Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|
| ADVANCED ALGORITHM ANALYSIS and DESIGN | COED1212915 | Spring Semester | 3+0 | 3 | 8 |
| Prerequisites Courses | |
| Recommended Elective Courses | |
| Language of Course | English |
| Course Level | Third Cycle (Doctorate Degree) |
| Course Type | Elective |
| Course Coordinator | Prof.Dr. Reda ALHAJJ |
| Name of Lecturer(s) | Prof.Dr. Reda ALHAJJ |
| Assistant(s) | |
| Aim | Introduce fundamental techniques for designing algorithms and analyzing the time and space requirements of these algorithms in a formal way. Mathematical background for algorithm analysis, sorting, searching, basic algorithms design and graph algorithms will be covered. |
| Course Content | This course contains; Introduction: analysing algorithms, designing algorithms.,Asymptotic Notation.,Divide and Conquer Design Paradigm. ,Solving Recurrences.,Analysis of Quicksort, Randomized Quicksort.,Heapsort. ,Quicksort.,Sorting in Linear Time. ,Midterm Study,Medians and Order Statistics. ,Dynamic Programming.,Greedy Algorithms.,Amortized Analysis, Dynamic Tables.,Graphs, Breadth-first Search (BFS). . |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 1) Describe the fundamentals of algorithm analysis. | 12, 14, 16, 9 | A, E |
| 2) Construct complex algorithms using the data structures that they have learned. | 12, 14, 16, 9 | A, E |
| 3) Develop complex algorithms and advanced data structures that are using trees and will be able to apply them to real world problems. | 10, 12, 14, 17, 9 | A, E, F |
| 4) Develop complex algorithms and advanced data structures that are using graphs and will be able to apply them to real world problems. | 10, 12, 14, 17, 9 | A, E, F |
| 5) Systematically look at a given computational problem and design a novel algorithm using techniques like dynamic programming, divide and conquer and greedy algorithms. | 12, 14, 16, 19, 9 | A, E |
| Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 14: Self Study Method, 16: Question - Answer Technique, 17: Experimental Technique, 19: Brainstorming Technique, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, E: Homework, F: Project Task |
Course Outline
| Order | Subjects | Preliminary Work |
|---|
| 1 | Introduction: analysing algorithms, designing algorithms. | Lecture Slides and textbook chapters 1 & 2 |
| 2 | Asymptotic Notation. | Lecture Slides and textbook chapter 3. |
| 3 | Divide and Conquer Design Paradigm. | Lecture Slides and textbook chapter 4 |
| 4 | Solving Recurrences. | Lecture Slides and textbook chapter 4 |
| 5 | Analysis of Quicksort, Randomized Quicksort. | Lecture Slides and textbook chapter 5 |
| 6 | Heapsort. | Lecture Slides and textbook chapter 6 |
| 7 | Quicksort. | Lecture Slides and textbook chapter 7 |
| 8 | Sorting in Linear Time. | Lecture Slides and textbook chapter 8 |
| 9 | Midterm Study | Lecture Slides and textbook chapters from 1 to 9, inclusive. |
| 10 | Medians and Order Statistics. | Lecture Slides and textbook chapter 9 |
| 11 | Dynamic Programming. | Lecture Slides and textbook chapter 15 |
| 12 | Greedy Algorithms. | Lecture Slides and textbook chapter 16 |
| 13 | Amortized Analysis, Dynamic Tables. | Lecture Slides and textbook chapter 17 |
| 14 | Graphs, Breadth-first Search (BFS). | Lecture Slides and textbook chapter 22 |
| Resources |
| T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, Mit Press and McGraw-Hill, 2009. |
| The notes and the presentations will be delivered during the lectures. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications |
| No | Program Qualification | Contribution Level |
| 1 | 2 | 3 | 4 | 5 |
| 1 | Develop and deepen the current and advanced knowledge in the field with original thought and/or research and come up with innovative definitions based on Master's degree qualifications. | | | | X | |
| 2 | Conceive the interdisciplinary interaction which the field is related with ; come up with original solutions by using knowledge requiring proficiency on analysis, synthesis and assessment of new and complex ideas. | | | | X | |
