Mathematics

Linear Algebra II(MAT262)

Course Code Course Name Semester Theory Practice Lab Credit ECTS
MAT262 Linear Algebra II 4 4 0 0 4 7
Prerequisites
Admission Requirements
Language of Instruction French
Course Type Compulsory
Course Level Bachelor Degree
Course Instructor(s) Oğuzhan KAYA oguzabel@gmail.com (Email)
Assistant
Objective Get to grips with basis Linear Algebra.
Content Matrices. Reduction of Endomorphisms (diagonalisation, trigonalisation, polynomial of endomorphisms).
Course Learning Outcomes Eigenvalues, eigenvectors. Diagonalisation. Gram-Schmidt orthonormalisation. Jordan normal forms.
Teaching and Learning Methods Lecture and exercises.
References Algèbre linéaire et bilinéaire, F. Cottet Emard, de Boeck, 2007 ..
Print the course contents
Theory Topics
Week Weekly Contents
1 Reminders of Linear Algebra I
2 Reminders of Linear Algebra I
3 Reduction
4 Diagonalisation
5 Diagonalisation
6 Diagonalisation
7 Mid-term examination
8 Test correction
9 Polynomial of endomorphisms
10 Polynomial of endomorphisms
11 Trigonalisation
12 Trigonalisation
13 Trigonalisation
14 Jordan decomposition
Practice Topics
Week Weekly Contents
Contribution to Overall Grade
  Number Contribution
Contribution of in-term studies to overall grade 3 50
Contribution of final exam to overall grade 1 50
Toplam 4 100
In-Term Studies
  Number Contribution
Assignments 1 34
Presentation 0 0
Midterm Examinations (including preparation) 2 66
Project 0 0
Laboratory 0 0
Other Applications 0 0
Quiz 0 0
Term Paper/ Project 0 0
Portfolio Study 0 0
Reports 0 0
Learning Diary 0 0
Thesis/ Project 0 0
Seminar 0 0
Other 0 0
Toplam 3 100
No Program Learning Outcomes Contribution
1 2 3 4 5
1 understands principles of deductive reasoning; has experience to verify well-foundedness and exactness of mathematical statements in systematic ways; X
2 can properly state and use concepts and results of major mathematical interest; X
3 masters current computational techniques and algorithms; has a good ability in their use; can identify relevant tools, among those one has learned, suitable to solve a problem and is able to judge whether or not one is in possession of these tools; X
4 is able to express one’s mathematical ideas in an organised way both in written and oral forms; X
5 understands relations connecting substantial concepts and results; can switch from one viewpoint to another on mathematical objects (pictures, formulae, precise statements, heuristic trials, list of examples,...); X
6 has followed individually a guided learning strategy; has pursued steps toward the resolution of unfamiliar problems; X
7 has a theoretical and practical knowledge in computer science well adapted for learning a programming language; X
8 has investigated the relevance of modeling and using mathematical tools in natural sciences and in the professional life; is conscious about historical development of mathematical notions; X
9 has followed introduction to some mathematical or non-mathematical disciplines after one’s proper choice; had experience to learn selected subjects according to one’s proper arrangement; X
10 masters French language as well as other foreign languages, to a level sufficient to study or work abroad. X
Activities Number Period Total Workload
Class Hours 14 4 56
Working Hours out of Class 14 3 42
Assignments 2 4 8
Presentation 2 1 2
Midterm Examinations (including preparation) 2 6 12
Project 1 20 20
Laboratory 0 0 0
Other Applications 0 0 0
Final Examinations (including preparation) 1 6 6
Quiz 0 0 0
Term Paper/ Project 0 0 0
Portfolio Study 0 0 0
Reports 0 0 0
Learning Diary 0 0 0
Thesis/ Project 0 0 0
Seminar 0 0 0
Other 0 0 0
Total Workload 146
Total Workload / 25 5,84
Credits ECTS 6
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