DATA STRUCTURE AND ALGORITHMS PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
BIL202	DATA STRUCTURE AND ALGORITHMS	4	5	4	7

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assist.Prof. OĞUZHAN ÖZTAŞ
Instructor(s) of the Course Unit
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	The goal is to teach students to analyze the time and space requirements of essential algorithms and data structures, to examine various data structures such as stacks, queues, trees, and graphs, and to implement algorithms in Python.
Contents of the Course Unit:	Stacks, applications of stack structures, queues, enqueue and dequeue operations, priority queues, tree structures, tree applications, binary search trees, applications of heap structures, balanced search trees, graph structures, and applications of graph structures.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Understand the fundamental principles of recursion and its relationship with mathematical induction.
Use recursion as a problem-solving and programming technique.
Develop design and implementation skills for key abstract data types such as linked lists, doubly linked lists, stacks, and queues.
Analyze discrete data structures, such as trees, using combinatorial methods.
Understand algorithmic solutions for sorting and searching problems and design common search structures like binary search trees.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	Written Resources	Introduction to the stack data structure	Face-to-Face Instruction
2	Written Resources	Coding the stack data structure in Python	Face-to-Face Instruction
3	Written Resources	Coding the stack data structure in Python	Face-to-Face Instruction
4	Written Resources	Coding the stack data structure in Python	Face-to-Face Instruction
5	Written Resources	Queue, deque, and priority queue data structures	Face-to-Face Instruction
6	Written Resources	Coding queue, deque, and priority queue data structures in Python	Face-to-Face Instruction
7	Written Resources	Introduction to the tree data structure	Face-to-Face Instruction
8	-	MID-TERM EXAM	-
9	Written Resources	Coding the tree data structure in Python	Face-to-Face Instruction
10	Written Resources	Binary search trees and coding them in Python	Face-to-Face Instruction
11	Written Resources	Heap data structure and coding it in Python	Face-to-Face Instruction
12	Written Resources	Heap structures	Face-to-Face Instruction
13	Written Resources	Balanced search trees	Face-to-Face Instruction
14	Written Resources	Introduction to the graph data structure	Face-to-Face Instruction
15	Written Resources	Coding the graph data structure in Python	Face-to-Face Instruction
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Data Structures and Program Design In C, Robert L. Kruse, Bruce P. Leung, ve Clovis L. Tondo, Pearson, 1996 Goodrich, M. T., Tamassia, R., & Goldwasser, M. H. (2013). Data structures and algorithms in Python (pp. 978-1). Hoboken: Wiley.

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Explains the fundamental engineering concepts of computer science and relates them to the groundwork of computer science.				3

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Uses theoretical and practical knowledge coming from mathematics, probability, statistics and various other branches of life sciences, to find solutions to engineering problems.				3

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Determines the components and the underlying process of a system and designs an appropriate computational model under reasonable constraints.				3
2	Designs a computer-aided conceptual model with modern techniques.				3

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Determines, detects and analyzes the areas of computer science applications and develops appropriate solutions.				3
2	Identifies, models and solves computer engineering problems by applying appropriate analytical methods.				3
3	Determines and uses the necessary information technologies in an efficient way for engineering applications.				3

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Possess the responsibility and ability to design and conduct experiments for engineering problems by collecting, analyzing and interpreting data.					4
2	Possess the ability to conduct effective individual study.				3
3	Takes responsibility as a team work and contributes in an effective way.				3

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Monitors the developments in the field of information technologies by means of internet and related journals and possess the required knowledge for the management, control, development and security of information technologies.				3
2	Develops positive attitude towards lifelong learning.				3

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Communicates effectively by oral and/or written form and uses at least one foreign language.				3
2	Possess sufficient consciousness about the issues of project management, practical applications and also environmental protection, worker's health and security.					4

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Possess professional and ethical responsibility and willingness to share it.				3
2	Possess sufficient consciousness about the universality of engineering solutions and applications and be well aware of the importance of innovation.					4

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	5	70
Preliminary & Further Study	14	3	42
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	0	0	0
Reading	0	0	0
Assignment (Homework)	0	0	0
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	1	1
Preparation for the Final Exam	5	4	20
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	4	4	16
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	39	0	150