Department of Electrical and Electronics Engineering

ACADEMICS
Course Details

ELE411 - Data Structures

2025-2026 Fall term information
The course is open this term
Supervisor(s)
Name Surname Position Section
Dr. İsmail Uyanık Supervisor 21
Weekly Schedule by Sections
Section Day, Hours, Place
21 Monday, 12:40 - 15:30, E7

Timing data are obtained using weekly schedule program tables. To make sure whether the course is cancelled or time-shifted for a specific week one should consult the supervisor and/or follow the announcements.

ELE411 - Data Structures
Program Theoretıcal hours Practical hours Local credit ECTS credit
Undergraduate 3 0 3 6
Obligation : Elective
Prerequisite courses : ELE120
Concurrent courses : -
Delivery modes : Face-to-Face
Learning and teaching strategies : Lecture, Question and Answer, Problem Solving
Course objective : The course aims at teaching students programming tools, programming structures, models, analysis and applications.
Learning outcomes : Know programming tools and analyses programs. Uses Data Structures in Programming Applications. Implements algorithms in engineering area. Designs algorithms and programs using techniques taught in the class.
Course content : 1.Data Structures; Concepts and Review 2. Effective Programming Techniques 3. Stack, Recurson and Queues 4. Searching Algorithms 5. Linked Lists and Applications 6. Sorting Algorithms 7. Tree Structures
References : Ford W., Topp W., Data Structures with C++, Prentice Hall, 1996.; Sedgewick R., Algorithms in C, Addison Wesley, 1990.
Course Outline Weekly
Weeks Topics
1 Data Structures, Intrıduction, Definitions, Concepts
2 Stack, Recursion and Queues, Applicatioins
3 Queues, Calssification, Types and Applications
4 Lists, Linked Lists and Applications
5 Searching Algorithms
6 Hash Algorithms
7 Sorting Algorithms, Simple Algorithms, Algorithm Analysis
8 Bubble Sort, Smple Selection Sort and Insertion Sort
9 Quick Sort, HeapSort, Merge Sort and Shell Sort Algorithms
10 Radix Sort, Bucket Sort and Counting Sort
11 Midterm
12 Tree, Definition and Applications
13 Binary Trees, Analysis and Applications
14 AVL Trees, Analysis and Applications
15 Preparation for Final exam
16 Final Exam
Assessment Methods
Course activities Number Percentage
Attendance 0 0
Laboratory 0 0
Application 0 0
Field activities 0 0
Specific practical training 0 0
Assignments 0 0
Presentation 0 0
Project 0 0
Seminar 0 0
Quiz 0 0
Midterms 1 40
Final exam 1 50
Total 90
Percentage of semester activities contributing grade success 40
Percentage of final exam contributing grade success 50
Total 90
Workload and ECTS Calculation
Course activities Number Duration (hours) Total workload
Course Duration 14 3 42
Laboratory 0 0 0
Application 0 0 0
Specific practical training 0 0 0
Field activities 0 0 0
Study Hours Out of Class (Preliminary work, reinforcement, etc.) 13 3 39
Presentation / Seminar Preparation 0 0 0
Project 0 0 0
Homework assignment 1 5 5
Quiz 0 0 0
Midterms (Study Duration) 1 35 35
Final Exam (Study duration) 1 35 35
Total workload 30 81 156
Matrix Of The Course Learning Outcomes Versus Program Outcomes
Key learning outcomes Contribution level
1 2 3 4 5
1. Possesses the theoretical and practical knowledge required in Electrical and Electronics Engineering discipline.
2. Utilizes his/her theoretical and practical knowledge in the fields of mathematics, science and electrical and electronics engineering towards finding engineering solutions.
3. Determines and defines a problem in electrical and electronics engineering, then models and solves it by applying the appropriate analytical or numerical methods.
4. Designs a system under realistic constraints using modern methods and tools.
5. Designs and performs an experiment, analyzes and interprets the results.
6. Possesses the necessary qualifications to carry out interdisciplinary work either individually or as a team member.
7. Accesses information, performs literature search, uses databases and other knowledge sources, follows developments in science and technology.
8. Performs project planning and time management, plans his/her career development.
9. Possesses an advanced level of expertise in computer hardware and software, is proficient in using information and communication technologies.
10. Is competent in oral or written communication; has advanced command of English.
11. Has an awareness of his/her professional, ethical and social responsibilities.
12. Has an awareness of the universal impacts and social consequences of engineering solutions and applications; is well-informed about modern-day problems.
13. Is innovative and inquisitive; has a high level of professional self-esteem.
1: Lowest, 2: Low, 3: Average, 4: High, 5: Highest
General Information | Course & Exam Schedules | Real-time Course & Classroom Status
Undergraduate Curriculum | Minor Program For Non-departmental Students | Open Courses, Sections and Supervisors | Tentative Course List of Next Term | Weekly Course Schedule | Examination Schedules | Information for Registration | Prerequisite and Concurrent Courses | Legal Info and Documents for Internship | Academic Advisors for Undergraduate Program | Information for ELE 401-402 Graduation Project | Virtual Exhibitions of Graduation Projects | Erasmus+ Program | Program Educational Objectives & Student Outcomes | ECTS Course Catalog | HU Registrar's Office
Graduate Curriculum | Department's Graduate Education Directive | Open Courses and Supervisors | Tentative Course List of Next Term | Weekly Course Schedule | Final Examinations Schedule | Schedule of Graduate Thesis Defences and Seminars | Information for Registration | ECTS Course Catalog - Master's Degree | ECTS Course Catalog - PhD Degree | HU Graduate School of Science and Engineering