| INDUSTRIAL PRODUCTS DESIGN | |||||
| 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) | Having the theoretical and practical knowledge proficiency in the discipline of industrial product design | |
| 2) | Applying professional knowledge to the fields of product, service and experience design development | |
| 3) | Understanding, using, interpreting and evaluating the design concepts, knowledge and language | |
| 4) | Knowing the research methods in the discipline of industrial product design, collecting information with these methods, interpreting and applying the collected knowledge | |
| 5) | Identifying the problems of industrial product design, evaluating the conditions and requirements of problems, producing proposals of solutions to them | |
| 6) | Developing the solutions with the consideration of social, cultural, environmental, economic and humanistic values; being sensitive to personal differences and ability levels | |
| 7) | Having the ability of communicating the knowledge about design concepts and solutions through written, oral and visual methods | |
| 8) | To identify and apply the relation among material, form giving, detailing, maintenance and manufacturing methods of design solutions | |
| 9) | Using the computer aided information and communication technologies for the expression of industrial product design solutions and applications | |
| 10) | Having the knowledge and methods in disciplines like management, engineering, psychology, ergonomics, visual communication which support the solutions of industrial product design; having the ability of searching, acquiring and using the knowledge that belong these disciplines when necessary. | |
| 11) | Using a foreign language to command the jargon of industrial product design and communicate with the colleagues from different cultures | |
| 12) | Following and evaluating the new topics and trends that industrial product design needs to integrate according to technological and scientific developments |