Information Systems Engineering
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

FET317

Ders İsmi:

Algorithm Analysis

Ders Yarıyılı:

Spring

Ders Kredileri:

Theoretical	Practical	Laboratory	ECTS
2	1	0	5

Language of instruction:

Turkish

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Bölüm Seçmeli

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Asst. Prof. Dr. ARiF YELĞİ

Course Lecturer(s):

Asst. Prof. Dr. ARiF YELĞİ

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	The aim of the course is to discuss and introduce algorithm design and analysis in various application areas.
Course Content:	Knowledge of algorithm design concepts and algorithm complexity analysis, solving and proving recursive equations, formal and intuitive introduction to level and growth rate, brute force approach, divide and conquer approach, dynamic programming, greedy approach and NP theory.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Can learn and use many standard algorithms, especially search and sorting algorithms.
2 - Skills
Cognitive - Practical
1) The student can analyze the accuracy of an algorithm.
2) The student will learn the time and space usage complexity of an algorithm, the calculation of worst-case, average-case and best-case complexities, and asymptotic notations.
3) The student can design effective algorithms for solving general engineering problems.
4) The student can calculate the complexity of algorithms,
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Introduction
2)	Fundamentals of Algorithm Analysis, Algorithm Complexity	Pre-readings on the topics
3)	Asymptotic Analysis	Pre-readings on the topics
4)	Divide and Conquer Algorithms	Pre-readings on the topics
5)	Priority Queue	Pre-readings on the topics
6)	Depth Search, Transverse Search	Pre-readings on the topics
7)	Balanced Search Trees (2-3 trees, B-trees, Red-Black Trees)	Pre-readings on the topics
8)	Midterm	Pre-readings on the topics
9)	Dynamic Programming	Pre-readings on the topics
10)	Linear Programming	Pre-readings on the topics
11)	Recursive Algorithms	Pre-readings on the topics
12)	Branch and Boundary Algorithms	Pre-readings on the topics
13)	Midterm Exam 2 - NP, NP-complete, NP-hard problems	Pre-readings on the topics
14)	Advanced Algorithms	Pre-readings on the topics
15)	Advanced Algorithms	Pre-readings on the topics
16)	Final exam	Pre-readings on the topics

Sources

Course Notes / Textbooks:	Aref yelghi -ders notları
References:	Introduction to the Design and Analysis of Algorithms (3rd Edition) by Anany Levitin, 2011 Introduction to Algorithms, Third Edition, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, The MIT Press, 2009

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3	4	5
Program Outcomes

Ders - Öğrenme Kazanımı İlişkisi

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

Program Outcomes

Level of Contribution

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
total		%
PERCENTAGE OF SEMESTER WORK		% 0
PERCENTAGE OF FINAL WORK		%
total		%