An introduction to computer programming using the C++ language. The course will teach the concepts of problem-solving and procedural design, and will introduce object-oriented programming through the use of C++. Students will learn to design, code, test, debug, and document computer programs.

This course highlights various technological updates of recent years and provides students with highly relevant and current information as it pertains to the practice of software development. The topics addressed within the course include the areas of Software Engineering best practices, dependability & security, advanced Software Engineering concepts, and software management. The course strives to set students on the journey to becoming the innovators of tomorrow and creating software that will make our world is a better, safer, and more advanced place to live. The course is an introduction to Software Engineering covering the development life cycle models, requirements analysis and specification design concepts and methods, testing, maintenance, CASE tools and management concerns. Additional topics may include reuse metrics, experimentation, reengineering, development environments, and standards.

This course will teach students the introductory skills of programming, problem solving and algorithmyic thinking in Python. Topics include variables, input/output, conditional statements/logic, Boolean expressions, flow control, loops and functions. We will use the Cloud 9(http://c9.io) integraded development environment (IDE).

This course is a continuation of CSCI 200 with a focus on objects, classes, and data structures in C++. Students will learn the implementation and use of C++ objects to represent mathematical objects, as well as abstract data types in C++ programs.

The theory and practice behind computer networking design and implementation, particularly related to the internet. Topics include: structure and components of computer networks; routing, addressing, packet switching; network protocols; flow and error control; local area networks; network security.

Introduction to statistics with an emphasis on theory and application. Includes probability; sampling; t-test, analysis of variance; chi square; correlation; regression; effect size. Intended as an introduction for students meeting additional statistics, data science, or data analysis coursework. This course does not count toward the major or minor in mathematics.

A study of algorithms and methods of analysis of their complexity: asymptotic analysis of complexity, searching and sorting algorithms, language processing algorithms, NP-completeness.

An introduction to the theory, design, and implementation of programming languages - the course covers the general concepts common to all programming languages. Language types (functional, procedural, object-oriented, scripting) are compared and implementation strategies are discussed.

A study of the techniques and algorithms of operating systems, and implementation of these algorithms. Topics include computer organization; processes, synchronization, scheduling; I/O; memory management; file systems.

This course examines algorithms and systems that can learn without being explicitly programmed. Topics include: clustering, classification, prediction, supervised learning, unsupervised learning, decision trees, support vector machines, random forests, and regression. The course begins with an overview of machine learning systems, then escorts students through an end-to-end machine learning project example involving regression. Classification systems are considered and the metrics used to evaluate classifiers are discussed. The training of linear models is discussed, with special attention paid to closed-form solutions and gradient descent algorithms.

This course will introduce students to various ethical issues related to computing technology and the internet. Free/open source software, cybersecurity, privacy, monopoly power and artificial intelligence will be considered within a Christian framework.