DEPARTMENT OF SOFTWARE ENGINEERING (ENGLISH)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

1400221026

Ders İsmi:

Design and Analysis of Algorithms

Ders Yarıyılı:

Spring

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	6

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Necessary

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 :

Dr.Öğr.Üyesi Recep DURANAY

Course Lecturer(s):

Dr.Öğr.Üyesi İmren YEŞİLYURT

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	The aim of this course is to provide students with the knowledge and skills to design programming languages using modern design methods and to implement the designed languages using modern development tools.
Course Content:	Algorithm design concepts and knowledge of algorithm complexity analysis, solving and proving recursive equations, formal and heuristic introduction to level and growth rate, brute force approach, divide and conquer approach, dynamic programming, greedy approach, graph algorithms and NP theory.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Adequate knowledge of algorithm design techniques and algorithmic solutions of basic problems
2 - Skills
Cognitive - Practical
1) Ability to use design techniques to model and solve problems; Ability to adapt basic algorithms to complex problems.
3 - Competences
Communication and Social Competence
Learning Competence
1) Adequate knowledge in algorithm analysis; ability to analyze sequential and recursive algorithms using theoretical and experimental methods; Adequate knowledge of NP theory
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	THEORETICAL INFRASTRUCTURE	Neapolitan, and K. Naimipour, Foundations of Algorithms
2)	EFFICIENCY, ANALYSIS AND GROWTH RATE	Neapolitan, and K. Naimipour, Foundations of Algorithms
3)	RECURSION	Neapolitan, and K. Naimipour, Foundations of Algorithms
4)	RECURSION II	Neapolitan, and K. Naimipour, Foundations of Algorithms
5)	ROUGH FORCE ALGORITHMS	Neapolitan, and K. Naimipour, Foundations of Algorithms
6)	DIVIDE AND CONQUER I	Neapolitan, and K. Naimipour, Foundations of Algorithms
7)	DIVIDE AND CONQUER II	Neapolitan, and K. Naimipour, Foundations of Algorithms
8)	MIDTERM	Neapolitan, and K. Naimipour, Foundations of Algorithms
9)	DYNAMIC PROGRAMMING I	Neapolitan, and K. Naimipour, Foundations of Algorithms
10)	DYNAMIC PROGRAMMING II	Neapolitan, and K. Naimipour, Foundations of Algorithms
11)	GREEDY APPROACH	Neapolitan, and K. Naimipour, Foundations of Algorithms
12)	GRAPH ALGORITHMS	Neapolitan, and K. Naimipour, Foundations of Algorithms
13)	GRAPH ALGORITHMS II	Neapolitan, and K. Naimipour, Foundations of Algorithms
14)	REVIEW	Neapolitan, and K. Naimipour, Foundations of Algorithms
15)	REVIEW	Neapolitan, and K. Naimipour, Foundations of Algorithms
16)	FINAL	Neapolitan, and K. Naimipour, Foundations of Algorithms

Sources

Course Notes / Textbooks:	Neapolitan, and K. Naimipour, Foundations of Algorithms
References:	Neapolitan, and K. Naimipour, Foundations of Algorithms

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3
Program Outcomes
1) Competent knowledge of mathematics, science and technology, and computer engineering; ability to apply this knowledge to engineering solutions.
2) Skills to design and conduct experiments, collect data, analyze and interpret results.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose.
4) Ability to develop, select and use modern techniques and tools required for analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
5) Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics.
6) Ability to work effectively in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in Turkish, both orally and in writing; Knowledge of at least one foreign language; the ability to write and understand written reports effectively, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8) Awareness of the necessity of lifelong learning; the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
9) Acting in accordance with ethical principles, professional and ethical responsibility awareness; information about standards used in engineering applications.
10) Information about business life practices such as project management, risk management and change management; awareness of entrepreneurship, innovation; information about sustainable development.
11) Knowledge about the universal and social effects of engineering applications on health, environment and safety and the problems of the age reflected in the field of engineering; awareness of the legal consequences 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)	Competent knowledge of mathematics, science and technology, and computer engineering; ability to apply this knowledge to engineering solutions.
2)	Skills to design and conduct experiments, collect data, analyze and interpret results.
3)	Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose.
4)	Ability to develop, select and use modern techniques and tools required for analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
5)	Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics.
6)	Ability to work effectively in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7)	Ability to communicate effectively in Turkish, both orally and in writing; Knowledge of at least one foreign language; the ability to write and understand written reports effectively, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8)	Awareness of the necessity of lifelong learning; the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
9)	Acting in accordance with ethical principles, professional and ethical responsibility awareness; information about standards used in engineering applications.
10)	Information about business life practices such as project management, risk management and change management; awareness of entrepreneurship, innovation; information about sustainable development.
11)	Knowledge about the universal and social effects of engineering applications on health, environment and safety and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions.

Öğrenme Etkinliği ve Öğretme Yöntemleri

Course
Homework

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Homework

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	1	% 10
Midterms	1	% 30
Semester Final Exam	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	5	70
Homework Assignments	10	2	20
Midterms	1	2	2
Final	1	3	3
Total Workload			137