COMPUTER ENGINEERING
Qualification Awarded Program Süresi Toplam Kredi (AKTS) Öğretim Şekli Yeterliliğin Düzeyi ve Öğrenme Alanı
Bachelor's (First Cycle) Degree 4 240 FULL TIME TYÇ, TR-NQF-HE, EQF-LLL, ISCED (2011):Level 6
QF-EHEA:First Cycle
TR-NQF-HE, ISCED (1997-2013): 48,52

Ders Genel Tanıtım Bilgileri

Course Code: 1410211001
Ders İsmi: Data Structures
Ders Yarıyılı: Fall
Ders Kredileri:
Theoretical Practical Labs Credit ECTS
3 0 0 3 8
Language of instruction: TR
Ders Koşulu:
Ders İş Deneyimini Gerektiriyor mu?: No
Other Recommended Topics for the Course:
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 : Assoc. Prof. Ali ÇİVRİL
Course Lecturer(s):


Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives: Students who successfully complete this course
1. Understand the necessity and importance of using different data structures to solve problems encountered in Computer Science/Engineering.
2. Know basic data structures and algorithms and their implementation
3. Will be able to solve various problems with knowledge of data structures and algorithms
4. Will be able to write the solutions to these problems in C++.
Course Content: Bu ders C++’ta bilgisayar bilimi ve mühendisliğinde kullanılan temel veri yapılarıyla problem çözme tekniklerini ve temel algoritmik yöntemleri konu edinmektedir. Ders girişte algoritma analizi ve verimliliğinden, sıralama algoritmalarından bahseder. Konu edinilen veri yapıları arasında bağlı listeler, yığıtlar, kuyruklar, ağaçlar, yığınlar, çırpı tabloları ve çizgeler vardır. Çizgeler üzerindeki temel algoritmalardan, böl-ve-fethet yönteminden ve dinamik programlamadan da bahsedilecektir.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
1) Students will be able to analyze the time and space complexity of algorithms and express this complexity using Big-O notation.
Field Specific Competence
1) Ability to use and compare data structures in different application areas.
2) Ability to use the necessary tools for application design and development.
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week Subject Related Preparation
1) Algorithm Analysis, O Notation Çölkesen Bölüm 5, Weiss Chapter 2
1)
2) Sorting Algorithms Çölkesen Bölüm 6, Weiss Chapter 7
3) Sorting Algorithms, Search Algorithms Çölkesen Bölüm 6, Bölüm 7, Weiss Chapter 7
4) Linked Lists Çölkesen Bölüm 8, Weiss Chapter 3
5) Linked Lists Çölkesen Bölüm 8, Weiss Chapter 3
6) Stacks Çölkesen Bölüm 9, Weiss Chapter 3
7) Queues Çölkesen Bölüm 9, Weiss Chapter 3
8) Midterm Exam
9) Trees Çölkesen Bölüm 10, Weiss Chapter 4
10) Trees Çölkesen Bölüm 10, Weiss Chapter 4
11) Heaps and Heapsort Çölkesen Bölüm 6.6, Weiss Chapter 6
12) Hash Tables Çölkesen Bölüm 7.4, Weiss Chapter 5
13) Graph Algorithms Çölkesen Bölüm 12, 13, Weiss Chapter 9
14) Graph Algorithms Çölkesen Bölüm 12, 13, Weiss Chapter 9
15) Final

Sources

Course Notes / Textbooks: Tavsiye) Veri Yapıları ve Algoritmalar, Toros Rifat Çölkesen, Papatya Yayıncılık. (Tavsiye) Data Structures and Algorithm Analysis in C++, 4th Edition, Mark Allen Weiss, Pearson. (Tavsiye) C++ How to Program, 10th Edition (Global Edition), Paul Deitel-Harvey Deitel, Pearson.
References: Tavsiye) Veri Yapıları ve Algoritmalar, Toros Rifat Çölkesen, Papatya Yayıncılık. (Tavsiye) Data Structures and Algorithm Analysis in C++, 4th Edition, Mark Allen Weiss, Pearson. (Tavsiye) C++ How to Program, 10th Edition (Global Edition), Paul Deitel-Harvey Deitel, Pearson.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları

