This course introduces computational problem solving. Basic problem-solving techniques and algorithm development through the process of top-down stepwise refinement and functional decomposition are introduced throughout the course. Classical numerical problems encountered in science and engineering are used to demonstrate the development of algorithms and their implementations. May not be taken for credit by Computer Science, Software Engineering, or Computer Engineering majors. This course is designed for Electrical Engineering and Micro-Electronic Engineering majors and students interested in the Electrical Engineering minor.

This course introduces the student to the basic components and methodologies used in digital systems design. It is usually the student's first exposure to engineering design. The laboratory component consists of small design, implement, and debug projects. The complexity of these projects increases steadily throughout the term, starting with circuits of a few gates, until small systems containing several tens of gates and memory elements. Topics include: Boolean algebra, synthesis and analysis of combinational logic circuits, arithmetic circuits, memory elements, synthesis and analysis of sequential logic circuits, finite state machines, and data transfers.

Students will learn a variety of leading edge computing technologies and create computing-based solutions to address organizational requirements using these technologies. This will include an introduction to artificial intelligence (AI), contemporary hardware platforms, how they operate and interact with the components of the operating systems that drive them, and how to deliver these solutions using virtualization such as cloud computing. Ultimately the course is designed to bridge the gap between theoretical knowledge and practical application. Students will develop an understanding of contemporary computing systems through practical assignments and projects that integrate the various aspects of contemporary computing.