| 3 | Evaluate and use new information within the field in a systematic approach and gain advanced level skills in the use of research methods in the field. | | | | X | |
| 4 | Develop an innovative knowledge, method, design and/or practice or adapt an already known knowledge, method, design and/or practice to another field. | | | | | X |
| 5 | Broaden the borders of the knowledge in the field by producing or interpreting an original work or publishing at least one scientific paper in the field in national and/or international refereed journals. | | | | | |
| 6 | Contribute to the transition of the community to an information society and its sustainability process by introducing scientific, technological, social or cultural improvements. | | | | | |
| 7 | Independently perceive, design, apply, finalize and conduct a novel research process. | | | X | | |
| 8 | Ability to communicate and discuss orally, in written and visually with peers by using a foreign language at least at a level of European Language Portfolio C1 General Level. | | | | X | |
| 9 | Critical analysis, synthesis and evaluation of new and complex ideas in the field. | | | | X | |
| 10 | Recognizes the scientific, technological, social or cultural improvements of the field and contribute to the solution finding process regarding social, scientific, cultural and ethical problems in the field and support the development of these values. | | | | | |
Assessment Methods
| Contribution Level | Absolute Evaluation |
| Rate of Midterm Exam to Success | | 50 |
| Rate of Final Exam to Success | | 50 |
| Total | | 100 |
| ECTS / Workload Table |
| Activities | Number of | Duration(Hour) | Total Workload(Hour) |
| Course Hours | 14 | 3 | 42 |
| Guided Problem Solving | 14 | 4 | 56 |
| Resolution of Homework Problems and Submission as a Report | 6 | 8 | 48 |
| Term Project | 0 | 0 | 0 |
| Presentation of Project / Seminar | 0 | 0 | 0 |
| Quiz | 0 | 0 | 0 |
| Midterm Exam | 1 | 40 | 40 |
| General Exam | 1 | 40 | 40 |
| Performance Task, Maintenance Plan | 0 | 0 | 0 |
| Total Workload(Hour) | 226 |
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(226/30) | 8 |
| ECTS of the course: 30 hours of work is counted as 1 ECTS credit. |
Detail Informations of the Course
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|
| ADVANCED ALGORITHM ANALYSIS and DESIGN | COED1212915 | Spring Semester | 3+0 | 3 | 8 |
| Prerequisites Courses | |
| Recommended Elective Courses | |
| Language of Course | English |
| Course Level | Third Cycle (Doctorate Degree) |
| Course Type | Elective |
| Course Coordinator | Prof.Dr. Reda ALHAJJ |
| Name of Lecturer(s) | Prof.Dr. Reda ALHAJJ |
| Assistant(s) | |
| Aim | Introduce fundamental techniques for designing algorithms and analyzing the time and space requirements of these algorithms in a formal way. Mathematical background for algorithm analysis, sorting, searching, basic algorithms design and graph algorithms will be covered. |
| Course Content | This course contains; Introduction: analysing algorithms, designing algorithms.,Asymptotic Notation.,Divide and Conquer Design Paradigm. ,Solving Recurrences.,Analysis of Quicksort, Randomized Quicksort.,Heapsort. ,Quicksort.,Sorting in Linear Time. ,Midterm Study,Medians and Order Statistics. ,Dynamic Programming.,Greedy Algorithms.,Amortized Analysis, Dynamic Tables.,Graphs, Breadth-first Search (BFS). . |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 1) Describe the fundamentals of algorithm analysis. | 12, 14, 16, 9 | A, E |
| 2) Construct complex algorithms using the data structures that they have learned. | 12, 14, 16, 9 | A, E |
| 3) Develop complex algorithms and advanced data structures that are using trees and will be able to apply them to real world problems. | 10, 12, 14, 17, 9 | A, E, F |
| 4) Develop complex algorithms and advanced data structures that are using graphs and will be able to apply them to real world problems. | 10, 12, 14, 17, 9 | A, E, F |
