This course covers the use of numerical computing techniques for mathematical and scientific problems. Topics include: floating-point representation, approximations and computer arithmetic, error analysis, conditioning and stability, Taylor series, roots of nonlinear equations, Newton's method, curve fitting and interpolation solution to systems of linear equations using techniques such as LU decomposition, Gaussian elimination, Jacobi, Gauss-Seidel Iteration, eigenvalue problems, numerical integration and solutions to differential equations.
Introduction to Scientific Computing (CS 409)
2018 Summer
Faculty of Engineering and Natural Sciences
Computer Sci.& Eng.(CS)
3
6
Mehmet Keskinöz keskinoz@sabanciuniv.edu,
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English
Undergraduate
CS201
Formal lecture,Interactive lecture
Simulation
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Programs\Type | Required | Core Elective | Area Elective |
Computer Science and Engineering | * | ||
Computer Science and Engineering | * | ||
Electronics Engineering | * | ||
Electronics Engineering | * | ||
Industrial Engineering (Previous Name: Manufacturing Systems Engineering) | * | ||
Materials Science and Nano Engineering | * | ||
Materials Science and Nano Engineering (Previous Name: Materials Science and Engineering) | * | ||
Mathematics Minor | * | ||
Mechatronics Engineering | * | ||
Mechatronics Engineering | * | ||
Microelectronics | * | ||
Molecular Biology, Genetics and Bioengineering | * | ||
Molecular Biology, Genetics and Bioengineering (Pre. Name: Biological Sciences and Bioengineering) | * | ||
Telecommunications | * |
CONTENT
OBJECTIVE
Learning numerical methods such as interpolation, integration, derivation and finding roots.
LEARNING OUTCOMES
- Apply the basic numerical concepts such as error analysis, round off error, subtractive cancellation, and error magnification.
- Apply fundamental numerical analysis tools and identify their limitations
- Apply these basic numerical principles to model and analyze engineering problems.
- Gain hand on experience by developing computational tools for applied numerical problems.
Update Date:
ASSESSMENT METHODS and CRITERIA
Percentage (%) | |
Final | 40 |
Midterm | 30 |
Individual Project | 30 |
RECOMENDED or REQUIRED READINGS
Textbook |
Numerical Analysis, J. Douglas Faires and Richard L. Burden, Thomson Press. |
Readings |
Numerical Methods for Engineers, S.C. Chapra & R.P. Canale, 6th Edt., McGraw-Hill, 2010. Numerical Methods using MATLAB, J.H. Mathews & K.D. Fink, 4th Edt., Pearson, 2004. |