1

2

1

Program Outcomes
1) 1.1 Sufficient knowledge of subjects such as mathematics and science
2) 1.2 Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems.
3) 1.3 Ability to use theoretical and applied knowledge in fields such as mathematics and science in complex engineering problems.
4) 2.1 Ability to identify, define, formulate and solve complex engineering problems
5) 2.2 Ability to select and apply appropriate analysis and modeling methods for this purpose
6) 3.1 Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions
7) 3.2 Ability to apply modern design methods for this purpose
8) 4.1 Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications.
9) 4.2 Ability to use information technologies effectively
10) 5.1 Ability to design experiments to examine complex engineering problems or discipline-specific research issues
11) 5.2 Ability to conduct experiments to examine complex engineering problems or discipline-specific research topics
12) 5.3 Ability to collect data to examine complex engineering problems or discipline-specific research topics
13) 5.4 Ability to analyze and interpret experimental results for the study of complex engineering problems or discipline-specific research issues
14) 6.1 Ability to work individually within the discipline
15) 6.2 Ability to work effectively in interdisciplinary teams
16) 6.3 Ability to work effectively in multidisciplinary teams
17) 7.1 Ability to communicate effectively and make presentations both verbally and in Turkish
18) 7.2 Knowledge of at least one foreign language
19) 7.3 Ability to write effective reports and understand written reports
20) 7.4 Ability to prepare design and production reports
21) 7.5 Ability to give and receive clear and understandable instructions
22) 8.1 Awareness of the necessity of lifelong learning
23) 8.2 The ability to access information, follow developments in science and technology and constantly renew oneself
24) 9.1 Acting in accordance with ethical principles, awareness of professional and ethical responsibility
25) 9.2 Information about standards used in engineering applications
26) 10.1 Knowledge of business practices such as project management, risk management and change management
27) 10.2 Awareness about entrepreneurship, innovation
28) 10.3 Information about sustainable development
29) 11.1 Information about the effects of engineering practices on health, environment and security at universal and social dimensions and the problems of the age reflected in the field of engineering
30) 11.2 Awareness of the legal consequences of engineering solutions
31) 12.1 Having knowledge about discrete mathematics

Ders - Öğrenme Kazanımı İlişkisi

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) 1.1 Sufficient knowledge of subjects such as mathematics and science
2) 1.2 Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems.
3) 1.3 Ability to use theoretical and applied knowledge in fields such as mathematics and science in complex engineering problems.
4) 2.1 Ability to identify, define, formulate and solve complex engineering problems
5) 2.2 Ability to select and apply appropriate analysis and modeling methods for this purpose
6) 3.1 Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions
7) 3.2 Ability to apply modern design methods for this purpose
8) 4.1 Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications.
9) 4.2 Ability to use information technologies effectively
10) 5.1 Ability to design experiments to examine complex engineering problems or discipline-specific research issues
11) 5.2 Ability to conduct experiments to examine complex engineering problems or discipline-specific research topics
12) 5.3 Ability to collect data to examine complex engineering problems or discipline-specific research topics
13) 5.4 Ability to analyze and interpret experimental results for the study of complex engineering problems or discipline-specific research issues
14) 6.1 Ability to work individually within the discipline
15) 6.2 Ability to work effectively in interdisciplinary teams
16) 6.3 Ability to work effectively in multidisciplinary teams
17) 7.1 Ability to communicate effectively and make presentations both verbally and in Turkish
18) 7.2 Knowledge of at least one foreign language
19) 7.3 Ability to write effective reports and understand written reports
20) 7.4 Ability to prepare design and production reports
21) 7.5 Ability to give and receive clear and understandable instructions
22) 8.1 Awareness of the necessity of lifelong learning
23) 8.2 The ability to access information, follow developments in science and technology and constantly renew oneself
24) 9.1 Acting in accordance with ethical principles, awareness of professional and ethical responsibility
25) 9.2 Information about standards used in engineering applications
26) 10.1 Knowledge of business practices such as project management, risk management and change management
27) 10.2 Awareness about entrepreneurship, innovation
28) 10.3 Information about sustainable development
29) 11.1 Information about the effects of engineering practices on health, environment and security at universal and social dimensions and the problems of the age reflected in the field of engineering
30) 11.2 Awareness of the legal consequences of engineering solutions
31) 12.1 Having knowledge about discrete mathematics

Öğrenme Etkinliği ve Öğretme Yöntemleri

Course
Homework
Problem Çözme

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 3 % 30
Midterms 1 % 30
Semester Final Exam 1 % 40
total % 100
PERCENTAGE OF SEMESTER WORK % 60
PERCENTAGE OF FINAL WORK % 40
total % 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Laboratory 14 2 28
Study Hours Out of Class 14 4 56
Homework Assignments 10 2 20
Midterms 1 2 2
Final 1 3 3
Total Workload 151