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İzmir Ekonomi Üniversitesi

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    GRADUATE SCHOOL

    M.SC. in Computer Engineering (Without Thesis)

    CE 601 | 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 -
    National Occupation Classification -
    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
    Major Area Courses
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation Learning Outcome
    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 Exams
    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
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    0
    Study Hours Out of Class
    15
    4
    60
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    0
    Presentation / Jury
    0
    Project
    1
    25
    25
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    2
    25
    50
    Final Exam
    1
    42
    42
        Total
    225

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    		 PC Sub 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

     

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