Mar 29, 2024  
2018-2019 Academic Catalog 
    
2018-2019 Academic Catalog [ARCHIVED CATALOG]

Course Descriptions


 

Other Courses

  
  • CAP 4793 - Advanced Data Science


    Credits: 3

    Prerequisites: CAP 4770 - Data Mining & Text Mining COP 3710 - Database 1   
    Co-requisite or Prerequisite: None
    Co-requisite: None
    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.

Accounting

  
  • ACG 2020 - Accounting for Managers


    Credits: 3

    Prerequisites: None.
    Co-requisite or Prerequisite: None.
    Co-requisite: 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..
  
  • 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.
  
  • 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.

American History

  
  • 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).
  
  • 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).
  
  • AMH 2930 - Special Topics


    Credits: 1-3

    Course Description: Selected topics in the history of the United States. Topic will be determined by the instructor. This course meets communication/writing-intensive requirements (W).

Art History

  
  • 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).

Aviation Management

  

Biological Sciences

  
  • 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).
  
  • BSC 1010L - Biology 1 Laboratory


    Credits: 1

    Co-requisite: BSC 1010 - Biology 1   
    Course Description: Students will participate in laboratory experiments designed to reflect the topics presented in BSC 1010. This course meets communication/ writing-intensive requirements (W).

Biomedical Engineering

  
  
  
  • BME 4577 - Nanomedicine and Nanotherapeutics


    Credits: 3

    Prerequisites: BSC 1010 - Biology 1  BSC 1010L Biology 1 Laboratory  EMA 1083C - Unique Nanoscale Phenomena and Interfaces  
    Course Description: The anatomy and physiology of health and disease states are covered in this course. Topics include basic immunology; passive and active targeting design; common synthesis; and characterization approaches for nanomedicines.

Business Law

  
  • BUL 2241 - Law, Public Policy, Negotiation and Business


    Credits: 3

    Prerequisites:  ENC 1101 - English Composition 1: Expository and Argumentative Writing  
    Co-requisite or Prerequisite: None.
    Co-requisite: None.
    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.

Chemistry

  
  • CHM 2045 - Chemistry 1


    Credits: 3

    Co-requisite or Prerequisite: MAC 1147 or the equivalent, or 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.
  
  • 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 . This course meets communication/writing-intensive requirements (W).
  

Computer Applications

  
  • 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.
  
  • 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.

  
  • 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.
  
  • 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 I). 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.
  
  
  
  • CAP 4453 - Robotics and Computer Vision


    Credits: 3

    Prerequisites: None
    Course Description: This course discusses robotics, computer vision, image formation and analysis, rigid body and coordinate frame transformations, low level visions and edge detection, models for shading and illuminations, camera models, calibration, 3-D stereo reconstruction, epipolar geometry, fundamental matrices, object recognition and motion estimation.
  
  
  
  • 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  
    Co-requisite or Prerequisite: None
    Co-requisite: None
    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.

  
  • CAP 4733 - Senior Capstone 1: Systems Acquisition, Integration, and Implementation


    Credits: 3

    Prerequisites: Senior-level status or Program Coordinator Permission.
    Co-requisite or Prerequisite: None
    Co-requisite: None
    Course Description: This course is part one of the Senior Capstone sequence for Data Analytics. This advanced course covers critical thinking and problem solving techniques applied to information systems. Fundamentals and complexities associated with learning and applying the methods for creating a system development and implementation (S-DIP) plan are also covered. The course includes materials and exercises for students to develop skills in the domain of systems acquisition, integration, and implementation through applied system development and planning, and application lifecycle management.
  
  
  • CAP 4763 - Advanced Topics 1: Time Series Modeling and Forecasting


    Credits: 3

    Prerequisites: QMB 3200 Advanced Quantitative Methods  
    Co-requisite or Prerequisite: None
    Co-requisite: None
    Course Description: The course covers modeling stochastic time series, building and evaluating forecasts, including appropriate techniques for cross validation in a time series context. Applications to issues in business, economics, and healthcare will be used.
  
