Advanced Algorithms (CMPE524) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Advanced Algorithms CMPE524 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type N/A
Course Level Ph.D.
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
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;
  • Analyze and design algorithms and measure their complexities
  • Recognize the theoretical foundations of the algorithms
  • Develop efficient algorithms for the solution of real life computational problems
  • Implement algorithms
Course Content Design and analysis of algorithms, O-notation, graph algorithms, topological sort, minimum spanning trees, single-shortest paths, all-pairs shortest paths, flow networks, NP-hard and NP-complete problems.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction: Growth of Functions Chapters 1-3 (main text)
2 Introduction: Recurrences Chapter 4
3 Introduction: Sorting Chapter 6-7
4 Graphs, BFS, DFS Chapter 22
5 Topological Sort, Strongly Connected Components Chapter 22
6 Minimum Spanning Trees: Kruskall and Prim Algorithms Chapter 23
7 Single-Shortest Paths: Bellman-Ford Algorithm Chapter 24
8 Single-Shortest Paths: Dijkstra's Algorithm Chapter 24
9 All-Pairs Shortest Paths Chapter 25
10 Maximum-Flow: Flow networks Chapter 26
11 Maximum-Flow: Ford-Fulkerson's Algorithm Chapter 26
12 Maximum-Flow: Maximum Bipartite Matching Chapter 26
13 NP-Completeness Chapter 34
14 NP-Completeness Chapter 34
15 Review
16 Review

Sources

Course Book 1. T.H.Cormen, C.E.Leiserson, R.L.Rivest and C.Stein: Introduction to Algorithms, 2nd ed., MIT Press 2001.
Other Sources 2. E.Horowitz, S.Sahni: Fundamentals of Computer Algorithms, Computer Science Press, 1989.
3. E.Horowitz, S.Sahni, S.Rajasekeran, Computer Algorithms, ISBN: 978-0-929306-41-4, Silicon Press, 2008.
4. J.Kleinberg, E.Tardos, Algorithm Design, Addison – Wesley, ISBN: 0-321-29535-8, 2006.
5. 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.
6. 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 1 10
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 50
Final Exam/Final Jury 1 35
Toplam 5 100
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 carry out advanced research activities, both individual and as a member of a team
2 Ability to evaluate research topics and comment with scientific reasoning
3 Ability to initiate and create new methodologies, implement them on novel research areas and topics
4 Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions
5 Ability to apply scientific philosophy on analysis, modelling and design of engineering systems
6 Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level
7 Contribute scientific and technological advancements on engineering domain of his/her interest area
8 Contribute industrial and scientific advancements to improve the society through research activities

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 1 5 5
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 8 16
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 132