CE 401 | Course Introduction and Application Information - Department of Software Engineering

Course Name

Algorithms Design

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
CE 401	Fall/Spring	3	0	3	5

Prerequisites

CE 221 To succeed (To get a grade of at least DD)

Course Language

English

Course Type

Elective

Course Level

First Cycle

Mode of Delivery

-

Teaching Methods and Techniques of the Course

Problem Solving
Lecture / Presentation

National Occupation Classification

-

Course Coordinator

Prof. Dr. Turhan TUNALI

Course Lecturer(s)

Prof. Dr. Turhan TUNALI

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. Approximation algorithms with an emphasis on load balancing and set cover problems will also be covered.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	classify the different types of algorithms together with their purpose of use.
2	explain time and space complexity of different type of algorithms,
3	devise efficient greedy algorithms suitable to solve a particular computational problem,
4	implement efficient divide and conquer algorithms suitable to solve a particular computational problem,
5	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, dynamic programming, and approximation algorithms.

Course Category	Core Courses
	Major Area Courses	X
	Supportive Courses
	Media and Management Skills Courses
	Transferable Skill Courses

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
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	Approximation Algorithms: Load Balancing	Course Book; Chapter 11.
15	Semester Review
16	Final Exam

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

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3	LO 4	LO 5
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	1	30
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm	1	30
Final Exam	1	40
Total

Weighting of Semester Activities on the Final Grade	2	60
Weighting of End-of-Semester Activities on the Final Grade	1	40
Total

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	14	4	56
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments	4	5	20
Presentation / Jury			0
Project			0
Seminar / Workshop			0
Oral Exam			0
Midterms	1	12	12
Final Exam	1	14	14
		Total	150

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Engineering Knowledge: Knowledge of mathematics, science, basic engineering, computer computation, and topics specific to related engineering disciplines; the ability to use this knowledge in solving complex engineering problems		-	-	-	X	-
	1	Mathematics	-	-	-	-	-
	2	Science	-	-	-	-	-
	3	Basic engineering	-	-	-	-	-
	4	Computer computation	-	-	-	-	-
	5	Topics specific to related engineering disciplines	-	-	-	-	-
	6	The ability to use this knowledge in solving complex engineering problems	-	-	-	-	-
2	Problem Analysis: The ability to define, formulate, and analyze complex engineering problems by using fundamental science, mathematics, and engineering knowledge, while considering the relevant UN Sustainable Development Goals (SDGs) related to the problem.		-	-	-	-	X
3	Engineering Design: The ability to design creative solutions to complex engineering problems; the ability to design complex systems, processes, devices, or products that meet present and future requirements, considering realistic constraints and conditions.		-	X	-	-	-
	1	The ability to design creative solutions to complex engineering problems	-	-	-	-	-
	2	Considering realistic constraints and conditions in designing complex systems, processes, devices, or products	-	-	-	-	-
	3	The ability to design in a way that meets current and future requirements	-	-	-	-	-
4	Use of Techniques and Tools: The ability to select and use appropriate techniques, resources, and modern engineering and information technology tools, including prediction and modeling, for the analysis and solution of complex engineering problems, while being aware of their limitations		-	X	-	-	-
5	Research and Investigation: The ability to use research methods, including literature review, designing experiments, conducting experiments, collecting data, analyzing and interpreting results, for the investigation of complex engineering problems.		-	-	-	-	-
	1	The ability to use research methods, including literature review	-	-	-	-	-
	2	Designing experiments	-	-	-	-	-
	3	Conducting experiments, collecting data, analyzing and interpreting results, for the investigation of complex engineering problems	-	-	-	-	-
6	Global Impact of Engineering Practices: Knowledge of the impacts of engineering practices on society, health and safety, the economy, sustainability, and the environment within the scope of the UN Sustainable Development Goals (SDGs); awareness of the legal consequences of engineering solutions		-	-	-	-	-
	1	Global Impact of Engineering Practices: Knowledge of the impacts of engineering practices on society, health and safety, the economy, sustainability, and the environment within the scope of the UN Sustainable Development Goals (SDGs)	-	-	-	-	-
	2	Awareness of the legal consequences of engineering solutions	-	-	-	-	-
7	Ethical Behavior: Acting in accordance with the principles of the engineering profession; knowledge of ethical responsibility; awareness of acting impartially and inclusively, without discrimination in any matter. (FENG101)		-	-	-	-	-
	1	Acting in accordance with the principles of the engineering profession; knowledge of ethical responsibility	-	-	-	-	-
	2	Awareness of acting impartially and inclusively, without discrimination in any matter.	-	-	-	-	-
8	Individual and Team Work: The ability to work effectively as an individual and as a member or leader of both intra-disciplinary and interdisciplinary teams (whether face-to-face, remote, or hybrid).		-	-	-	-	-
9	Verbal and Written Communication: Taking into account the various differences of the target audience (such as education, language, profession), particularly in technical matters.		-	-	-	-	-
	1	Verbal (ENGxxx)	-	-	-	-	-
	2	Written effective communication skills. (ENGxxx)	-	-	-	-	-
10	Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation.		-	-	-	-	-
	1	Knowledge of business practices such as project management and economic feasibility analysis; (FENG497-FENG498)	-	-	-	-	-
	2	Awareness of entrepreneurship and innovation. (FENG101)	-	-	-	-	-
11	Lifelong Learning: The ability to learn independently and continuously, adapt to new and emerging technologies, and think critically about technological changes.		-	-	-	-	-

CE 401 | Course Introduction and Application Information

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

EVALUATION SYSTEM

ECTS / WORKLOAD TABLE

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

NEWSALL NEWS

Visit of broadAngle in Izmir University of Economics

Success Stories of Izmir University of Economics Students

NEW GÜZELBAHÇE CAMPUS

GLOBAL CAREER

CONTRIBUTION TO SCIENCE

VALUING PEOPLE

BENEFIT TO SOCIETY