  • CAP 4764 - Advanced Topics 2: Data Center Design & Large Data Sets


    Credits: 3

    Prerequisites: CAP 4763 - Advanced Topics 1: Time Series Modeling and Forecasting  
    Course Description: Application of a variety of analytical tools from the curriculum used for solving real world problems, with the focus on identifying the problem, constructing an appropriate model, and finding the best available method to solve it. Topics include data center design, working with large data sets and mining information from text, including scalable supervised and unsupervised machine learning methods, visualization and extraction. Other topics covered include: Discovering heuristic rules from large data sets, handling special data types, creating methods, procedures and models for extracting and sorting large amounts of unstructured data.
  
  
  • CAP 4830 - Modeling and Simulation


    Credits: 3

    Prerequisites: STA 2023 - Statistics 1 COP 3330C - Computer Programming 2  
    Co-requisite or Prerequisite: None
    Co-requisite: None
    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.
  
  • 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.

     

     

  
  • CAP 5431 - Medical Imaging Informatics


    Credits: 3

    Prerequisites: Graduate Standing
    Course Description: This course provides a broad and practical introduction to the major techniques employed in medical image processing: 3D and 4D medical imaging modalities, dilation and erosion, segmentation and thresholding, denoising, direct space filter kernels, Fourier-based filters, matching and morphing, artificial neural networks, self-organizing maps, principal component analysis. The course will be useful for graduate students in biomedical computing who wish to learn state of the art data mining and image vision techniques. Medical imaging related policies (DICOM, HIPPA compliance, data sharing) are also discussed.
  
  • CAP 5630 - 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.
  
  • 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.
  
  • CAP 5771 - Data Mining & Text Mining


    Credits: 3

    Prerequisites: None
    Co-requisite or Prerequisite: None
    Co-requisite: 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.
  
  • CAP 5774 - Data Warehousing


    Credits: 3

    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.
  
  • CAP 5781 - Complex Modeling, Forecasting Techniques and Web Analytics


    Credits: 3

    Prerequisites: COP 3729C - Database 2 , CAP 4770 - Data Mining & Text Mining , CAP 3774 - Data Warehousing , MAD 2104 - Discrete Mathematics  
    Course Description: Applying Big Data analysis techniques to the complexities of emergent and predictive analytics such as marketing issues, financial reporting, and stock market trading schemes. Advanced application of knowledge discovery, CRM systems, and modeling for trends and predictions are covered. Emphasis on mathematical methods such as deterministic and probabilistic operations research models for decision problems. Complex applications of web analytics are also covered.
  
  • 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.

Computer Design-Architecture

  
  • CDA 2108 - Introduction to Computer Systems


    Credits: 3

    Prerequisites: COP 2272C - Computer Programming 1  
    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).
  
  • CDA 3100 - Computer Architecture


    Credits: 3

    Prerequisites:  COP 2272C - Computer Programming 1 , 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.
  
  • 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, embedded software.
  
  • CDA 4210 - VLSI Design


    Credits: 3

    Prerequisites: EEL 4768C - Computer Architecture and Organization 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.
  
  
  • CDA 4910 - Senior Capstone 2: Directed Research


    Credits: 3

    Prerequisites: CAP 4733 Senior Capstone 1: Systems Acquisition, Integration, and Implementation  
    Course Description: This course is part two of the senior capstone sequence for the Data Analytics degree. Students will conduct intensive research and produce significant written documentation of an experiment, research exploration, or special interest project in technology. This course meets communication/writing-intensive requirements (W).

Computer General Studies

  
  • CGS 1100C - Applications for Business


    Credits: 2

    Prerequisites: None
    Co-requisite or Prerequisite: None.
    Co-requisite: None.
    Course Description: Using technology to improve global business performance as well as the creation of value for organizations by using business process innovations and technology are discussed. Hardware concepts, operating systems, word processing, spread sheets, database, project management, networks, internet, World Wide Web, multimedia presentations, information systems, and other microcomputer hardware and software applications that are typically used in the work place are presented.
  
  • 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.
  
  • 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.

Computer Networks

  
  • CNT 3004C - Introduction to Computer Networks


    Credits: 3

    Prerequisites: COP 2272C - Computer Programming 1  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.
  
