ECTS - Algorithms
Algorithms (CMPE323) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Algorithms | CMPE323 | 3 | 0 | 0 | 3 | 7 |
| Pre-requisite Course(s) |
|---|
| CMPE226 |
| Course Language | English |
|---|---|
| Course Type | N/A |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| Course Objectives | This course is designed to teach students how to analyse and design algorithms and measure their complexities. In addition, students will be able to develop efficient algorithms for the solution of real life computational problems. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Design and analysis of algorithms, O-notation, divide and conquer algorithms, dynamic programming, backtracking and branch and bound, lower bound theory, complexity of sorting and searching algorithms, graph algorithms, NP-hard and NP-complete problems, basic NPC problems, proving problems to be NPC, analysis of some string processing algorithms. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction; Growth Functions | Chapters 1.1, 1.2, 3.1, 3.2 (main text) |
| 2 | Analyzing Algorithms: Insertion Sort | Chapters 2.1, 2.2 |
| 3 | Analyzing Algorithms: Merge Sort, Recurrences (The Recursion-Tree Method) | Chapter 2.3, 4 (introduction of chapter), 4.2 |
| 4 | Analyzing Algorithms: Quicksort and Analysis of Quicksort | Chapter 7.1, 7.2, 7.4, 5.2 |
| 5 | Red-Black Trees | Chapter 13.1, 13.2, 13.3 |
| 6 | Dynamic Programming | Chapter 15 (introduction of chapter), 15.1 |
| 7 | Dynamic Programming | Chapter 15.3, 15.2 |
| 8 | Dynamic Programming | Chapter 15.2 (cont.), 15.4 |
| 9 | Greedy Algorithms | Chapter 16.1, 16.2 |
| 10 | Greedy Algorithms | Chapter 16.2 (cont.), 16.3 |
| 11 | Graph Algorithms | Chapters 22.1, 22.2, 22.3 |
| 12 | Graph Algorithms | Chapters 22.4, 23 (introduction of chapter), 23.1, 23.2 (Kruskal) |
| 13 | Graph Algorithms | Chapters 24 (introduction of chapter), 24.1, 24.2 |
| 14 | Graph Algorithms, NP-Completeness | Chapter 24.2 (cont.), 24.3, 34 (introduction of chapter) |
| 15 | Review | - |
| 16 | Review |
Sources
| Course Book | 1. T.H.Cormen, C.E.Leiserson, R.L.Rivest and C.Stein: Introduction to Algorithms, MIT Press 2001. |
|---|---|
| Other Sources | 2. Anany Levitin, Introduction to the Design & Analysis of Algorithms, 3rd edition, Pearson, 2012. |
| 3. E.Horowitz, S.Sahni: Fundamentals of Computer Algorithms, Computer Science Press, 1989 | |
| 4. E.Horowitz, S.Sahni, S.Rajasekeran, Computer Algorithms, ISBN: 978-0-929306-41-4, Silicon Press, 2008. | |
| 5. J.Kleinberg, E.Tardos, Algorithm Design, Addison – Wesley, ISBN: 0-321-29535-8, 2006. | |
| 6. A.V.Aho, J.E.Hopcroft, J.D.Ullman, The Design and Analysis of Computer Algorithms, Addison-Wesley Series in Computer Science and Information Processing, 1979. | |
| 7. S.S. Skiena, The Algorithm Design Manual, Springer – Verlag, New York, 1998. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | 1 | 5 |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 3 | 10 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 50 |
| Final Exam/Final Jury | 1 | 35 |
| Toplam | 7 | 100 |
| Percentage of Semester Work | 65 |
|---|---|
| Percentage of Final Work | 35 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Ability to apply knowledge on Mathematics, Science and Engineering to advanced systems. | |||||
| 2 | Implementing long-term research and development studies in major areas of Electrical and Electronics Engineering. | |||||
| 3 | Ability to use modern engineering tools, techniques and facilities in design and other engineering applications. | X | ||||
| 4 | Graduating researchers active on innovation and entrepreneurship. | |||||
| 5 | Ability to report and present research results effectively. | |||||
| 6 | Increasing the performance on accessing information resources and on following recent developments in science and technology. | |||||
| 7 | An understanding of professional and ethical responsibility. | |||||
| 8 | Increasing the performance on effective communications in both Turkish and English. | |||||
| 9 | Increasing the performance on project management. | |||||
| 10 | Ability to work successfully at project teams in interdisciplinary fields. | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 3 | 48 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 3 | 6 | 18 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 20 | 40 |
| Prepration of Final Exams/Final Jury | 1 | 20 | 20 |
| Total Workload | 174 | ||