22 courses with the subject ISE, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
ISE 102Introduction to Intelligent Systems Engineering4
Interdisciplinary introduction to intelligent systems, covering topics such as: how intelligent systems interact with the physical world through inputs and inputs, algorithms to transform inputs to outputs, handling data in intelligent systems, binary numbers, discrete mathematics, basic logic operations, computer architecture, and problem-solving.
Introduction to fundamentals of programming using C/C++, with a strong emphasis on object-oriented programming (OOP). Structured programming in C before transitioning to C++ to explore OOP alongside basic to intermediate data structure implementations. Skills in both paradigms with a particular focus on using OOP to solve complex problems effectively.
Introduction to concepts of intelligent systems, focusing on impact on societal structures and human behavior. Exploration of AI within social institutions, examining the ethical implications and potential for societal change, emphasis on the role of intelligent systems in shaping public policies and the cooperative strategies necessary for a sustainable future.
Introduction to theory, analysis, and design of electric circuits. Study of voltage, current, power, energy, resistance, capacitance, and inductance. Use of Kirchhoff’s laws, node analysis, mesh analysis, Thevenin’s theorem, Norton’s theorem, steady state, and transient analysis, etc.
Introduction to computer organizations, data representation, CPU organization, I/O memory and communication, implementation of a microcontroller or microprocessor embedded systems, assembly language programming, interfacing to peripherals, interrupt handling and debugging techniques.
Concepts and practice behind deploying AI applications as cloud services that others can access. Importance of engineered robustness and trustworthiness are covered. Computer system design principles applied to practice, resulting in a rounded practicum experience.
Study of linear dynamic systems, and methods for examining, evaluating, and autonomously controlling them. Examination of several standard methods for linear system analysis and design using time and frequency domain tools (such as transfer functions, pole placement, stability and performance criteria, etc.). Consideration of analytical and numerical methods to explore signals, dynamics systems, and control systems.
Fundamentals of digital signal processing (DSP). Topics include: A/D-D/A conversion and quantization, number representations and finite word length effects; FIR, IIR, and lattice filter structures, block diagram, and equivalent structures; multi-rate DSP and filterbanks; digital filter design methods and verification; and DSP hardware architecture.
Introduction to the fundamental principles of systems engineering and their application to developing complex systems. Study of how systems engineering viewpoint can address engineering challenges and the essential role of systems engineering in project management.
Introduction to the architecture, design, and analysis of cyber-physical systems (CPS), including the principles of design, specification, and modeling. Explanation of core ideas related to CPS design including model-based design, distributed algorithms, system specification and verification, control theory, and real-time systems.
Focus on image-guided control of robotic manipulators, including mathematical modeling concepts and implementation via open-source software libraries, robotic manipulators, and RGBD cameras. Analysis of complex 3D motions of robotic systems and integration into a closed-loop vision control strategy via different programming tools.
Introduction to human-centered design (HCD) and engineering principles and practices. Application of these principles to the area of artificial intelligence and intelligent systems, such as autonomous vehicles, etc. Focus on developing collaborative strategies between human users and autonomous systems for safety and effectively utilizing state-of-the-art autonomous features.
Study of the Internet of Things (IoT) and related technologies, including solving practical programs using IoT, embedded, and edge technologies, as well as IoT device programming, sensing, actuating, communications, networking, and cloud technologies.
Fundamentals of wireless sensor networks, including hardware and radio architecture through protocols and software to applications. Sensor network architectures, hardware platforms, physical layer techniques, medium access control, routing, topology control, quality of service management, localization, time synchronization, security, storage, and other advanced topics.
First semester of a two-semester capstone course in Intelligent Systems Engineering. Topics include: identifying a suitable project, researching and evaluating existing solutions, proposing a new solution, performing concept definition and requirements analysis, preparing design documents (plans and specifications), and presenting a solution to a review board.
Second semester of a two-semester capstone course in Intelligent Systems Engineering. Topics include: implementing the project plan, which includes working with stakeholders, executing the hardware design and implementation, developing system software, testing solutions, and deploying the solution. A functional model of the solution, a final report, and a project presentation are required.
Investigation under faculty supervision beyond what is offered in existing courses. Written experience report and oral presentation required. For further information, consult the Directed Individual Studies section in this catalogue.
ISE 495Seminar in Intelligent Systems Engineering1
Presentations on current topics in intelligent engineering education and related subjects. Speakers may come from campus, other universities, or business, industry, or government.
ISE 498Internship in Intelligent Systems Engineering3
Academic training and practical experience through work in a private company or public agency. Faculty supervision and evaluation of all study and on-site activity. Open to students of junior or senior standing who have been approved by the faculty supervisor, department chair, and dean. Written experience report and oral presentation required.