  • 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.
  
  • CNT 3502 - Data Communication


    Credits: 3

    Prerequisites: CIS 1000 - Introduction to Innovation and Technology  
    Course Description: Fundamentals of data communication, including network architectures, communication protocols, transmission standards, internet, and distributed computing are covered. Basic concepts of network management systems, including fundamentals of standards, models, languages, network management systems architectures and protocols as well as SNMP based protocols that manage TCP/IP networks are also discussed. Broadband network management systems and Web-based network management systems tools and applications are presented.
  
  • 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.
  
  • 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.
  
  • CNT 4526 - Wireless and Mobile Networking


    Credits: 3

    Prerequisites: CNT 3004C - Introduction to Computer Networks , COP 4531 - Algorithm Design & Analysis  
    Co-requisite or Prerequisite: None
    Co-requisite: None
    Course Description: This course will introduce students to wireless and mobile network architecture, protocols, and technologies. The course will cover topics including cellular networks, Wi-Fi, Bluetooth, ZigBee, etc.
  
  • ESI 4011 - Data Analytics for Smart City & Transportation


    Prerequisites: ESI 3005 - Introduction to Networks and a Connected World   
    Course Description: This course focuses on design strategies, simulation techniques, and data analytics to strengthen the knowledge of existing cities, and understand the needs and requirements of future cities through a data driven analysis. Smart cities untilize information and communication technologies to enhance the quality and performance of transportation, utility and energy services from cost and consumption perspectives. The course explains how smart cities operate ina controlled and monitored network environments and discusses techniques to work with data generated by transportation and communication networks, crowd-sensing systems and other relevant technologies.

Computer Programming

  
  • COP 2034 - Introduction to Programming Using Python


    Credits: 3

    Prerequisites: MAC 2311 - Analytic Geometry and Calculus 1   
    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.
  
  • COP 2271C - Introduction to Computation and Programming


    Credits: 3

    Prerequisites: MAC 2311 - Analytic Geometry and Calculus 1  
    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 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. 
  
  • COP 2272C - Computer Programming 1


    Credits: 3

    Prerequisites: COP 2271C - Introduction to Computation and Programming  
    Course Description: This is an intermediate programming course designed for students with prior programming experience in any language. It revises the fundamental programming concepts focusing on best practices in designing and writing efficient code. It also covers basic user-defined data types and the use of essential built-in data structures. After completing the course, students will have a solid command of computer programming and will be able to write medium-sized computer code.
  
  • COP 3330C - Computer Programming 2


    Credits: 3

    Prerequisites: COP 2272C - Computer Programming 1  
    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.
  
  
  • COP 3530 - Data Structures & Algorithms


    Credits: 3

    Prerequisites: COP 2272C - Computer Programming 1  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.
  
  • COP 3710 - Database 1


    Credits: 3

    Prerequisites: COP 2272C - Computer Programming 1   
    Course Description: The use of Structured Query Language (SQL) and broad knowledge of database design, implementation, and systems development are presented in this course. Emphasis is places upon data modeling concepts, approaches and techniques, and stages in database development processes (conceptual, logical and physical design).
  
  • COP 3729C - 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.
  
  • COP 3834C - Web Application Development


    Credits: 3

    Prerequisites: COP 2271C - 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.
  
  • 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   
    Co-requisite or Prerequisite: None
    Co-requisite: None
    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.

  
  • COP 4415 - Data Structures


    Credits: 3

    Prerequisites: COP 2272C - Computer Programming 1   
    Co-requisite or Prerequisite: None
    Co-requisite: None
    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.
  
  
  
  • 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.
  
  • COP 4620 - Compilers and Interpreters


    Credits: 3

    Prerequisites: COP 4415 - Data Structures 
    Co-requisite or Prerequisite: None
    Co-requisite: None
    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.
  
  • COP 4656 - Mobile Device Applications


    Credits: 3

    Prerequisites: COP 2272C - Computer Programming 1   
    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.
  
