Course Information
SchoolMechanical Engineering
Cycle / Level1st / Undergraduate
Teaching PeriodWinter
CoordinatorVasileios Rothos
Course ID600014332

Programme of Study: UPS of School of Mechanical Engineering

Registered students: 286
OrientationAttendance TypeSemesterYearECTS
CoreCompulsory Course114

Class Information
Academic Year2020 – 2021
Class PeriodWinter
Faculty Instructors
Instructors from Other Categories
Weekly Hours3
Class ID
Course Category
General Foundation
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
This course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines. Linear algebra is a branch of mathematics that studies systems of linear equations and the properties of matrices. The concepts of linear algebra are extremely useful in physics, economics and social sciences, natural sciences, and engineering. Due to its broad range of applications, linear algebra is one of the most widely taught subjects in college-level mathematics (and increasingly in high school). After successfully completing the course, you will have a good understanding of the following topics and their applications: Systems of linear equations Row reduction and echelon forms Matrix operations, including inverses Block matrices Linear dependence and independence Subspaces and bases and dimensions Orthogonal bases and orthogonal projections Gram-Schmidt process Linear models and least-squares problems Determinants and their properties Cramer's Rule Eigenvalues and eigenvectors Diagonalization of a matrix Symmetric matrices Positive definite matrices Similar matrices Linear transformations Singular Value Decomposition
General Competences
  • Apply knowledge in practice
  • Work autonomously
  • Work in teams
Course Content (Syllabus)
Cartesian products, mathematical induction. Matrices, linear transformations on real n-space,solving linear algebraic systems, linear independence and dimension, bases and coordinates, determinants, orthogonal projections, least squares, eigenvalues and eigenvectors and their applications to quadratic forms. Complex eigenvalues and eigenvectors are also covered in the 2 by 2 and 3 by 3 cases.
matrices linear systems bases vector spaces eignevalues eigenvectors quadratic forms applications
Educational Material Types
  • Notes
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
projector PC
Course Organization
Interactive Teaching in Information Center200.7
Written assigments50.2
Student Assessment
Final exam 3hrs and 2 midterm tests
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Formative, Summative)
  • Written Exam with Short Answer Questions (Summative)
  • Written Exam with Extended Answer Questions (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
Course Bibliography (Eudoxus)
Βιβλίο [2898]: ΕΙΣΑΓΩΓΗ ΣΤΗ ΓΡΑΜΜΙΚΗ ΑΛΓΕΒΡΑ, GILBERT STRANG Βιβλίο [204]: ΓΡΑΜΜΙΚΗ ΑΛΓΕΒΡΑ ΚΑΙ ΕΦΑΡΜΟΓΕΣ, STRANG GILBERT Βιβλίο [33314]: Εισαγωγή στη ΓΡΑΜΜΙΚΗ ΑΛΓΕΒΡΑ, Θεδοδώρα Θεοχάρη-Αποστολίδη, Χαρά Χαραλάμπους, Χαρίλαος Βαβατσούλας Βιβλίο [4649]: ΓΡΑΜΜΙΚΗ ΑΛΓΕΒΡΑ ΚΑΙ ΑΝΑΛΥΤΙΚΗ ΓΕΩΜΕΤΡΙΑ, ΦΙΛΙΠΠΟΣ Ι. ΞΕΝΟΣ Λεπτομέρειες
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