Algorithms (MCS401) Course Detail

Course Name	Course Code	Season	Lecture Hours	Application Hours	Lab Hours	Credit	ECTS
Algorithms	MCS401	Elective Courses	2	2	0	3	6

Pre-requisite Course(s)
N/A

Course Language	English
Course Type	Elective Courses
Course Level	Bachelor’s Degree (First Cycle)
Mode of Delivery	Face To Face
Learning and Teaching Strategies	Lecture, Question and Answer, Drill and Practice, Team/Group.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives	The objective of this course is to introduce the importance of algorithms in computing. Students will learn variety of different algorithmic design and analysis techniques and how to measure the complexity of algorithms. The reason for teaching well known and basic algorithms in this course is not only to show how these particular problems are solved, but also to give the students the practice and the skills required in developing solutions for new problems.
Course Learning Outcomes	The students who succeeded in this course; gain the basic knowledge of searching and sorting algorithms. gain the ability of making complexity analysis. gain the ability of applying recursion whenever appropriate. gain the basic knowledge of approaches like divide and conquer, dynamic programming, greedy algorithms and graph algorithms.
Course Content	Design and Analysis of Algorithms, O,o,ω,Ω,Θ Notations, Lower and Upper Bound Theory, Divide and Conquer Algorithms, Recurrences, Dynamic Programming, Complexity of Sorting and Searching Algorithms, Greedy Algorithms, Greedy Algorithms vs. Dynamic Programming, Elementary Graph Algorithms, NP-Completeness

Weekly Subjects and Releated Preparation Studies

Week	Subjects	Preparation
1	Analysis and Design of Algorithms, Basics	pp. 5-14
2	Growth of Functions: Asymptotic Notations O,o,ω,Ω,Θ	pp. 41-56
3	Proof of Correctness of Algorithms	pp. 15-27
4	Divide and Conquer Algorithms	pp. 28-33
5	Recurrences	pp. 63-76
6	Sorting, Insertion Sort , Quicksort	pp. 145-163
7	Merge Sort , Bubble Sort , Linear Sort Algorithms: Counting Sort, Radix Sort	pp. 165-174
8	Dynamic Programming, Matrix Multiplication Order	pp. 331-348
9	Longest Common Subsequence, Linear Search and Binary Search	pp. 350-356
10	Graph algorithms, Shortest Path Algorithms	pp. 595-607
11	Depth First Search and Breadth First Search	pp. 527-549
12	Greedy Approach. Kruskal's Algorithm	pp. 562-577
13	P, NP and NP-complete Problems	pp. 966-995
14	Basic Cryptographic Algorithms, RSA, Review	pp. 881-896
15	Review
16	Final Exam

Sources

Course Book	1. Introduction to Algorithms (Second Edition), Thomas Cormen, Charles Leiserson, Ronald Rivest and Clifford Stein, MIT Press, 2001
Other Sources	2. Algorithms in C++, 3rd Edition, Part 1-4, Robert Sedgewick, Addison Wesley, 1998, ISBN, 0-201-35088-2.
	3. Foundations of Algorithms Using C++ Pseudocode, 3rd Edition, Jones And Bartlett Publishers 2004.

Evaluation System

Requirements	Number	Percentage of Grade
Attendance/Participation	-	-
Laboratory	-	-
Application	-	-
Field Work	-	-
Special Course Internship	-	-
Quizzes/Studio Critics	-	-
Homework Assignments	5	10
Presentation	-	-
Project	-	-
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	2	50
Final Exam/Final Jury	1	40
Toplam	8	100

Percentage of Semester Work	60
Percentage of Final Work	40
Total	100

Course Category

Core Courses
Major Area Courses	X
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
#	Program Qualifications / Competencies	1	2	3	4	5
1	Has the ability to apply scientific knowledge gained in the undergraduate education and to expand and extend knowledge in the same or in a different area		X
2	Can apply gained knowledge and problem solving abilities in inter-disciplinary research	X
3	Has the ability to work independently within research area, to state the problem, to develop solution techniques, to solve the problem, to evaluate the obtained results and to apply them when necessary				X
4	Takes responsibility individually and as a team member to improve systematic approaches to produce solutions in unexpected complicated situations related to the area of study					X
5	Can develop strategies, implement plans and principles on the area of study and can evaluate obtained results within the framework					X
6	Can develop and extend the knowledge in the area and to use them with scientific, social and ethical responsibility			X
7	Has the ability to follow recent developments within the area of research, to support research with scientific arguments and data, to communicate the information on the area of expertise in a systematically by means of written report and oral/visual presentation	X
8	To have an oral and written communication ability in at least one of the common foreign languages ("European Language Portfolio Global Scale", Level B2)	X
9	Has software and hardware knowledge in the area of expertise, and has proficient information and communication technology knowledge	X
10	Follows scientific, cultural, and ethical criteria in collecting, interpreting and announcing data in the research area and has the ability to teach.			X
11	Has professional ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications.	X

ECTS/Workload Table

Activities	Number	Duration (Hours)	Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory	16	2	32
Application
Special Course Internship
Field Work
Study Hours Out of Class	14	3	42
Presentation/Seminar Prepration
Project
Report
Homework Assignments	5	6	30
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury	2	12	24
Prepration of Final Exams/Final Jury	1	18	18
Total Workload			146