This course introduces students to Engineering Ethics, as a set of moral principles that relate to Engineering projects and designs. The course explores creative ways of reconciling conflicting moral claims. It outlines the responsibilities of Engineers towards public safety and the environment, within economic constraints and governing laws. A systematic Engineering Design process is introduced. Each design stage explores relevant methods and their ethical implications. The course critically examines litigations that involve the engineering profession in relation to product liability.
Thermo-physical properties of pure substances and gases. 1st law of thermodynamics, conservation of energy, and closed and open systems. Limitations and efficiencies of energy conversion processes. Introduction to the 2nd law of thermodynamics and entropy. Applications in Engineering.
Introduction to computing, data types and variables, expressions, selection and repetition control structures, library and user-defined functions, files and streams, arrays, library and user-defined classes, pointers.
Introduction to the basic concepts and principles of engineering economics. Familiarization of the different cost components, cost estimation techniques, cash flow analysis, time value of money, and measures of project performance. Comparing alternatives. Application of engineering practice and entrepreneurship to engineering design and projects.
This course offers the students the opportunity to integrate their knowledge, skills, and practical experience with their peers and the course instructor. The course will contribute to the student’s professional development focusing on skills and professional experience. It consists of presentations on current research or applied projects in engineering, informatics, or related fields. The presentations are delivered by the course instructor, registered PhD students, faculty members, or invited speakers.
This course provides students with a comprehensive understanding of research methodologies. It will cover the fundamental concepts of theory and scientific research, literature search and referencing, design and analysis of experiments, problem identification and formulation, research design including experimentation, measurements and sampling, data analysis, and paper and thesis organization. The course also includes proposal presentation, ethical issues in research and the importance of time management and multi-disciplinary research.
This course focuses on the use of numerical search and optimization tools for purposes of conducting advanced technical decision-making. It will provide students with the fundamentals of the theory of optimization. The topics to be covered in this course include: formulation of optimization problems, mathematical modelling, non-gradient and stochastic search techniques, gradient-based optimization algorithms for unconstrained and constrained problems, numerical methods for sensitivity analysis, global optimization and surrogate modelling. A series of practical examples and case studies will complement the course material
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