Computer Science

This course is an introduction to computer programming that aims to develop fundamental programming skills using Java as the teaching language. Topics include data types, control structures, arrays, object-oriented design, abstraction, encapsulation, algorithms, documentation, testing, and debugging

This course concentrates on the design function of the operating systems of multiuser computers. Topics include time sharing methods of memory allocation and protection, files, CPU scheduling, input/output management, interrupt handling, process synchronization, deadlocking and recovery, and design principles

Python Programming enables students to implement fundamental principles of modern programming using the Python programming language and problem-solving techniques related to computing

This course provides a basic introduction to how artificial intelligence (AI) methods solve problems that are difficult or impractical to solve with other methods. The focus in the course is on the fundamentals of how to determine when an AI approach is appropriate for a given situation, then selecting an AI scheme, and, subsequently, implementing it. AI methods will be chosen from various search algorithms and techniques, use of game theory, simple logic, theorem proving, and structured representation. Finally, neural networks, machine learning, robotics philosophy, ethics, and the future of AI will be explored

This course builds upon the foundations of basic/intermediate algebra to further develop students' mathematical knowledge and professional skill set. Students in a wide range of disciplines and careers build real-world technical skills through the use of technology, data, and application modeling. This course also emphasizes critical thinking, logic, problem solving, and analytical skills. Topics include a review of pre-algebraic concepts, linear equations and inequalities, quadratic equations, functions (linear, quadratic, polynomial, exponential, and logarithmic), real-world applications using modeling and applying regression analysis to data.

This course aims at serving the needs of a wide student audience, including students in engineering, mathematics, the physical and life sciences, and economics. It is constructed around multiple focal points with the intention of helping students become creative and efficient problem solvers. The course uses technology as a means of discovery for numerical, graphical, and analytical solutions to problems. It also emphasizes communication skills and requires students to interpret, describe, discuss, justify, and conjecture as they search for solutions to problems. Real-life applications provide links with students' everyday life. Topics covered include the Cartesian plane, limits and continuity, problems of tangents, velocity and instantaneous rates of change, rules for differentiation, implicit differentiation, maxima and minima theory, antiderivatives and the indefinite integral, exponential and logarithmic functions, and the area between curves.

This course involves an investigation of various data structures, including stacks, queues, lists and trees, and searching and sorting techniques.

Computer Architecture covers the nature and limitations of computers. The CPU is covered in detail, including processor, control, and memory design.