Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
4MATH214Numerical Analysis3+0+03529.07.2024
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program Civil Engineering
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course Enhancing problem solving skills: Numerical methods are extremely powerful problem-solving tools. Construction and use of numerical systems for solving a problem.
Course Content Methods for finding Roots of Equations: The Intermediate Value Theorem, The Mean Value Theorem, The Rolle’s Theorem, Taylor Series, Approximations and Errors, Bisection, NewtonRaphson Method, Lagrange polynomial interpolation, System of Non-linear Equations, System of Linear Algebraic Equations: Gauss Elimination, Matrix Inversion, Gauss-Seidel Iteration, Least Squares Regression, Polynomial Interpolation, Numerical Differentiation, Numerical Integration,Newton-Cotes Formulae, Romberg’s and Gauss-Quadrature Integration, Solution of Ordinary Differential Equations, Euler, Runge-Kutta, Multi-Step Methods, Initial-Value Problems, BoundaryValue Problems
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator Asist Prof.Dr. Amin Gharehbaghi
Name of Lecturers None
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Lecture notes
Course Notes Numerical Analysis , 9th ed., by Burden & Faires, edited by Brooks & Cole
2001.

Course Category
Mathematics and Basic Sciences %60
Engineering %40

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 40
Final examination 1 % 60
Total
2
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 13 3 39
Hours for off-the-c.r.stud 14 7 98
Mid-terms 1 2 2
Final examination 1 2 2
Total Work Load   Number of ECTS Credits 4,5 141

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 A comprehension of mathematics (algebra, differential, integration …) and fundamentals of science
2 Ability to apply knowledge of mathematics, science and engineering to problems in electronics engineering
3 Ability to recognize the needs and challenges of our age and to assess the global and social impact of engineering solutions
4 Ability to identify, formulate and solve engineering problems.
5 Ability to effectively communicate knowledge and opinions via written, oral visual means.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Methods for finding Roots of Equations: The Intermediate Value Theorem, The Mean Value Theorem, The Rolle’s Theorem
2 Taylor Series, Approximations and Errors
3 Bisection Method
4 Newton-Raphson Method
5 Lagrange Polynomial Interpolation
6 System of Non-linear Equations System of Linear Algebraic Equations: Gauss Elimination, Matrix Inversion, Gauss-Seidel Iteration
7 Least Squares Regression
8 Midterm exam
9 Numerical Differentiation
10 Numerical Integration, Newton-Cotes Formula
11 Romberg’s and Gauss-Quadrature Integration
12 Solution of Ordinary Differential Equations
13 Euler, Runge-Kutta, Multi-Step Methods
14 Initial-Value Problems, Boundary-Value Problems

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
All 5
C1 5
C2 5
C3 5
C4 5
C5 5

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant