INDUSTRIAL ENGINEERING | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
SEN2212 | Data Structures and Algorithms II | Fall | 2 | 2 | 3 | 7 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Non-Departmental Elective |
Course Level: | Bachelor’s Degree (First Cycle) |
Mode of Delivery: | Face to face |
Course Coordinator : | Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR |
Course Lecturer(s): |
Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR Dr. Öğr. Üyesi YÜCEL BATU SALMAN RA SEVGİ CANPOLAT RA MERVE ARITÜRK |
Recommended Optional Program Components: | None |
Course Objectives: | The objective of this course is to analyze data structures and algorithms used in software engineering in detail. After completing the course, the student will have knowledge of applying, implementing and analysis of data structures, including, trees, binary search trees, balanced search trees, heaps and graphs. Certain fundamental techniques, such as sorting, hashing and greedy algorithms are also taught. |
The students who have succeeded in this course; The students who have succeeded in this course; 1) Describe and apply basic object oriented programming principles. 2) Implement basic data structures such as trees, binary search trees, balanced search trees, heaps and graphs. 3) Describe and implement sorting algorithms on common data structures. 4) Describe and implement searching algorithms on common data structures. 5) Implement and use hashing algorithms. 6) Implement and use greedy algorithms. 7) Choose and design data structures for writing efficient programs. |
The course content is composed of basic data structures like trees, binary search trees, balanced search trees, heaps, graphs and sorting, hashing and greedy algorithms. |
Week | Subject | Related Preparation |
1) | Introduction and Sorting Algorithms. | Sorting algorithms. |
2) | Introduction to different tree structures. | Trees. |
3) | Introduction to binary search trees. | Binary search trees. |
4) | Implementing binary search tree using Java. | Binary search trees. |
5) | Introduction to balanced trees and implementing AVL balanced tree structure using Java. | AVL trees. |
6) | Using other balanced tree structure using Java. | Other balanced trees. |
7) | Using heap structure and implementing them using Java. | Heap. |
8) | Using heaps as priority queues. Midterm. | Heap. |
9) | Analyzing and implementing hashing algorithms. | Hashing algorithms. |
10) | Analyzing and implementing graph structure using Java. | Graph. |
11) | Analyzing and implementing graph algorithms. | Graph algorithms. |
12) | Analyzing and implementing greedy algorithms. | Greedy algorithms. |
13) | Analyzing and implementing greedy algorithms. Quiz. | Greedy algorithms. |
14) | Review. |
Course Notes / Textbooks: | Data Structures & Problem Solving Using Java (Mark Allen Weiss) Data Structures and Algorithm Analysis in Java (Mark Allen Weiss) Data Structures and Abstractions with Java (Frank Carrano) |
References: | Yok. |
Semester Requirements | Number of Activities | Level of Contribution |
Application | 4 | % 10 |
Quizzes | 1 | % 10 |
Project | 1 | % 15 |
Midterms | 1 | % 25 |
Final | 1 | % 40 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 45 | |
PERCENTAGE OF FINAL WORK | % 55 | |
Total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 2 | 28 |
Laboratory | 14 | 2 | 28 |
Study Hours Out of Class | 12 | 2 | 24 |
Project | 10 | 2 | 20 |
Homework Assignments | 2 | 5 | 10 |
Quizzes | 5 | 2 | 10 |
Midterms | 5 | 3 | 15 |
Final | 10 | 3 | 30 |
Total Workload | 165 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Build up a body of knowledge in mathematics, science and industrial engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems. | |
2) | Identify, formulate, and solve complex engineering problems; select and apply proper analysis and modeling methods for this purpose. | |
3) | Design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose. The ability to apply modern design methods to meet this objective. | |
4) | Devise, select, and use modern techniques and tools needed for solving complex problems in industrial engineering practice; employ information technologies effectively. | |
5) | Design and conduct experiments, collect data, analyze and interpret results for investigating the complex problems specific to industrial engineering. | |
6) | Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working independently. | |
7) | Demonstrate effective communication skills in both oral and written English and Turkish. Writing and understanding reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instructions. | |
8) | Recognize the need for lifelong learning; show ability to access information, to follow developments in science and technology, and to continuously educate him/herself. | |
9) | Develop an awareness of professional and ethical responsibility, and behaving accordingly. Information about the standards used in engineering applications. | |
10) | Know business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development. | |
11) | Know contemporary issues and the global and societal effects of modern age engineering practices on health, environment, and safety; recognize the legal consequences of engineering solutions. | |
12) | Develop effective and efficient managerial skills. |