Numerical Analysis

Course Information
TitleΑριθμητική Ανάλυση / Numerical Analysis
SchoolElectrical and Computer Engineering
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorKonstantinos Papalamprou
Course ID600000970

Programme of Study: Electrical and Computer Engineering

Registered students: 308
OrientationAttendance TypeSemesterYearECTS
COREElective Courses426

Class Information
Academic Year2019 – 2020
Class PeriodSpring
Faculty Instructors
Class ID
Course Type 2016-2020
  • Background
Course Type 2011-2015
General Foundation
Mode of Delivery
  • Face to face
Language of Instruction
  • Greek (Instruction, Examination)
General Prerequisites
1. Basic knowledge linear algebra 2. Basic knowledge of differential and integral calculus 3. Basic knowledge of elements of algorithms and programming 4. Elementary knowledge of differential equations
Learning Outcomes
1. Have a complete understanding of the advantages, disadvantages and limitations of numerical methods. 2. Have a complete understanding of common numerical methods and how they are used to obtain approximate solutions to otherwise intractable mathematical problems. 3. Apply numerical methods to obtain approximate solutions to mathematical problems. 4. Apply numerical methods for various mathematical operations and tasks, such as interpolation, integration, solution of nonlinear equations, solution of systems of linear equations. 5. Analyse and evaluate the accuracy of common numerical methods. 6. Be aware of the computational tools and the numerical libraries that can be used in order to solve numerical analysis problems.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work in an international context
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Errors. Solving nonlinear equations in one variable. Matrices, eigenvalues and eigenvectors. Solving systems of linear equations. Interpolation. Least squares. Householder transformations. QR factorization. Numerical integration. Linear programming methods (and related optimization topics). Solving initial-value problems for ordinary differential equations.
Errors, Root finding, Interpolation, Numerical integration, Numerical Linear Algebra, Numerical Solution of Ordinary Differential Equations, Least Squares, Householder Factorization
Educational Material Types
  • Notes
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Course Organization
Student Assessment
1. Written Examination
Student Assessment methods
  • Written Exam with Problem Solving (Formative, Summative)
Course Bibliography (Eudoxus)
1. Εισαγωγή στην Αριθμητική Ανάλυση, Λ. Πιτσούλης 2. Εισαγωγή στην Αριθμητική Ανάλυση, Γ.Δ. Ακρίβης και Β.Α. Δούγαλης
Additional bibliography for study
Numerical Analysis, R.L. Burden and J.D. Faires
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