowledge of database fundamentals, Statistics and modeling, computer programming.
Course Description: This course covers historical and modern approaches of knowledge management (KM), knowledge discovery (KD), data analytics (DA), and information retrieval (IR). This is an advanced level course and is focused on direct application of the principles and methods of information science theories and model building. Students are exposed to a variety of commercial data analytic tools for visualization and analysis techniques.
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Computer Networks |
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CNT 3004C - Introduction to Computer Networks
Credits: 3
Prerequisites: COP 3337 - Object Oriented Programming and (STA 2023 - Statistics 1 or STA 3032 Probability and Statistics )
Course Description: This course provides an introduction to fundamental concepts in computer networks, including their design and implementation. Topics covered include all seven layers of OSI Reference Model, network protocols (providing reliability and congestion control), routing, and link access. Special attention is also paid to wireless networks and security.
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CNT 3200 - Distributed Information Systems
Credits: 3
Prerequisites: COP 3710 - Database 1
Course Description: This course discusses server based operating systems which are deployed, administered and managed via remote locations. Emphasis is placed upon the hardware required for interconnecting digital devices for the purpose of enabling data communication through a network. Bus architectures, ports, network cards, cabling, routers, switches are also covered. Ensuring network reliability and optimizing network performance are presented.
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CNT 4403 - Data Security
Credits: 3
Prerequisites: (COP 3530 - Data Structures & Algorithms or COP 4415 Data Structures ) and COP 4531 Algorithm Design & Analysis .
Course Description: Access control systems, telecommunications and network security, security management practices, application and systems development security, cryptography, disaster recovery planning, legal and ethical issues, and physical security are covered in this course. Special topics include Network Security, Cryptography, Access Control, Security Architecture and Models, Applications and Systems Development, and Vulnerability Assessment.
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CNT 4409 - Network Security
Credits: 3
Prerequisites: CIS 4362 - Applied Cryptography and CNT 3004C - Introduction to Computer Networks
Course Description: The course introduces networks security tools and techniques. Topics covered are: hardware and software network security tools, firewalls, attacks and mitigation at the network level, authentication, intrusion detection, network vulnerability analysis, threat and risk assessment.
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Computer Programming |
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COP 2034 - Introduction to Programming Using Python
Credits: 3
Prerequisites: None
Co-requisite or Prerequisite: None
Co-requisite: None
Course Description: This course is an introduction to computational thinking and the art of computer programming using Python. Students will learn fundamental programming concepts and systematic design techniques. They will use them to write programs that computationally solve and reduce problems. At the end of the course, students will be able to use a programming language without focusing on the language specifics. No prior programming background is required and a working knowledge of high school level algebra is expected.
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COP 2073 - Introduction to Data Science
Credits: 3
Prerequisites: None
Course Description: Students will learn how to work through data science problems within a modern statistical programming language. The course covers the complete analytical process, from gathering the data, to applying appropriate exploratory and statistical analysis, and communicating the results. Important topics in data science projects workflows, version control, and efficient programming are integrated throughout the course. Fundamentals of analytics, data visualization, and management of data are presented.
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COP 2271 - Introduction to Computation and Programming
Credits: 3
Prerequisites: MAC 1147 - Pre-calculus Algebra and Trigonometry or equivalent, e.g. Aleks score
Course Description: This course is an introduction to computational thinking and the art of computer programming using the C programming language. Students will learn fundamental programming concepts and systematic design techniques. They will use them to write programs that computationally solve and reduce problems. At the end of the course, students will be able to use a programming language without focusing on the language specifics. No prior programming background is required and a working knowledge of high school level algebra is expected.
(Amended 10/25/2021)
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COP 3330C - Computer Programming 2
Credits: 3
Prerequisites: COP 3337 - Object Oriented Programming
Course Description: This course is an advanced level computer programming course. It introduces advanced programming concepts: Object-Oriented design principals, data abstraction, classes, polymorphism, inheritance, and basic algorithms. Students will acquire skills to solve larger projects and algorithmic problems with more efficient code.
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COP 3337 - Object Oriented Programming
Credits: 3
Prerequisites: A letter grade of C or higher in COP 2271 - Introduction to Computation and Programming (Amended 10/25/2021)
Course Description: This is an intermediate programming course designed for students with prior programming experience. This course focuses on object-oriented programming concepts and techniques using C++. The covered topics will include: streams, classes, recursion, template classes, file handling, and exception handling.
(Amended 10/25/2021)
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COP 3338 - Advanced Computer Programming
Credits: 3
Prerequisites: COP 3530 - Data Structures & Algorithms
Course Description: The course includes advanced programming topics: multithreading, libraries, exception handling, GUI, networks, memory allocation, database connection, cross-platform development issues.
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COP 3530 - Data Structures & Algorithms
Credits: 3
Prerequisites: COP 3337 - Object Oriented Programming and MAD 2104 - Discrete Mathematics
Course Description: The course introduces program run-time analysis and algorithm design and analysis. Topics include: data abstraction principals, serial and parallel data structures, linked lists, graphs, trees, divide and conquer algorithms, greedy algorithms, and linear programming.
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COP 3729 - Database 2
Credits: 3
Prerequisites: COP 3710 - Database 1
Course Description: Datacenter infrastructure and management including technologies such as: virtualization, networking, server consolidation, green IT computing, and network storage configurations are discussed. The utilization of virtualized platforms, networking and infrastructure configurations as well as the deployment, analysis and management of applications are also presented.
(Amended 10/25/2021)
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COP 3809 - Advanced Topics in Programming
Credits: 3
Prerequisites: COP 3337 Object Oriented Programming
Course Description: This course is an advanced level computer programming course. It reinforces the object-oriented programming concepts and techniques using Java. The course will cover topics include interfaces, exception handling, advanced GUI design, graphics and Java 2D, regular expressions, object serialization, collections, concurrency, accessing databases, and networking.
(Amended 10/25/2021)
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COP 3834 - Web Application Development
Credits: 3
Prerequisites: COP 2271 - Introduction to Computation and Programming
Course Description: Topics include: Client-side programming, distributed transactions, remote procedure calls, component objects, server side programming and network load balancing. Methods such as HTML5, CSS, JavaScript, XML, and PHP are introduced.
(Amended 10/25/2021)
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COP 4020 - Programming Languages
Credits: 3
Prerequisites: Computer Engineering majors: COP 3530 - Data Structures & Algorithms
Computer Science and Data Analytics majors: COP 4415 - Data Structures and COP 4531 - Algorithm Design & Analysis
Course Description: The course covers programming models underlying different languages. The course will help students make informed design choices in languages supporting multiple complementary approaches. Students will be introduced to the principles of how programming language features are defined, composed, and implemented. In addition, the effective use of programming languages, and appreciation of their limitations, is emphasized by introducing main constructs on programming languages as well as lexical and syntax analysis. The course will include the following topics: Introduction to the theory of computation, including models of computation such as Turing machines; theory of programming languages; including grammars; parsing; syntax and semantics.
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COP 4368 - Advanced Programming
Credits: 3
Prerequisites: CEN 4010 - Software Engineering
Course Description: This course gives an in-depth analysis of algorithms using object oriented techniques. Emphasis is placed on practical applications and programming within Electrical and Computer Engineering. The programming languages included in this course are C++ and Java.
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COP 4415 - Data Structures
Credits: 3
Prerequisites: A letter grade of C or higher in COP 3337 - Object Oriented Programming (Amended 10/25/2021)
Course Description: This course examines the essential properties of algorithms and data structures. The data structures will be used as tools to aid in algorithm design and application.
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COP 4421 - Autonomous Systems Programming
Credits: 3
Prerequisites: COP 3337C - Object Oriented Programming
Course Description: Robots are becoming increasingly ubiquitous in all aspects of our life. Students taking this course will learn how to reuse and develop code with ROS. The topics will cover: ROS foundations, simulation and visualization, perceptual processing, and mobile-robot motion, system integration and proper robotic control architecture design.
(Amended 10/25/2021)
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COP 4610 - Operating Systems Concepts
Credits: 3
Prerequisites: EEL 4768C - Computer Architecture and Organization or CDA 3100 - Computer Architecture
Course Description: This course covers the concepts of the design and implementation of operating systems. Topics included: memory and storage management, virtual memory, processes/threads, system calls, interfaces, I/O, file system, and introduction to virtualization.
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COP 4620 - Compilers and Interpreters
Credits: 3
Prerequisites: COP 4415 - Data Structures
Course Description: This course introduces students to the theory of programming language processors. The topics will cover: organization of translators, grammars and languages, symbol tables, lexical analysis, syntax analysis, error handling, code generation, optimization, and interpretation.
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COP 4656 - Mobile Device Applications
Credits: 3
Prerequisites: COP 3337 - Object Oriented Programming
Course Description: This course covers the design principles and technologies for the development of software applications for mobile devices. The application development process and tools will also be covered. Through hands-on exercises, the students are given practice in mobile applications programming and develop their problem solving skills in a collaborative classroom environment.
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COP 4934 - Senior Design 1
Credits: 3
Prerequisites: CEN 4010 - Software Engineering and COP 3710 - Database 1
Course Description: This is the first course in a sequence of two courses that are based on supervised team projects. In this course, students will learn and demonstrate teams work, efficient communication, reading standards, software design methodology, performing project feasibility study, and writing proposals. In addition, the course will touch on aspects of intellectual property, professional ethics, and social impact.
(Amended 10/25/2021)
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COP 4935 - Senior Design 2
Credits: 3
Prerequisites: COP 4934 - Senior Design 1
Course Description: This is the second course in a sequence of two courses that are based on supervised team projects. This is a continuation to the project in Senior Design 1. In this course students will learn and demonstrate project implement, debugging, documentation, and testing. The students are expected to: 1) write a final report describing the activity performed during the course; and 2) present the project.
(Amended 10/25/2021)
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COP 5090 - Scientific Computation and Programming
Credits: 3
Prerequisites: Graduate standing
Course Description: The course will introduce the students to scientific computing and graphics using R. The topics covered include programming with R, Numerical Accuracy, Root finding, Integration, Ordinary Differential Equations, Probability and Random Variables, Estimation, Markov Chains, and Basic Simulation.
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COP 5272 - Computation Theory
Credits: 3
Prerequisites: Graduate Standing
Course Description: The course develop understanding of the underlying fundamentals of computation. It is assumed that students have had decent exposure to computability topics in an undergrad level course. A significant portion of this course will then be focused on computational complexity, including major topics in theory of computation such as randomization, interactive proofs, time and space measures, complexity classes, quantum computing.
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COP 5531 - Advanced Algorithm Design and Analysis
Credits: 3
Prerequisites: Graduate Standing
Course Description: The course covers theory of NP-completeness, methods for dealing with NP-complete problem. Selected topics in such areas as combinatorial optimization, computational geometry, cryptography, parallel algorithms. This course also discuss algorithms for graph theoretical applications, lower bounds, upper bounds, and average performance of algorithms. If time permits discussion on complexity theory will also discussed. Core results and techniques are introduced, which are useful to those planning to specialize in other areas in computer science. Moreover, some fairly advanced topics will be covered. This will provide an idea of the current research for the benefit of those who might wish to specialize in this area.
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