| Course Name | Advanced Algorithms |
| Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
|---|---|---|---|---|---|
| CE 601 | Fall/Spring | 3 | 0 | 3 | 7.5 |
| Prerequisites | None | |||||
| Course Language | English | |||||
| Course Type | Service Course | |||||
| Course Level | Third Cycle | |||||
| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | ||||||
| Course Coordinator | ||||||
| Course Lecturer(s) | ||||||
| Assistant(s) | - | |||||
| Course Objectives | The objective of this course is to provide a comprehensive and detailed study of the design and analysis of algorithms. The course aims at discussing state of the art algorithms and related data structures that are crucial to achieve satisfactory levels of performance in industry and research since the processor speed-ups we have been enjoying are coming to an end and better algorithms are needed in order to cope with the increasing demand of data processing. |
| Learning Outcomes | The students who succeeded in this course;
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| Course Description | The course covers master theorem for solving recurrences, probabilistic analysis, amortized analysis, greedy algorithms, divide-and-conquer type of algorithms, dynamic programming and approximation algorithms. |
| Related Sustainable Development Goals | |
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| Core Courses | X |
| Major Area Courses | ||
| Supportive Courses | ||
| Media and Managment Skills Courses | ||
| Transferable Skill Courses |
| Week | Subjects | Required Materials |
| 1 | The Role of Algorithms in Computing, Growth of Functions | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 1, 2, 3) |
| 2 | Recurrences, Master Theorem | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 4) |
| 3 | Probabilistic Analysis and Randomized Algorithms | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 5) |
| 4 | Medians and Order Statistics | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 9) |
| 5 | Red-Black Trees | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 13) |
| 6 | Augmenting Data Structures | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 14) |
| 7 | Dynamic Programming | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 15) |
| 8 | Greedy Algorithms | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 16) |
| 9 | Amortized Analysis | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 17) |
| 10 | Number-Theoretic Algorithms | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 31) |
| 11 | String Matching | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 32) |
| 12 | NP-Completeness | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 34) |
| 13 | Approximation Algorithms | T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms, 3/e, The MIT Press, 2009 (Ch. 35) |
| 14 | Learning Algorithms, Decision Tree Learning | |
| 15 | Review of the semester | |
| 16 | - |
| Course Notes/Textbooks | The textbook referenced above and course slides |
| Suggested Readings/Materials | Related Research Papers |
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments | ||
| Presentation / Jury | ||
| Project | ||
| Seminar / Workshop | ||
| Oral Exam | ||
| Midterm | 2 | 50 |
| Final Exam | 1 | 50 |
| Total |
| Weighting of Semester Activities on the Final Grade | 50 | |
| Weighting of End-of-Semester Activities on the Final Grade | 50 | |
| Total |
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Course Hours (Including exam week: 16 x total hours) | 16 | 3 | 48 |
| Laboratory / Application Hours (Including exam week: 16 x total hours) | 16 | ||
| Study Hours Out of Class | 15 | 6 | 90 |
| Field Work | |||
| Quizzes / Studio Critiques | |||
| Portfolio | |||
| Homework / Assignments | |||
| Presentation / Jury | |||
| Project | |||
| Seminar / Workshop | |||
| Oral Exam | |||
| Midterms | 2 | 25 | |
| Final Exams | 1 | 37 | |
| Total | 225 |
| # | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
| 1 | Accesses information in breadth and depth by conducting scientific research in Computer Engineering; evaluates, interprets and applies information. | X | ||||
| 2 | Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations. | X | ||||
| 3 | Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines. | X | ||||
| 4 | Is informed about new and upcoming applications in the field and learns them whenever necessary. | X | ||||
| 5 | Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions. | X | ||||
| 6 | Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs | X | ||||
| 7 | Designs and implements studies based on theory, experiments and modelling; analyses and resolves the complex problems that arise in this process. | X | ||||
| 8 | Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility. | X | ||||
| 9 | Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale. | X | ||||
| 10 | Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form. | X | ||||
| 11 | Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications. | X | ||||
| 12 | Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