  • COP 4930 - Special Topics


    Credits: 1-3

    Prerequisites: CEN 4010 - Software Engineering  
    Co-requisite or Prerequisite: None
    Co-requisite: None
    Course Description: A comprehensive study on selected advanced topics in Computer Science. 
  
  • COP 4934C - Senior Design 1


    Credits: 3

    Prerequisites: CEN 4010 - Software Engineering   COP 3710 - Database 1   
    Co-requisite: None
    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.
  
  • COP 4935C - Senior Design 2


    Credits: 3

    Prerequisites: COP 4934C - Senior Design 1   
    Co-requisite: None
    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.
  
  • 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.
  
  • 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.
  
  • 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.
  
  • COP 5610 - Advanced Operating Systems Concepts


    Credits: 3

    Prerequisites: Graduate Standing
    Course Description: The course cover 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.
  
  • COP 5616 - High Performance Computing


    Credits: 3

    Prerequisites: COP 4520 - Introduction to Parallel and Distributed Computing  
    Course Description: Advanced topics in grid and cluster computing, parallel algorithms optimization, scalability studies, parallel languages, performance-oriented computing, concurrency, high performance scientific applications, virtualized HPC environments, memory hierarchies, and high throughput computing.
  
  • COP 5727 - Advanced Database Systems Design


    Credits: 3

    Prerequisites: Foundation in programming and databases, e.g. COP 3710 - Database 1  or equivalent.
    Co-requisite or Prerequisite: None
    Co-requisite: None
    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.

Computer Science and Information Systems

  
  • CIS 1000 - Introduction to Innovation and Technology


    Credits: 3

    Prerequisites: None
    Course Description: This is an introductory level course intended to prepare students for the more complex courses they will encounter in their academic careers, by introducing foundational  technology concepts and principles. The course is also intended to orient students to the various majors and concentration tracks in the I & T College.
  
  • CIS 2005 - Fundamentals of Applied Information


    Credits: 3

    Prerequisites: None
    Course Description: This course covers the concepts of knowledge management (KM), knowledge discovery (KD), data analytics, and information retrieval (IR). This is an introductory level course designed to familiarize students with the principles and fundamentals of information science theories and methods. The course is intended to introduce and explain foundations that students will need to be able to use and master in their upper level courses, internships and careers.
  
  • CIS 3301 - Business Intelligence


    Credits: 3

    Prerequisites: COP 3710 - Database 1  and QMB 3200 Advanced Quantitative Methods 
    Co-requisite or Prerequisite: None
    Co-requisite: None
    Course Description: This course discusses the application of decision support systems in the organizational environment. Designing and implementing decision support systems with a variety of development systems as well as language, concepts, structures and processes involved in the management of information systems including fundamentals of computer-based technology and the use of business-based software for support of managerial decisions are also covered. Emphasis will be placed on enterprise resources systems such as SAP and SAS.
  
  • CIS 4203 - Digital Forensics


    Credits: 3

    Prerequisites: CNT 3004C - Introduction to Computer Networks  
    Co-requisite or Prerequisite: CIS 4367 - Computer Security  
    Course Description: This course provides an introduction to fundamental concepts in digital forensics. Topics covered include File Systems, Allocated and Unallocated Space, Standard Operating Procedures, Quality Assurance, hardware, software, accreditation, and certification are all important aspects of an effective lab. Collecting Evidence, Windows System Artifacts, Antiforensics, Legal Principles for Digital Forensics, Internet and Email Forensics, Network Forensics, Mobile Device Forensics.
  
  • CIS 4204 - Ethical Hacking


    Credits: 3

    Prerequisites: CNT 3004C - Introduction to Computer Networks  
    Co-requisite or Prerequisite: CIS 4367 - Computer Security  
    Course Description: This course explores the topic of Computer Security from the hacker’s perspective. Latest hacking tools are explored and countermeasures are proposed. Topics covered: penetration testing, reconnaissance, scanning, exploitation, backdoors, rootkits, viruses, worms, packet sniffers, social engineering, phishing, Denial of Service.
  
