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

Ders Genel Tanıtım Bilgileri

Course Code:

EFC201

Ders İsmi:

Data Structures and Algorithms

Ders Yarıyılı:

Fall

Ders Kredileri:

Theoretical	Practical	Laboratory	ECTS
3	2	0	5

Language of instruction:

Turkish

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Required

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 Data Structures course is to teach students how data is organized and how this organization affects the efficiency of algorithms. By learning fundamental data structures (such as lists, stacks, queues, trees, and graphs) and sorting algorithms, students will be able to effectively use these structures in problem-solving and software development processes. Additionally, the course focuses on developing the ability to evaluate the efficiency of algorithms and choose the appropriate data structure accordingly.

Course Content:

In the Data Structures course, key topics include notations used in algorithm analysis, lists, stacks, queues, and recursive structures. The course also covers hash tables, binary search trees, balanced search trees (such as AVL and Red-Black trees), B-trees, and B-234 trees. Sorting algorithms like QuickSort, MergeSort, and Radix Sort, as well as graph structures and graph traversal algorithms (DFS, BFS), are also explored. These structures and algorithms aim to enhance data organization and problem-solving skills.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Ability to calculate time and memory usage complexity of algorithms
2 - Skills
Cognitive - Practical
1) Ability to use basic data structures to solve algorithmic problems effectively
2) Ability to write programs that use basic data structures
3) Ability to apply to programs using effective search and sorting algorithms
4) Ability to use mathematical symbols used in algorithm analysis in basic algorithm analysis
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
1) Ability to write programs using data structures and algorithms to perform desired program functions
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)
2)
3)
4)
5)
6)
7)
8)
9)
10)
11)
13)
14)
15)
16)

Sources

Course Notes / Textbooks:
References:	Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	4	5	3	6
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.	4
3)	Ability to identify, formulate and solve complex engineering problems.	5
4)	Ability to select and apply appropriate analysis and modeling methods to complex engineering problems.	4
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.	5
8)	Ability to use information technologies effectively to analyze and solve complex problems encountered in engineering applications.	4
9)	Ability to design and conduct experiments to investigate complex engineering problems or discipline-specific research topics.	3
10)	Ability to collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics.	3
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.

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