PhD in Computer Engineering with a master's degree
PhD	TR-NQF-HE: Level 8	QF-EHEA: Third Cycle	EQF-LLL: Level 8

General course introduction information

Course Code:

BIL611

Course Name:

Analysis of Paralell Algorithms

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	10

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Department Elective

Course Level:

PhD

TR-NQF-HE:8. Master`s Degree

QF-EHEA:Third Cycle

EQF-LLL:8. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Prof. Dr. PINAR YILDIRIM

Course Lecturer(s):

Course Assistants:

Course Objective and Content

Course Objectives:	The aim of this course is to gain algorithmic thinking skills and apply to basic programming problems, to analyze the complexity of the designed algorithm.
Course Content:	The concept of algorithm, algorithmic complexity, recursion concept, divide-and-manage, sorting and search algorithms

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Knows fundamentals of asymptotic complexity analysis.
2) Knows and able to analyse searching algorithms.
3) Knows divide-and-conquer algorithm design paradigm
4) Knows and able to analyse sorting algorithms.
5) Knows fundamentals of probabilistic analysis
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Introduction to Algorithms
2)	Asymtotic Analysis
3)	Divide-and-Conquer
4)	Probabilistic Analysis and Random Algorithms
5)	Order and Order Statistics
6)	Review
7)	Midterm
8)	Data Structures
9)	Hash Table
10)	Binary Search Trees
11)	Red-Black Trees (Basic Definition, Insertion)
13)	Red-Black Trees (Deletion)
14)	Review

Sources

Course Notes / Textbooks:	Introduction to Algorithms Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest ve Clifford Stein Third Edition
References:	MIT Opencourse: Introduction to Algorithms. http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/

Course-Program Learning Outcome Relationship

Learning Outcomes	1	1	2	3	4
Program Outcomes
1) Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
2) Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
3) The ability to identify, define, formulate and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
4) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
5) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
6) Ability to design experiments, conduct experiments, collect data, analyze and interpret results for the examination of engineering problems.
7) The ability to communicate effectively in Turkish both verbally and in writing; at least one foreign language knowledge.
8) Knowledge of the necessity of lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Professional and ethical responsibility.
10) Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.
11) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
2)	Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
3)	The ability to identify, define, formulate and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
4)	The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
5)	Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
6)	Ability to design experiments, conduct experiments, collect data, analyze and interpret results for the examination of engineering problems.
7)	The ability to communicate effectively in Turkish both verbally and in writing; at least one foreign language knowledge.
8)	Knowledge of the necessity of lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9)	Professional and ethical responsibility.
10)	Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.
11)	The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.

Learning Activity and Teaching Methods

Expression

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	1	% 10
Midterms	1	% 30
Final	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	13	3	39
Quizzes	1	24	24
Midterms	1	36	36
Final	1	36	36
Total Workload			135