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Course Criteria
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0.00 Credits
first-year experience course introduces students to Boston University, the College of Engineering, and the field of engineering. Students meet with faculty and student advisors and attend lectures to broaden their knowledge of the inner workings of the College and to gain a better understanding of engineering as a discipline and the ethical responsibilities of an engineer. Includes academic policies and special programs along with support services. 0 cr.
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3.00 Credits
of linear equations and matrices. Vector spaces and linear transformation using matrix notation, determinants, and eigenvalues and eigenvectors. Examples drawn from engineering applications. Cannot be taken for credit in addition to CAS MA 142 or MA 242. 2 cr.
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4.00 Credits
introduction to engineering problem solving using a modern computational environment. Basic procedural programming concepts include input/output, branching, looping, functions, file input/output, and data structures such as arrays and structures. An introduction to basic linear algebra concepts such as matrix operations and solving sets of equations. Introduction to numerical methods, for example least squares solutions and their use for curve fitting. Programming projects provided by all College of Engineering departments will reinforce these concepts and introduce engineering freshmen to the various disciplines. 4 cr.
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4.00 Credits
to engineering analysis and/or design offered by participating engineering faculty. Course presents students with key concepts and techniques relevant to an applied area of engineering. Limited to freshmen and sophomores (students with less than 64 credits toward degree requirements). 4 cr.
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2.00 Credits
to design and processing steps required in manufacturing. Specialized project involving the design, scheduling, budgeting, and building of a project selected by the student with the consent of the instructor. Includes lab. 2 cr.
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4.00 Credits
of technology as a fundamental element of and driving force in our culture. Balanced understanding of the promises, consequences, and dilemmas brought about by specific technologies. Opportunity to improve critical thinking abilities and to broaden perspectives and sense of responsibility of new professionals as they become involved in decisions related to technology. ENG EK 280 (for engineering students) meets with CAS SO 277 (for non-engineering students) and fulfills 4 credit hours of social science elective as a sociology course. The course cannot be used as a core elective. 4 cr.
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4.00 Credits
CAS PY 211 and ENG EK 127; coreq: CAS MA 225. Fundamental statics of particles, rigid bodies, and trusses; dynamics of particles: Newton's laws of motion; energy and momentum methods. Application of vector analysis and introduction to engineering design. Includes design project. (MET EK 311 and EK 312 fulfill this requirement; however, only 4 credits can be applied towards the graduation requirement.) 4 cr.
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4.00 Credits
CAS MA 226 and CAS PY 212. Introduction to electric circuit analysis and design; voltage, current, and power, element I-V curves, circuit laws and theorems; energy storage; frequency domain, frequency response, transient response; sinusoidal steady state and transfer functions; operational amplifiers, design. Includes lab. (MET EK 317 and EK 318 fulfill this requirement; however, only 4 credits can be applied toward the graduation requirement.) 4 cr.
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4.00 Credits
junior standing or consent of instructor. Analysis of engineering alternatives for replacement. Present worth analysis. Cost control, budgeting, and indirect costs and their allocation. Company startups, stock ownership, and annual reports. Cost optimization, economic life, taxes, inflation, inventories, and depreciation accounting. Contract negotiations, professional ethics, and cost proposal preparation. Evaluation of public projects. 4 cr.
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3.00 Credits
CAS MA 123 and ENG EK 127 and at least two semesters of physical science. Introduces fundamental methods for scientific computing in the context of massively parallel computation. Discussions are organized around important algorithmic concepts and specific applications chosen to illustrate the methods. Different parallel computation models are evaluated within the framework of specific algorithms. Students are required to observe, modify, and/or design programs suitable for running on highly parallel architectures such as the Connection Machine, and on current multiprocessor systems. In addition, students are required to develop competence with a variety of tools useful in the parallel computing environment including graphical methods to analyze large data sets, the high-level parallel language C++, and X-windows. Same as CAS CS 420. Alternates with CS 420. 4 cr.
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