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SECTION I: GENERAL INFORMATION ABOUT THE COURSE

Course Code Course Name Year Semester Theoretical Practical Credit ECTS
60613MEEOZ-CME0096 Analysis of Algorithms 3 Spring 2 2 3 5
Course Type : Compulsory
Cycle: Bachelor      TQF-HE:6. Master`s Degree      QF-EHEA:First Cycle      EQF-LLL:6. Master`s Degree
Language of Instruction: English
Prerequisities and Co-requisities: 60613MEEOZ-CME0044 - Data Structures and Algorithms
Mode of Delivery: Face to face
Name of Coordinator: Dr. Öğr. Üyesi GİZEM TEMELCAN ERGENECOŞAR
Dersin Öğretim Eleman(lar)ı: Dr. Öğr. Üyesi GİZEM TEMELCAN ERGENECOŞAR
Dersin Kategorisi: Programme Specific

SECTION II: INTRODUCTION TO THE COURSE

Course Objectives & Content

Course Objectives: This course will introduce the theoretical foundations of problem solving, algorithm design and analysis.
Course Content: Analysis of computer science algorithms: Sorting, searching, paging and parallelism; analysis of mathematical algorithms: Games and puzzles, network algorithms and probabilistic algorithms.

Course Learning Outcomes (CLOs)

Course Learning Outcomes (CLOs) are those describing the knowledge, skills and competencies that students are expected to achieve upon successful completion of the course. In this context, Course Learning Outcomes defined for this course unit are as follows:
Knowledge (Described as Theoritical and/or Factual Knowledge.)
  1) Determine the time and memory complexity and efficiency of algorithms. Choose one of many design alternatives by looking at the effectiveness of algorithms.
  2) Understand and explain that there are no algorithmic solutions to some problems.
  3) Solve problems using efficient sorting algorithms, and fundamental graph algorithms, including depth-first and breadth-first search, single-source and all-pairs shortest paths, transitive closure, topological sort, and at least one minimum spanning tree algorithm.
Skills (Describe as Cognitive and/or Practical Skills.)
  1) Design algorithms using commonly used algorithm design techniques such as rough-force, proliferative design, greedy, divide-and-win, random strategies.
  2) Solve the problem by using basic graphics algorithms such as Effective sorting algorithms and sorting by depth and width, single source and shortest paths of all pairs, transitive lock, topological sorting, at least one minimum spanning tree algorithm.
Competences (Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.)

Weekly Course Schedule

Week Subject
Materials Sharing *
Related Preparation Further Study
1) Growth of functions
2) Decrease and Conquer
3) Divide-and-Conquer
3) Heap and Quick Sort
4) Hash Tables and Binary Search Trees
6) Greedy Algorithms
7) B-Trees and Fibonacci Heaps
8) Midterm
9) Elementary Graph Algorithms, Minimum Spanning Trees
10) Single-Source Shortest Paths
11) All-Pairs Shortest Paths
12) Matrix Operations
13) NP-Completeness
14) Dynamic Programming
*These fields provides students with course materials for their pre- and further study before and after the course delivered.

Recommended or Required Reading & Other Learning Resources/Tools

Course Notes / Textbooks: Introduction to Algorithms ; Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein 4/e
References: The Algorithm Design Manual, 2nd Edition; Steven Skiena

SECTION III: RELATIONSHIP BETWEEN COURSE UNIT AND COURSE LEARNING OUTCOMES (CLOs)

(The matrix below shows how the course learning outcomes (CLOs) associates with programme learning outcomes (both KPLOs & SPLOs) and, if exist, the level of quantitative contribution to them.)

