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  • 3.00 Credits

    Prerequisite(s): MAT 1010 or MAT 1015 with a B or better, or ACT score 23 or higher or ALEKS score 38 or higher. Pass CS 1420 Entrance Exam.. Teaches techniques, tools and skills necessary to effectively program computers. Demonstrates algorithmic thinking using procedural and object-oriented concepts. Presents problems of increasing size and complexity requiring standard libraries and other appropriate language constructs. May be delivered online.
  • 3.00 Credits

    Prerequisite(s): CS 1400. Covers practical Java programming in-depth, including abstract classes and interfaces, proper use of the packages Java.lang, Java.io, and Java.util, GUI design and implementation, and programming.. Lab access fee of $45 for computers applies.
  • 3.00 Credits

    Prerequisite(s): (CS 1410 or INFO 2200) and MATH 1050 or higher. Covers algebraic structures applied to computer programming. Includes logic, sets, elementary number theory, mathematical induction, recursion, algorithm complexity, combinatorics, relations, graphs, and trees.. Lab access fee of $45 for computers applies.
  • 3.00 Credits

    Prerequisite(s): CS 1410. Introduces C++ programming for students with prior programming experience. Covers language fundamentals, core standard library components, error handling, value semantics, pointers and memory management, object-oriented programming, and templates.. Lab access fee of $45 for computers applies.
    General Education Course
  • 3.00 Credits

    Prerequisite(s): CS 1410. Uses data abstraction to design and implement modular programs of medium size and complexity. Structures solutions to problems using common data structures and algorithms such as advanced arrays, lists, stacks, records, dynamic data structures, searching and sorting, vectors, trees, linked lists, and graphs. Evaluates alternative solutions to problems. Analyzes algorithmic complexity metrics in Big-O notation.. Lab access fee of $45 for computers applies.
  • 3.00 Credits

    Prerequisite(s): CS 2300, CS 2420. Presents concepts, methodology and best-practices necessary to develop large scale software projects. Includes step-wise software requirements analysis, design, implementation, testing and release. Discusses software generation, reuse, scheduling, verification, and maintenance. Emphasizes current "real world" industry best-practices and tools.. Lab access fee of $45 for computers applies.
  • 3.00 Credits

    Prerequisite(s): CS 1410 or DWDD 2720 or INFO 1200. Covers design and development of browser-based programs with an emphasis on single-page applications. Teaches generation and modification of HTML via JavaScript, debugging techniques, communicating with web servers, and use of XML and JSON.. Lab access fee of $45 for computers applies.
  • 3.00 Credits

    Prerequisite(s): CS 2810 or (INFO 1200 and IT 1600). A rigorous introduction to computer networking theory and technologies for Computer Science and Information Technology majors. Includes theory of data communications protocols; theory and design of transmission systems; transmission media; and communication software. Emphasizes the lower layers of the Open Systems Interconnection model. Requires lab exercises to be completed outside of lecture.. Lab access fee of $45 for computers applies.
  • 3.00 Credits

    Prerequisite(s): CS 1410, CS 2300, CS 2600, CS 2370. Pre- or Corequisite(s): MATH 1210. Continues CS 2600 Computer Networks I. Focuses on the upper layers of the OSI and Internet models. Covers Internet (TCP/IP) protocols, routing theory, transport protocols, network application interfaces, presentation formatting, information theory and compression, cryptography, and other emerging technologies as time permits. Requires lab exercises and programming assignments to be completed outside of lecture.. Lab access fee of $45 for computers applies.
  • 3.00 Credits

    Prerequisite(s): CS 1400. Explores a variety of data generating processes of importance for causal inference with computer simulations. Includes stratified sampling, inverse probability weighting, matching, blocking, propensity, sensitivity, causal graphs, d-separation, identifiability, the causal Markov condition, and the back-door criterion for selecting an admissible set of covariates. Examines causal mechanisms, the Rubin causal model, and both deterministic and stochastic counterfactuals. Develops ethical A/B testing procedures.