| MATHEMATICS (TURKISH, PHD) | |||||
| PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| SEN2211 | Data Structures and Algorithms I | Fall | 2 | 2 | 3 | 7 |
| The course opens with the approval of the Department at the beginning of each semester |
| Language of instruction: | En |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Assist. Prof. ÖZGE YÜCEL KASAP |
| Course Lecturer(s): |
Assist. Prof. DUYGU ÇAKIR YENİDOĞAN Assist. Prof. TAMER UÇAR Assist. Prof. BETÜL ERDOĞDU ŞAKAR RA MERVE ARITÜRK Prof. Dr. NAFİZ ARICA RA SEVGİ CANPOLAT |
| Course Objectives: | This is an introductory course on common data structures that are used in software engineering. After completing the course, the student will have knowledge of applying, implementing and analysis of basic data structures, including, lists, stacks and queues. Certain fundamental techniques, such as sorting, searching and recursion are also taught. The teaching methods of the course are lecture and practice. |
|
The students who have succeeded in this course; 1) Describe and apply basic object oriented programming principles. 2) Implement basic data structures such as linked lists, stacks and queues. 3) Analyze the complexity and efficiency of algorithms. 4) Choose and design data structures for writing efficient programs. 5) Implement recursive algorithms. 6) Describe and implement sorting algorithms on common data structures. 7) Describe and implement search algorithms on common data structures. |
| The course content is composed of object oriented Java review, the complexity and efficiency of algorithms, introduction to list-stack-queue structures, implementing list-stack-queue structures, recursion, searching algorithms and sorting algorithms. |
| Week | Subject | Related Preparation | |
| 1) | Introduction to Data Structures and Algorithms Complexity Analysis | ||
| 2) | Introduction to Linked Lists | ||
| 3) | Doubly Linked Lists Ordered Linked Lists | ||
| 4) | |||
| 5) | Stacks | ||
| 6) | Stacks for Algebraic Operations | ||
| 7) | Queues | ||
| 8) | Queues | ||
| 9) | Data Structure Classes in Java | ||
| 10) | Recursion | ||
| 11) | Recursive Complexity | ||
| 12) | Searching Algorithms | ||
| 13) | Sorting Algorithms | ||
| 14) | Sorting algorithms | ||
| Course Notes: | 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 |
| Attendance | 0 | % 0 |
| Laboratory | 2 | % 25 |
| Application | 0 | % 0 |
| Field Work | 0 | % 0 |
| Special Course Internship (Work Placement) | 0 | % 0 |
| Quizzes | 2 | % 15 |
| Homework Assignments | 0 | % 0 |
| Presentation | 0 | % 0 |
| Project | 0 | % 0 |
| Seminar | 0 | % 0 |
| Midterms | 1 | % 20 |
| Preliminary Jury | 0 | % 0 |
| Final | 1 | % 40 |
| Paper Submission | 0 | % 0 |
| Jury | 0 | % 0 |
| Bütünleme | % 0 | |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 2 | 28 |
| Laboratory | 14 | 2 | 28 |
| Application | 0 | 0 | 0 |
| Special Course Internship (Work Placement) | 0 | 0 | 0 |
| Field Work | 0 | 0 | 0 |
| Study Hours Out of Class | 0 | 0 | 0 |
| Presentations / Seminar | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework Assignments | 1 | 8 | 8 |
| Quizzes | 2 | 20 | 40 |
| Preliminary Jury | 0 | 0 | 0 |
| Midterms | 1 | 30 | 30 |
| Paper Submission | 0 | 0 | 0 |
| Jury | 0 | 0 | 0 |
| Final | 1 | 30 | 30 |
| Total Workload | 164 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Be able to organize events, for the development of critical and creative thinking and problem solving skills, by using appropriate methods and techniques. | |
| 2) | Ability to make individual and team work on issues related to working and social life. | |
| 3) | Ability to transfer ideas and suggestions, related to topics about his/her field of interest, written and verball. | |
| 4) | Ability to use mathematical knowledge in technology. | |
| 5) | To apply mathematical principles to real world problems. | |
| 6) | Ability to use the approaches and knowledge of other disciplines in Mathematics. | |
| 7) | Be able to set up and develope a solution method for a problem in mathematics independently, be able to solve and evaluate the results and to apply them if necessary. | |
| 8) | To be able to link abstract thought that one has to concrete events and to transfer the solutions and examine and interpret the results scientifically by forming experiments and collecting data. |