Syllabus ( MATH 114 )
|
Basic information
|
|
Course title: |
Linear Algebra II |
Course code: |
MATH 114 |
Lecturer: |
Prof. Dr. Mustafa AKKURT
|
ECTS credits: |
6 |
GTU credits: |
4 (3+2+0) |
Year, Semester: |
1, Spring |
Level of course: |
First Cycle (Undergraduate) |
Type of course: |
Compulsory
|
Language of instruction: |
English
|
Mode of delivery: |
Face to face
|
Pre- and co-requisites: |
None. |
Professional practice: |
No |
Purpose of the course: |
To teach the fundamental concepts of Linear Algebra. |
|
|
|
Learning outcomes
|
|
Upon successful completion of this course, students will be able to:
-
Improve simple proof techniques.
Contribution to Program Outcomes
-
Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
-
Having improved abilities in mathematics communications, problem-solving, and brainstorming skills.
Method of assessment
-
Written exam
-
Choose solution techniques to calculate linear equations
Contribution to Program Outcomes
-
Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
-
Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
Method of assessment
-
Written exam
-
Interpret mathematical content of linear independency
Contribution to Program Outcomes
-
Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
-
Exhibiting professional and ethical responsibility.
Method of assessment
-
Written exam
|
|
Contents
|
|
Week 1: |
Length and direction in R^2 and R^3 and dot product Coordinates and Isomorphisms |
Week 2: |
Inner product spaces |
Week 3: |
Gram-Schmidt process |
Week 4: |
Orthogonal complements |
Week 5: |
Linear transformations (definition and examples) |
Week 6: |
Kernel and range of a linear transformation |
Week 7: |
Matrix of a linear transformation, transition matrices |
Week 8: |
Midterm exam and solutions |
Week 9: |
Similarity |
Week 10: |
Eigenvalues and eigenvectors |
Week 11: |
Diagonalization and similar matrices
|
Week 12: |
Diagonalization of symmetric matrices |
Week 13: |
Real quadratic forms |
Week 14: |
Jordan form of a matrix |
Week 15*: |
- |
Week 16*: |
Final exam |
Textbooks and materials: |
|
Recommended readings: |
Elementary Lineer Algebra, 7th Ed. Bernard Kolman ve David R. Hill |
|
* Between 15th and 16th weeks is there a free week for students to prepare for final exam.
|
|
|
|
Assessment
|
|
|
Method of assessment |
Week number |
Weight (%) |
|
Mid-terms: |
8 |
40 |
Other in-term studies: |
|
0 |
Project: |
|
0 |
Homework: |
|
0 |
Quiz: |
|
0 |
Final exam: |
16 |
60 |
|
Total weight: |
(%) |
|
|
|
Workload
|
|
|
Activity |
Duration (Hours per week) |
Total number of weeks |
Total hours in term |
|
Courses (Face-to-face teaching): |
3 |
14 |
|
Own studies outside class: |
3 |
14 |
|
Practice, Recitation: |
2 |
14 |
|
Homework: |
0 |
0 |
|
Term project: |
0 |
0 |
|
Term project presentation: |
0 |
0 |
|
Quiz: |
0 |
0 |
|
Own study for mid-term exam: |
15 |
1 |
|
Mid-term: |
2 |
1 |
|
Personal studies for final exam: |
15 |
1 |
|
Final exam: |
2 |
1 |
|
|
|
Total workload: |
|
|
|
Total ECTS credits: |
* |
|
* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)
|
|
|
-->