  • CIS 4320 - Design Science


    Credits: 3

    Prerequisites: None
    Course Description: This course introduces students to the paradigm of Design Science and the Information Systems Research Cycle (ISRC). Students will learn to apply ISRC to solve real business problems via the IT Artifact using methods, models and theories to design, evaluate and deliver IT solutions. This course meets communication/writing-intensive requirements (W).
  
  
  
  • CIS 4367 - Computer Security


    Credits: 3

    Co-requisite or Prerequisite: CIS 4362 - Applied Cryptography 
    Co-requisite: COP 4610 - Operating Systems Concepts  
    Course Description: This course covers security issues in different aspect of computing. Topics covered are: access control mechanisms, authentication models, and vulnerability detection. Attacks and mitigation methods at the OS level. Database and operating system security issues, mobile code, security kernels. Malicious code, Trojan horses and computer viruses. Security policy formation and enforcement.
  
  • CIS 4369 - Web Application Security


    Credits: 3

    Prerequisites: CIS 4362 - Applied Cryptography  
    Course Description: This course’s main focus is on securing web-based communications and applications. The security vulnerabilities involved in applications such as e-commerce that are based on communicating sensitive data over the Internet is covered. Web security issues, such as SQL injection and cross site scripting along with how to defend and protect against such attacks is covered. Securing the web client, the communication channel, and the web servers is reviewed in detail.
  
  • CIS 4510 - Advanced System Development and Production


    Credits: 3

    Prerequisites: CAP 4733 - Senior Capstone 1: Systems Acquisition, Integration, and Implementation  
    Course Description: This course is a second course in system design and development, focusing on the production readiness review process of an already vetted system development plan. As such the course assumes experience with project management, system analysis and design, and high level programming experience. Students will utilize the system design and implementation plan created in CAP 4733 Systems Acquisition, Integration, and Implementation. This is an advanced course covering critical thinking and problem solving techniques applied to information systems, and the fundamentals and complexities associated with software development and acquisition.
  
  • CIS 5616 - Advanced Business Intelligence Applications


    Credits: 3

    Prerequisites: Strong foundation in programming and databases, e.g. COP 3710 - Database 1  
    Course Description: Advanced design and implementation of decision support systems with emphasis on complexities of language, structures and processes involved in the management of information integration in computer-based technology and business-based software are covered in this course. Enterprise resources systems such as SAP, Oracle and SAS are also presented.
  
  • CIS 5910 - Directed Independent Research


    Credits: 3

    Prerequisites: Permission from VP of Academic Affairs or Designee
    Course Description: This course supports students who wish to explore special interests in an area supported by the College of Innovation and Technology. Students will conduct intensive research and produce significant written documentation of an experiment, research exploration, or special interest project in technology.

Computer Software Engineering

  
  • CEN 4010 - Software Engineering


    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   
    Co-requisite or Prerequisite: None
    Co-requisite: None
    Course Description: The course covers object-oriented software engineering, the software development life cycle, system specification, software design patterns, and the methods of software measurement and estimation.

  
  • CEN 4065 - Software Design and Architecture


    Credits: 3

    Prerequisites: CEN 4073 - Software Requirements Engineering  
    Course Description: This course covers the engineering processes of building the software architecture and designing the software product according to design criteria. Software design is the process to define the characteristics of a software system. The course begins with design fundamentals, including concepts, context and
    processes. Then the software structure and architecture; user interface design and design quality analysis and evaluation are covered within the context of real-world challenges.
  
  • CEN 4072 - Software Verification and Quality Assurance


    Credits: 3

    Prerequisites: CEN 4073 - Software Requirements Engineering  
    Course Description: This course introduces software verification and validation techniques with a particular focus on software testing. The course also provides students a comprehensive understanding of the software quality assurance and techniques used to assess software quality.
  
  • CEN 4073 - Software Requirements Engineering


    Credits: 3

    Co-requisite: CEN 4010 - Software Engineering  
    Course Description: This course covers software specification and requirements as well as software project management and how to effectively allocate resources. The course will provide the students with concepts of software requirement modeling, software requirements specification, prototyping requirements, testing and validating
    requirements, and requirements management. The students will practice managing a software project based on requirements and allocate resources.
 

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