Algorithm Design and Analysis
Computer Engineering (MSc.)
Institute of Natural and Applied Sciences
Second Cycle (Master's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Algorithm Design and Analysis | BLM591 | Elective | Master's degree | 1 | Fall | 8 |
Name of Lecturer(s)
Prof. Dr. Nevcihan DURU
Prof. Dr. Ahmet SAYAR
Associate Prof. Dr. Alev MUTLU
Learning Outcomes of the Course Unit
1) Specify the principles of algorithm design
2) Identify the strategies and criteria for selecting the best alternative for representing data and data structures on computer programming applications
3) Implement some well-known algorithms
4) Analyze the performance of algorithms
5) Identify algorithm design strategies providing appropriate solutions for certain problems
6) Analyze the efficiency of different algorithms for the same problem and classify them according to their complexity
7) Present recent applications and trends/improvements in algorithm designs
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
| Learning Outcomes | ||||||||||||
| 1 | No relation | No relation | Low | Middle | No relation | Low | No relation | No relation | Low | No relation | No relation | |
| 2 | No relation | No relation | Low | Middle | No relation | Low | No relation | Low | Middle | No relation | No relation | |
| 3 | No relation | No relation | No relation | Middle | No relation | High | No relation | Low | No relation | No relation | No relation | |
| 4 | No relation | No relation | Middle | Low | No relation | Middle | No relation | No relation | Low | No relation | No relation | |
| 5 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 6 | No relation | No relation | Low | Low | No relation | Middle | Low | No relation | No relation | No relation | No relation | |
| 7 | No relation | No relation | No relation | No relation | No relation | Middle | Middle | No relation | Low | No relation | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Undergraduate level Data Structure course
Course Contents
This course equips candidates with in-depth knowledge on the design of an algorithm, problems coming from many areas of computer science and engineering to motivate our exploration of algorithm design and analysis techniques, the techniques include divide-and-conquer, dynamic programming, greedy, randomization, amortized analysis and reduction.
Weekly Schedule
1) Introduction to Algorithm design and Analysis2) Data Structures: Stacks, Queues, Linked Lists
3) Data Structures: Trees, Binary Search Trees, Heaps, Graphs
4) Fundamentals of Algorithm Complexity Analysis
5) Divide and Conquer Method: Mergesort, Quicksort, Quickselect
6) Divide and Conquer Method 2
7) Greedy Method
8) Midterm Examination/Assessment
9) Dynamic Programming: Overall Technique
10) Dynamic Programming: Matrix Chain Problem, All-pairs Shortest Path
11) Applications of Search Algorithms
12) Applications of Sorting Algorithms
13) Graph Traversal Techniques: Tree Traversal and Applications
14) Introduction to the Theory of NP-completeness
15) Recent Applications and Trends in Algorithm Designs
16) Final Examination
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
1) Lecture
2) Discussion
3) Demonstration
4) Group Study
5) Problem Solving
Assessment Methods and Criteria
Contribution of Semester Studies to Course Grade |
50% |
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Contribution of Final Examination to Course Grade |
50% |
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Total | 100% | |||||||||||
Language of Instruction
Turkish
Work Placement(s)
Not Required