COURSE INTRODUCTION AND APPLICATION INFORMATION


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
Elective
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 introduce algorithms by looking at the real-world problems motivating them. Students will be taught a range of design and analysis techniques for problems that arise in computing applications. Greedy algorithms, divide and conquer type of algorithms and dynamic programming will be discussed within the context of different example applications.
Learning Outcomes The students who succeeded in this course;
  • will be able to classify the different types of algorithms together with their purpose of use.
  • will be able to explain time and space complexity of different type of algorithms,
  • will be able to devise efficient greedy algorithms suitable to solve a particular computational problem,
  • will be able to implement efficient divide and conquer algorithms suitable to solve a particular computational problem,
  • will be able to formulate efficient dynamic programs suitable to solve a particular optimization problem.
Course Description The course covers basics of Algorithms Analysis, graph theoretic concepts, greedy algorithms, divide and conquer algorithms and dynamic programming algorithms.

 



Course Category

Core Courses
X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction: Some Representative Problems Course Book; Chapter 1.
2 Basics of Algorithms Analysis Course Book; Chapter 2.
3 Graphs Course Book; Chapter 3.
4 Greedy Algorithms: Interval Scheduling Course Book; Chapter 4.
5 Greedy Algorithms: Scheduling to Minimize Lateness Course Book; Chapter 4.
6 Greedy Algorithms : Minimum-Cost Arborescences Course Book; Chapter 4.
7 Divide and Conquer: Counting Inversions Course Book; Chapter 5.
8 Midterm 1
9 Divide and Conquer: Integer Multiplication Course Book; Chapter 5.
10 Divide and Conquer: Convolutions and The Fast Fourier Transform Course Book; Chapter 5.
11 Dynamic Programming: Weighted Interval Scheduling Course Book; Chapter 6.
12 Dynamic Programming: Subset Sums and Knapsacks Course Book; Chapter 6.
13 Dynamic Programming: Sequence Alignment Course Book; Chapter 6.
14 Midterm 2 Course Book; Chapter 11.
15 Final Exam
16 -
Course Notes/Textbooks

Algorithm Design, Jon Kleinberg, Éva Tardos, ISBN-10: 0321295358, ISBN-13: 9780321295354, Addison-Wesley, 2005.

Suggested Readings/Materials

Algorithms, Cormen, T.H., Liesersan, C.E. and Rivest, R.L. ISBN 0-01-013143-0, McGraw-Hill

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
1
20
Seminar / Workshop
Oral Exam
Midterm
2
40
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
3
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

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
4
60
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
1
25
Seminar / Workshop
Oral Exam
Midterms
2
25
Final Exams
1
42
    Total
225

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1 Understands and applies the foundational theories of Computer Engineering in a high level. X
2 Possesses a great depth and breadth of knowledge about Computer Engineering including the latest developments. X
3 Can reach the latest information in Computer Engineering and possesses a high level of proficiency in the methods and abilities necessary to comprehend it and conduct research with it. X
4 Conducts a comprehensive study that introduces innovation to science and technology, develops a new scientific procedure or a technological product/process, or applies a known method in a new field.  X
5 Independently understands, designs, implements and concludes a unique research process in addition to managing it.  X
6 Contributes to science and technology literature by publishing the output of his/her academic studies in respectable academic outlets.
7 Interprets scientific, technological, social and cultural developments and relates them to the general public with a commitment to scientific objectivity and ethical responsibility.
8 Performs critical analysis, synthesis and evaluation of ideas and developments in Computer Engineering.
9 Performs verbal and written communications with professionals as well as broader scientific and social communities in Computer Engineering, by using English at least at the European Language Portfolio C1 General level, performs written, oral and visual communications and discussions in a high level.
10 Develops strategies, policies and plans about systems and topics that Computer Engineering uses, and interprets the outcomes.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest