Computing for Science and Engineering
Learning Objective:To expose students to computational concepts, tools, and skills useful for research in computational science and engineering, beyond what is learned in a first programming course (and basic mathematics courses). A related aim is to prepare students for other courses in CS&E.
Description:Intro course for Computational Engineering concentration. Computational concepts, tools, and skills for computational science and engineering: scripting for numerical computing, scripting for file processing, high performance computing, and software development. Project may be required. Credit in this course may not be used toward a graduate degree in Computer Science. Fall 2016 Syllabus
Topics Covered:Unix; Python scripting and C programming for numerical computation and file processing; introduction to data structures and computer science concepts; parallel programming; introduction to object-oriented programming, software engineering, and GUIs; matrix operations and interpolation.
Prerequisites:Familiarity with matrix algebra is expected. Some programming experience in C, C++, Java, or Fortran or extensive scripting experience; also, commensurate computer skills.
Applied / Theory:70 / 30
Web Content:Syllabus, lecture notes, homework assignments, and solutions will be available via Piazza; grades via Blackboard.
Homework:About six or seven assignment sets, much of it requiring the writing of programs. Submitted via Blackboard.
Exams:Two 75-minute evening exams, one final.
Textbooks:Official textbook information is now listed in the Schedule of Classes. NOTE: Textbook information is subject to be changed at any time at the discretion of the faculty member. If you have questions or concerns please contact the academic department.
Tentative: None Required - Notes will be distributed with links to Web resources.