Graduate
Institute of Graduate Studies
Mathematics And Computer Science
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Advanced Numerical Analysis

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
YMB0007 Advanced Numerical Analysis 3/0/0 DE Turkish 7
Course Goals
At the end of the course, the students would be acquainted with the basic concepts in advance numerical methods .
Prerequisite(s) None.
Corequisite(s) None.
Special Requisite(s) The minimum qualifications that are expected from the students who want to attend the course.(Examples: Foreign language level, attendance, known theoretical pre-qualifications, etc.)
Instructor(s) Assist. Prof. Dr. M. Fatih UÇAR
Course Assistant(s) None.
Schedule Will be announced in the forthcoming term.
Office Hour(s) Yrd. Doç. Dr. Hikmet ÇAĞLAR, AK/3-A-09.
Teaching Methods and Techniques Lecture and Homework
Principle Sources Lectures on advanced Numerical Analysis 1967, F. John
Other Sources  -
Course Schedules
Week Contents Learning Methods
1. Week Solutions of Nonlinear Equations Lecture and homework
2. Week Solutions of Linear Systems Lecture and homework
3. Week Computer Arithmetic and Roundoff Errors Lecture and homework
4. Week Algorithms and Convergence Lecture and homework
5. Week Error Analysis for Iterative Methods Lecture and homework
6. Week Accelerating Convergence Lecture and homework
7. Week Interpolation and the Lagrange Polynomial Lecture and homework
8. Week Midterm Midterm
9. Week Divided Differences Lecture and homework
10. Week Divided Differences Lecture and homework
11. Week Hermite Interpolation Lecture and homework
12. Week Numerical Integration Lecture and homework
13. Week Numerical Integration Lecture and homework
14. Week Eigenvalues and Eigenvectors Lecture and homework
15. Week Final Exam Week Final Exam
16. Week Final Exam Week Final Exam
17. Week Final Exam Week Final Exam
Assessments
Evaluation tools Quantity Weight(%)
Midterm(s) 1 50
Final Exam 1 50


Program Outcomes
PO-1Have scientific research in mathematics and computer science in the level of theoretical and practical knowledge.
PO-2On the basis of undergraduate level qualifications, develop and deepen the same or a different areas of information at the level of expertise, and analyze and interpret by using statistical methods
PO-3Develop new strategic approaches for the solution of complex problems encountered in applications related to the field and unforeseen and take responsibility for the solution.
PO-4Evaluate critically skills acquired in the field of information in the level of expertise and assess the learning guides.
PO-5Transfer current developments in the field and their work to the groups inside and outside the area supporting with quantitative and qualitative datas as written, verbal and visual by a systematic way.
PO-6Use information and communication technologies with computer software in advanced level.
PO-7Develop efficient algorithms by modeling problems faced in the field and solve such problems by using actual programming languages.
PO-8Respect to social, scientific, cultural and ethical values at the stages of data collection related to the field, interpretation, and implementation.
PO-9To solve problems related to the field, establish functional interacts by using strategic decision making processes.
PO-10Establish and discuss in written, oral and visual communication in an advanced level by using at least one foreign language.
Learning Outcomes
LO-1Estimate computation errors
LO-2Analyze sensitivity of the problem to be solved;
LO-3Select/propose numerically stable methods;
LO-4Understand important properties for a number of basic methods
LO-5Analyze results computed
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10
LO 1
LO 2
LO 3
LO 4
LO 5