This course provides the fundamental concepts and principles underlying computer architecture design and instruction set architectures. It highlights the lower end operations of a typical computer, and the way computers manage their resources during operation. The topics in this course include Von Neumann architecture, CPU, registers, MIPS assembly language, instruction types and addressing, memory, interrupts, and I/O, the system bus. Instructions: fetch and execute cycle, machine language instructions.

This course provides students with the necessary knowledge, tools, and techniques to provide software solutions to real-world problems using concepts of object-oriented programming.The Topics in this course include analysis of programming techniques: unstructured programming, procedural and modular techniques, problems, and strategies. Object-oriented structure and development. Object-oriented principles and programming concepts: inheritance, encapsulation, polymorphism, derived and abstract classes, interfaces, methods of overloading overload resolution.

This course provides the knowledge required to understand the structure and operation of the operating systems and its design as a software interface to a computer’s hardware and architecture.The topics covered include the evolution of the operating system, characteristics, and structure. Operating systems and programming. Design principles: layered OS structure, monolithic, and microkernel OS model, kernel, and user modes. System calls and interrupts. Processes and threads. Scheduling and dispatch. Deadlock and starvation. Concurrency and synchronization.

The objective of the course is to provide students with the theoretical foundation and concepts required to acquire, analyze, and process signals in both time and frequency domains, and design systems for processing the signals. This course will cover concepts of signal characteristics and representation in the time and frequency domains, and signal properties. Systems characteristics and properties such as linearity, causality, time invariance, memory, stability, and invertibility. LTI systems and convolution.

This course provides students with the mathematical analysis techniques required for solving numerical problems encountered in the field of engineering. It promotes the use of MATLAB for solving mathematical problems that require numerical solutions.The course involves matrices, linear homogeneous systems, and eigenvectors and values. Numerical methods and errors, stability, and convergence. Solving systems of linear equations: Gaussian elimination, Gauss-Jordan, LU decomposition methods.