| 5) Systematically look at a given computational problem and design a novel algorithm using techniques like dynamic programming, divide and conquer and greedy algorithms. | 12, 14, 16, 19, 9 | A, E |
| Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 14: Self Study Method, 16: Question - Answer Technique, 17: Experimental Technique, 19: Brainstorming Technique, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, E: Homework, F: Project Task |
Course Outline
| Order | Subjects | Preliminary Work |
|---|
| 1 | Introduction: analysing algorithms, designing algorithms. | Lecture Slides and textbook chapters 1 & 2 |
| 2 | Asymptotic Notation. | Lecture Slides and textbook chapter 3. |
| 3 | Divide and Conquer Design Paradigm. | Lecture Slides and textbook chapter 4 |
| 4 | Solving Recurrences. | Lecture Slides and textbook chapter 4 |
| 5 | Analysis of Quicksort, Randomized Quicksort. | Lecture Slides and textbook chapter 5 |
| 6 | Heapsort. | Lecture Slides and textbook chapter 6 |
| 7 | Quicksort. | Lecture Slides and textbook chapter 7 |
| 8 | Sorting in Linear Time. | Lecture Slides and textbook chapter 8 |
| 9 | Midterm Study | Lecture Slides and textbook chapters from 1 to 9, inclusive. |
| 10 | Medians and Order Statistics. | Lecture Slides and textbook chapter 9 |
| 11 | Dynamic Programming. | Lecture Slides and textbook chapter 15 |
| 12 | Greedy Algorithms. | Lecture Slides and textbook chapter 16 |
| 13 | Amortized Analysis, Dynamic Tables. | Lecture Slides and textbook chapter 17 |
| 14 | Graphs, Breadth-first Search (BFS). | Lecture Slides and textbook chapter 22 |
| Resources |
| T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, Mit Press and McGraw-Hill, 2009. |
| The notes and the presentations will be delivered during the lectures. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications |
| No | Program Qualification | Contribution Level |
| 1 | 2 | 3 | 4 | 5 |
| 1 | Develop and deepen the current and advanced knowledge in the field with original thought and/or research and come up with innovative definitions based on Master's degree qualifications. | | | | X | |
| 2 | Conceive the interdisciplinary interaction which the field is related with ; come up with original solutions by using knowledge requiring proficiency on analysis, synthesis and assessment of new and complex ideas. | | | | X | |
| 3 | Evaluate and use new information within the field in a systematic approach and gain advanced level skills in the use of research methods in the field. | | | | X | |
| 4 | Develop an innovative knowledge, method, design and/or practice or adapt an already known knowledge, method, design and/or practice to another field. | | | | | X |
| 5 | Broaden the borders of the knowledge in the field by producing or interpreting an original work or publishing at least one scientific paper in the field in national and/or international refereed journals. | | | | | |
| 6 | Contribute to the transition of the community to an information society and its sustainability process by introducing scientific, technological, social or cultural improvements. | | | | | |
| 7 | Independently perceive, design, apply, finalize and conduct a novel research process. | | | X | | |
| 8 | Ability to communicate and discuss orally, in written and visually with peers by using a foreign language at least at a level of European Language Portfolio C1 General Level. | | | | X | |
| 9 | Critical analysis, synthesis and evaluation of new and complex ideas in the field. | | | | X | |
| 10 | Recognizes the scientific, technological, social or cultural improvements of the field and contribute to the solution finding process regarding social, scientific, cultural and ethical problems in the field and support the development of these values. | | | | | |
Assessment Methods
| Contribution Level | Absolute Evaluation |
| Rate of Midterm Exam to Success | | 50 |
| Rate of Final Exam to Success | | 50 |
| Total | | 100 |
Numerical Data
Ekleme Tarihi: 24/12/2023 - 02:34Son Güncelleme Tarihi: 24/12/2023 - 02:34
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