COURSE UNIT TITLE

: APPLIED MATRIX ALGORITHMS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSC 5025 APPLIED MATRIX ALGORITHMS ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR MURAT ERŞEN BERBERLER

Offered to

Ph.D. in Computer Science (English)
Computer Science

Course Objective

In this course, the solution procedures will be held for the problems encountered in computer science that use matrices as data structures mostly, and the algorithms that uses these procedures, their design and analysis will be given with applications. The aim of this course is to teach the algorithmic approach for the problem literature that uses matrix representation, and to make the student to gain the knowledge and skill levels for solving the encountered new problems by using the literature.

Learning Outcomes of the Course Unit

1   Have a knowledge of basic concepts of matrix algorithms.
2   Be able to solve problems of matrix theory with algorithms.
3   Be able to solve computer science problems by using matrix algorithms concepts.
4   Be able to design efficient algorithms by using matrix theory concepts.
5   Be able to solve problems of different type of disciplines by using concepts of matrix algorithms.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Vectors, matrices and matrix operations
2 Fundamental matrix operations and their algebraic specifications
3 Matrix multiplication and fast multiplication algorithms
4 Calculating determinant
5 Finding inverse of a matrix
6 LU decomposition method
7 Matrix algorithms in graph theory
8 Midterm exam
9 Matrix algorithms in game theory
10 Geometric transformation matrices
11 Computer graphics
12 Dynamic programing
13 Markov process
14 Computer applications
15 Final exam

Recomended or Required Reading

Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Cliford Stein, Introduction to Algorithms, MIT Press, 2001.

Anany Levitin, Introduction to The Design and Analysis of Algorithms, Pearson International Edition, 2007.

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format. Besides the taught lecture, group presentations are to be prepared by the groups assigned and presented in a discussion session. In some weeks of the course, results of the homework given previously are discussed.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT/PRESENTATION
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE ASG * 0.40 +FIN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.40 +RST * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

To be announced.

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

murat.berberler@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Project Preparation 1 12 12
Preparation for final exam 1 24 24
Preparations before/after weekly lectures 13 10 130
Project Assignment 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 209

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15555
LO.25555
LO.35555
LO.45555
LO.55555

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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