1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
  3. ELECTRICAL AND ELECTRONICS ENGINEERING DEPARTMENT
  4. 1181 Electrical and Electronics Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ELK 0565COMPUTER AIDED NUMERICAL ANALYSIS3 + 01st Semester7,5

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective
Course Content Numerical methods and analysis required for engineering, suitable pocket programs for numerical analysis, problem solutions by means of pocket programs, special applications
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1-
1-
1-

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11
LO 001           
Sub Total           
Contribution00000000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14570
Assignments11515
Mid-terms12323
Final examination13030
Presentation / Seminar Preparation11515
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2020-2021 Fall1AHMET ÖZEK


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
ELK 0565 COMPUTER AIDED NUMERICAL ANALYSIS 3 + 0 1 Turkish 2020-2021 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Asts. Prof. Dr. AHMET ÖZEK ozek@pau.edu.tr MUH A0485 %70
Goals
Content Numerical methods and analysis required for engineering, suitable pocket programs for numerical analysis, problem solutions by means of pocket programs, special applications
Topics
WeeksTopics
1 Introduction to MATLAB
2 Systems of Linear Algebraic Equations
3 Interpolation and Curve Fitting
4 Roots of Equations
5 Numerical Differentiation
6 Numerical Differentiation
7 Numerical Integration
8 Numerical Integration
9 Initial Value Problems
10 Two-Point Boundary Value Problems
11 Symmetric Matrix Eigenvalue Problems
12 Introduction to Optimization
13 Sample Applications
14 Sample Applications
Materials
Materials are not specified.
Resources
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes