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):

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
1) Adequate knowledge in the fields of mathematics and science; ability to use theoretical and practical knowledge in these fields
2) Adequate knowledge in subjects specific to the relevant engineering discipline; ability to use theoretical and applied knowledge in these areas to solve complex engineering problems.
3) Ability to identify, formulate and solve complex engineering problems.
4) Ability to select and apply appropriate analysis and modeling methods to complex engineering problems.
5) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements.
6) Ability to apply modern design methods to design a complex system, process, device or product.
7) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice.
8) Ability to use information technologies effectively to analyze and solve complex problems encountered in engineering applications.
9) Ability to design and conduct experiments to investigate complex engineering problems or discipline-specific research topics.
10) Ability to collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics.
11) Ability to work effectively in disciplinary teams.
12) Ability to work effectively in multidisciplinary teams.
13) Ability to work individually.
14) Ability to communicate effectively both orally and in writing.
15) Knowledge of at least one foreign language.
16) Effective report writing and comprehension of written reports, ability to prepare design and production reports.
17) Ability to make effective presentations, give and receive clear and understandable instructions.
18) Awareness of the necessity of lifelong learning.
19) Ability to access information, to follow developments in science and technology and to continuously renew oneself.
20) Knowledge about acting in accordance with ethical principles, professional and ethical responsibility and standards used in engineering practices.
21) Knowledge of business practices such as project management, risk management and change management.
22) Awareness about entrepreneurship and innovation.
23) Knowledge about sustainable development.
24) Knowledge about the effects of engineering applications on health, environment and safety in universal and social dimensions and the problems of the era reflected in the field of engineering.
25) Awareness of the legal implications of engineering solutions.

Ders - Öğrenme Kazanımı İlişkisi

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

	Program Outcomes	Level of Contribution
1)	Adequate knowledge in the fields of mathematics and science; ability to use theoretical and practical knowledge in these fields
2)	Adequate knowledge in subjects specific to the relevant engineering discipline; ability to use theoretical and applied knowledge in these areas to solve complex engineering problems.
3)	Ability to identify, formulate and solve complex engineering problems.
4)	Ability to select and apply appropriate analysis and modeling methods to complex engineering problems.
5)	The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements.	5
6)	Ability to apply modern design methods to design a complex system, process, device or product.	5
7)	Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice.	4
8)	Ability to use information technologies effectively to analyze and solve complex problems encountered in engineering applications.	5
9)	Ability to design and conduct experiments to investigate complex engineering problems or discipline-specific research topics.	4
10)	Ability to collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics.	4
11)	Ability to work effectively in disciplinary teams.	3
12)	Ability to work effectively in multidisciplinary teams.
13)	Ability to work individually.
14)	Ability to communicate effectively both orally and in writing.
15)	Knowledge of at least one foreign language.
16)	Effective report writing and comprehension of written reports, ability to prepare design and production reports.
17)	Ability to make effective presentations, give and receive clear and understandable instructions.
18)	Awareness of the necessity of lifelong learning.
19)	Ability to access information, to follow developments in science and technology and to continuously renew oneself.
20)	Knowledge about acting in accordance with ethical principles, professional and ethical responsibility and standards used in engineering practices.
21)	Knowledge of business practices such as project management, risk management and change management.
22)	Awareness about entrepreneurship and innovation.
23)	Knowledge about sustainable development.
24)	Knowledge about the effects of engineering applications on health, environment and safety in universal and social dimensions and the problems of the era reflected in the field of engineering.
25)	Awareness of the legal implications of engineering solutions.

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Project	1	% 20
Midterms	1	% 30
Final	1	% 50
total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
total		% 100