Relationship Between CLOs & PLOs

(KPLOs and SPLOs are the abbreviations for Key & Sub- Programme Learning Outcomes, respectively. )
CLOs/PLOs KPLO 1 KPLO 2 KPLO 3 KPLO 4 KPLO 5
1 1 2 3 4 1 2 3 4 5 6 7 8 9 10 1 2 3 4 1 2 3 4 5 6 7 8 9 10 11 12
CLO1
CLO2
CLO3
CLO4
CLO5

Level of Contribution of the Course to PLOs

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Programme Learning Outcomes Contribution Level (from 1 to 5)
1) Uses and applies theoretical and applied sciences in the field of basic science subjects for the solution of computer engineering problems. 5
2) Analyzes computer engineering applications, designs and develops models to meet specific requirements under realistic constraints and conditions. For this purpose, selects and uses appropriate methods, tools and technologies. 4
3) Owns the competencies required by the constantly developing field of computer engineering and the global competitive environment. 3
4) Applies the theoretical knowledge in business life during a semester.
5) S/he acquires the competencies that develop by the expectations of business world and the society defined as the institutional outcomes of our university on the advanced level in relation with his/her field. 3

SECTION IV: TEACHING-LEARNING & ASSESMENT-EVALUATION METHODS OF THE COURSE

Teaching & Learning Methods of the Course

(All teaching and learning methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Teaching and Learning Methods defined at the Programme Level
Teaching and Learning Methods Defined for the Course
Lectures
Discussion
Case Study
Problem Solving
Demonstration
Views
Laboratory
Reading
Homework
Project Preparation
Thesis Preparation
Peer Education
Seminar
Technical Visit
Course Conference
Brain Storming
Questions Answers
Individual and Group Work
Role Playing-Animation-Improvisation
Active Participation in Class

Assessment & Evaluation Methods of the Course

(All assessment and evaluation methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Aassessment and evaluation Methods defined at the Programme Level
Assessment and Evaluation Methods defined for the Course
Midterm
Presentation
Final Exam
Quiz
Report Evaluation
Homework Evaluation
Oral Exam
Thesis Defense
Jury Evaluation
Practice Exam
Evaluation of Implementation Training in the Workplace
Active Participation in Class
Participation in Discussions

Relationship Between CLOs & Teaching-Learning, Assesment-Evaluation Methods of the Course

(The matrix below shows the teaching-learning and assessment-evaluation methods designated for the course unit in relation to the course learning outcomes.)
LEARNING & TEACHING METHODS
COURSE LEARNING OUTCOMES
ASSESMENT & EVALUATION METHODS
CLO1 CLO2 CLO3 CLO4 CLO5
-Lectures -Midterm
-Discussion -Presentation
-Case Study -Final Exam
-Problem Solving -Quiz
-Demonstration -Report Evaluation
-Views -Homework Evaluation
-Laboratory -Oral Exam
-Reading -Thesis Defense
-Homework -Jury Evaluation
-Project Preparation -Practice Exam
-Thesis Preparation -Evaluation of Implementation Training in the Workplace
-Peer Education -Active Participation in Class
-Seminar - Participation in Discussions
-Technical Visit
-Course Conference
-Brain Storming
-Questions Answers
-Individual and Group Work
-Role Playing-Animation-Improvisation
-Active Participation in Class

Contribution of Assesment & Evalution Activities to Final Grade of the Course

Measurement and Evaluation Methods # of practice per semester Level of Contribution
Quizzes 1 % 10.00
Project 1 % 20.00
Midterms 1 % 20.00
Semester Final Exam 1 % 50.00
Total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
Total % 100

SECTION V: WORKLOAD & ECTS CREDITS ALLOCATED FOR THE COURSE

WORKLOAD OF TEACHING & LEARNING ACTIVITIES
Teaching & Learning Activities # of Activities per semester Duration (hour) Total Workload
Course 14 3 42
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 14 3 42
Presentations / Seminar 0 0 0
Project 1 10 10
Homework Assignments 0 0 0
Total Workload of Teaching & Learning Activities - - 94
WORKLOAD OF ASSESMENT & EVALUATION ACTIVITIES
Assesment & Evaluation Activities # of Activities per semester Duration (hour) Total Workload
Quizzes 1 6 6
Midterms 1 6 6
Semester Final Exam 1 12 12
Total Workload of Assesment & Evaluation Activities - - 24
TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities) 118
ECTS CREDITS OF THE COURSE (Total Workload/25.5 h) 5