DATA STRUCTURES AND ALGORITHMS PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
BIL202	DATA STRUCTURES AND ALGORITHMS	5	5	4	6

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 :	Elective
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Prof. HAMDİ ALPER ÖZYİĞİT
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	Written Resources	Coding the tree data structure in Python	Face-to-Face Instruction
9	Written Resources	Binary search trees and coding them in Python	Face-to-Face Instruction
10	-	MID-TERM EXAM	-
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	Examination Method
Mid-Term Exam	1	30		Classical Exam
Homework Assessment	1	10
Practice	1	10
Final Exam	1	50		Classical Exam
TOTAL	4	100

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Able to adopt math and science knowledge to the problems of Mechatronic Engineering.				3

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Can use the scientific methods to solve problems of Mechatronic Engineering.				3
2	Able to plan experiment, build hardware, collect data using modern devices and analyze data.				3

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Can define, scientize and solve the actual mechatronics problems.				3

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use modern tools such as softwares in engineering design and analysis.				3

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Prone to work in interdisciplinary teams and be a team leadership.				3

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Able to find solutions that meet technical and economical expectations when designing a system with components.				3
2	Can approach with a global perspective to Mechatronics Engineering.				3
3	Able to keep up to date of self-awarness in the field.				3
4	Can follow academic and industrial developments related Mechatronics Engineering.				3

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Able to work in the field, interdisciplinary and multidisciplinary environments.				3
2	Have written and verbal communication skills in Turkish and English.				3

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Have professional and ethical values and sensitive to these.				3
2	Sensitive to health and safety issues in Mechatronic Engineering.				3
3	Sensitive to social, environmental and economic factors in professional activities.				3

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