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  Course Description
Course Name : Numerical Methods

Course Code : EEE228

Course Type : Compulsory

Level of Course : First Cycle

Year of Study : 2

Course Semester : Spring (16 Weeks)

ECTS : 6

Name of Lecturer(s) : Assoc.Prof.Dr. MUSTAFA GÖK

Learning Outcomes of the Course : Selects the proper numerical method for an analytical problem.
Performs statistical analyzes using regression and interpolation methods.
Writes small programs to apply numerical methods.
Aynı problemin farklı numerik çözümlerinin bilgi işlem açısından performans analizini yapar.

Mode of Delivery : Face-to-Face

Prerequisites and Co-Prerequisites : None

Recommended Optional Programme Components : None

Aim(s) of Course : Introduce numerical methods and modern programming tools to solve complex analytical problems using computer systems.Develop problem solving skills using computer programming. Introduce algorithm developing methods.

Course Contents : Engineering applications of numerical methods, approximation and precision,discussion of numeric errors, Surveys and applications of numerical techniques related to matrix inversion, systems of linear equations and optimization, finite difference expressions, interpolation and approximation, numerical differentiation and integration. The problem of speed, accuracy and applicability of the topics are examined with related algorithms.

Language of Instruction : English

Work Place : Computer Lab. and Classrooms of the Department of Electrical and Electronics Engineering, Computer Lab.


  Course Outline /Schedule (Weekly) Planned Learning Activities
Week Subject Student's Preliminary Work Learning Activities and Teaching Methods
1 Analytical solution numerical solution comparision Review of the simple differential equation problems Classic lecture, Software Installation
2 Error Definitions, Precision and Accuracy Read lecture notes Classic lecture, programming
3 Roots of Equations Bracketing Methods Read lecture notes Classic lecture, programming
4 Roots of Equations Open Methods Read lecture notes Classic lecture, programming
5 Optimization Read lecture notes Classic lecture, programming
6 Linear Algebraic Equations and Matrices Read lecture notes Classic lecture, programming
7 Midterm Review lecture notes Written Exam
8 Gaus Elimination Read lecture notes Classic lecture, programming
9 LU Factoring Read lecture notes Classic lecture, programming
10 Matrix Inverse and Condition Read lecture notes Classic lecture, programming
11 Gaus Seidel Method Read lecture notes Classic lecture, programming
12 Eigenvectors Read lecture notes Classic lecture, programming
13 Lineer Regression Read lecture notes Classic lecture, programming
14 Polynomial Interpolation Read lecture notes Classic lecture, programming
15 Fourier Series Read lecture notes Classic lecture, programming
16/17 Final Exam Review lecture notes. Written Exam


  Required Course Resources
Resource Type Resource Name
Recommended Course Material(s)  Numerical Methods for Engineers, S. Chapra and R. Canale
Required Course Material(s)


  Assessment Methods and Assessment Criteria
Semester/Year Assessments Number Contribution Percentage
    Mid-term Exams (Written, Oral, etc.) 1 70
    Homeworks/Projects/Others 1 30
Total 100
Rate of Semester/Year Assessments to Success 40
 
Final Assessments 100
Rate of Final Assessments to Success 60
Total 100

  Contribution of the Course to Key Learning Outcomes
# Key Learning Outcome Contribution*
1 Has capability in those fields of mathematics and physics that form the foundations of engineering. 5
2 Grasps the main knowledge in the basic topics of electrical and electronic engineering. 4
3 Comprehends the functional integrity of the knowledge gathered in the fields of basic engineering and electrical-electronics engineering. 4
4 Identifies problems and analyzes the identified problems based on the gathered professional knowledge. 5
5 Formulates and solves a given theoretical problem using the knowledge of basic engineering. 3
6 Has aptitude for computer and information technologies 4
7 Knows English at a level adequate to comprehend the main points of a scientific text, either general or about his profession, written in English. 4
8 Has the ability to apply the knowledge of electrical-electronic engineering to profession-specific tools and devices. 3
9 Has the ability to write a computer code towards a specific purpose using a familiar programming language. 5
10 Has the ability to work either through a purpose oriented program or in union within a group where responsibilities are shared. 3
11 Has the aptitude to identify proper sources of information, reaches them and uses them efficiently. 3
12 Becomes able to communicate with other people with a proper style and uses an appropriate language. 3
13 Internalizes the ethical values prescribed by his profession in particular and by the professional life in general. 3
14 Has consciousness about the scientific, social, historical, economical and political facts of the society, world and age lived in. 4
* Contribution levels are between 0 (not) and 5 (maximum).

  Student Workload - ECTS
Works Number Time (Hour) Total Workload (Hour)
Course Related Works
    Class Time (Exam weeks are excluded) 14 6 84
    Out of Class Study (Preliminary Work, Practice) 14 3 42
Assesment Related Works
    Homeworks, Projects, Others 1 5 5
    Mid-term Exams (Written, Oral, etc.) 1 5 5
    Final Exam 1 10 10
Total Workload: 146
Total Workload / 25 (h): 5.84
ECTS Credit: 6