| ARTIFICIAL INTELLIGENCE ENGINEERING | |||||
| Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| CMP2003 | Data Structures and Algorithms (C++) | Fall | 3 | 2 | 4 | 7 |
| The course opens with the approval of the Department at the beginning of each semester |
| Language of instruction: | En |
| Type of course: | Must Course |
| Course Level: | Bachelor |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Dr. Öğr. Üyesi TEVFİK AYTEKİN |
| Course Lecturer(s): |
Dr. Öğr. Üyesi ERKUT ARICAN Dr. Öğr. Üyesi TEVFİK AYTEKİN RA ÇİĞDEM ERİŞ |
| Course Objectives: | This is an introductory course on common data structures that are used in computer engineering. After completing the course, the student will have knowledge of applying, implementing and analysis of basic data structures, including, lists, stacks, queues, hash tables and binary trees. Certain fundamental techniques, such as sorting, searching and recursion are also introduced. |
|
The students who have succeeded in this course; I. Describe and apply basic object oriented programming principles. II. Implement basic data structures such as linked lists, stacks, queues, hash tables, and trees. III. Analyze the efficiency of algorithms. IV. Choose and design data structures for writing efficient programs and apply/report these methods in a group project. V. Implement recursive algorithms. VI. Describe and implement sorting algorithms on common data structures. VII. Describe and implement search algorithms on common data structures. |
| After course overview and review of object oriented programming and C++, complexity analysis of algorithms will be introduced then array-based lists, linked lists, recursion, stacks, and queues will be covered. After the midterm search algorithms and hashing will be introduced. Lastly, sorting algorithms, binary search trees and B-trees will be covered during the end of the course. |
| Week | Subject | Related Preparation | |
| 1) | Course overview and review of object oriented programming and C++ | ||
| 2) | Complexity analysis of algorithms | ||
| 3) | Array-based and linked lists | ||
| 4) | Array-based and linked lists | ||
| 5) | Recursion | ||
| 6) | Stacks | ||
| 7) | Queues | ||
| 8) | Midterm Exam | ||
| 9) | Searching algorithms | ||
| 10) | Hashing algorithms | ||
| 11) | Sorting algorithms | ||
| 12) | Sorting algorithms | ||
| 13) | Binary search trees | ||
| 14) | B-trees | ||
| Course Notes: | D. S. Malik, Data Structures Using C++, 2e. Course Technology - Cengage Learning, 2010. |
| References: |
| Semester Requirements | Number of Activities | Level of Contribution |
| Attendance | 0 | % 0 |
| Laboratory | 0 | % 0 |
| Application | 0 | % 0 |
| Field Work | 0 | % 0 |
| Special Course Internship (Work Placement) | 0 | % 0 |
| Quizzes | 1 | % 10 |
| Homework Assignments | 0 | % 0 |
| Presentation | 0 | % 0 |
| Project | 1 | % 20 |
| Seminar | 0 | % 0 |
| Midterms | 1 | % 30 |
| Preliminary Jury | 0 | % 0 |
| Final | 1 | % 40 |
| Paper Submission | 0 | % 0 |
| Jury | 0 | % 0 |
| Bütünleme | % 0 | |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 40 | |
| PERCENTAGE OF FINAL WORK | % 60 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 3 | 42 |
| Laboratory | 14 | 5 | 70 |
| 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 | 1 | 20 | 20 |
| Homework Assignments | 0 | 0 | 0 |
| Quizzes | 1 | 8 | 8 |
| Preliminary Jury | 0 | 0 | 0 |
| Midterms | 1 | 15 | 15 |
| Paper Submission | 0 | 0 | 0 |
| Jury | 0 | 0 | 0 |
| Final | 1 | 18 | 18 |
| Total Workload | 173 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Have sufficient background in mathematics, science and artificial intelligence engineering. | 5 |
| 2) | Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions. | 5 |
| 3) | Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose. | 5 |
| 4) | Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction. | 5 |
| 5) | Select and use modern techniques and tools necessary for engineering applications. | 5 |
| 6) | Design and conduct experiments, collect data, and analyse and interpret results. | 5 |
| 7) | Work effectively both as an individual and as a multi-disciplinary team member. | |
| 8) | Access information via conducting literature research, using databases and other resources | |
| 9) | Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning. | |
| 10) | Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field. | |
| 11) | Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level. | |
| 12) | Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age. | |
| 13) | Have a sense of professional and ethical responsibility. | |
| 14) | Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices. |