TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Master's Degree Without Thesis
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	10
NAME OF LECTURER(S)	-
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Learn scientific computing basic principles in engineering problems. 2) Have an ability for commenting on error analysis and their results. 3) Formulate measurements that depend on physiological parameters in biomedical field. 4) Applying course units in homeworks on MATLAB or similar programs.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Interpolation and polynomial approximation, the divided differences, Hermit interpolation, polynomial numerical differentivation, curve fifting, Interpolation by spline functions, Richardson's extrapolation, Numerical Integraiton, Romberg integration, finite element method, finite difference method, boundary element method. MATLAB applications.
COURSE CONTENTS	WEEK TOPICS 1st Week Introduction. Approximations in scientific computing, computer arithmetics 2nd Week Linear Equations. Linear system properties, sensitivity, solving linear systems, special types of linear sysems,iterative methods used in solving linear equations 3rd Week Linear Equations. Linear system properties, sensitivity, solving linear systems, special types of linear sysems,iterative methods used in solving linear equations 4th Week Linear Equations. Linear system properties, sensitivity, solving linear systems, special types of linear sysems,iterative methods used in solving linear equations 5th Week Linear Least Squares Problems and Properties. Problem transformation, orthogonalization methods, singular value decomposition 6th Week Linear Least Squares Problems and Properties. Problem transformation, orthogonalization methods, singular value decomposition 7th Week Eigenvalue Problems. Eigenvalues nad eigenvectors, properties, problem transormations, eigenvalue and eigenvector calculations 8th Week Midterm Exam 9th Week Eigenvalue Problems. Eigenvalues nad eigenvectors, properties, problem transormations, eigenvalue and eigenvector calculations 10th Week Nonlinear Equations.Properties of nonlinear system, convergense rate, stopping criteria, nonlinear euations in one plane. 11th Week Nonlinear Equations.Properties of nonlinear system, convergense rate, stopping criteria, nonlinear euations in one plane. 12th Week Optimization. Optimization problems, properties, optimization in one plane, unconstrained optimization, constrained optimization 13th Week Optimization. Optimization problems, properties, optimization in one plane, unconstrained optimization, constrained optimization 14th Week Interpolation and Properties. Polinomial interpolation, piecewise polinomial interpolation
RECOMENDED OR REQUIRED READING	(1)Scientific Computing, An Introductory Survey, Micheal T. Heath, 1997, McGraw-Hill Companies Inc. (2)Steven C. Chapra ve Raymond P. Canale, Numerical Methods for Engineers (4th Edt.), 2002, McGraw-Hill Companies Inc
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Problem Solving
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 35 Assignment 1 20 Total(%) 55 Contribution of In-term Studies to Overall Grade(%) 55 Contribution of Final Examination to Overall Grade(%) 45 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 72 72 Preparation for Quiz 1 12 12 Individual or group work 2 3 6 Preparation for Final exam 1 24 24 Course hours 14 3 42 Preparation for Midterm exam 1 11 11 Laboratory (including preparation) 0 0 0 Final exam 1 96 96 Homework 1 24 24 Total Workload 287 Total Workload / 30 9,56 ECTS Credits of the Course 10
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No