Computer Programming (CMPE102) Course Detail

Course Name	Course Code	Season	Lecture Hours	Application Hours	Lab Hours	Credit	ECTS
Computer Programming	CMPE102	1. Semester	2	2	0	3	4

Pre-requisite Course(s)
N/A

Course Language	English
Course Type	Service Courses Taken From Other Departments
Course Level	Bachelor’s Degree (First Cycle)
Mode of Delivery	Face To Face
Learning and Teaching Strategies	Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives	The objective of this course is to provide the basics of programming concepts using Python programming language and enable students to gain experience in laboratory environment.
Course Learning Outcomes	The students who succeeded in this course; Introduce concepts of programming Gain programming experience in laboratory environment Gain skills in algorithm development for problem solving
Course Content	The objective of this course is to provide the basics of programming concepts using Python programming language and enable students to gain experience in laboratory environment.

Weekly Subjects and Releated Preparation Studies

Week	Subjects	Preparation
1	Introduction to Computers and Programming	Chapter 1
2	Algorithm Development (pseudo code and flowchart)	Chapter 2
3	Input, Processing, and Output	Chapter 2
4	If and compound statements	Chapter 3
5	Nested decision structures	Chapter 3
6	Repetition and loop statements: While loop, For loop	Chapter 4
7	Repetition and loop statements: Nested loops	Chapter 4
8	Lists and Tuples	Chapter 7
9	Lists and Tuples	Chapter 7
10	Dictionaries	Chapter 9
11	Sets	Chapter 9
12	Functions	Chapter 5
13	Functions	Chapter 5
14	Review

Sources

Course Book	1. Tony Gaddis, “Starting Out with Python”, Pearson, 5th Edition, 2019.
Other Sources	2. "Python 3", Onur Sevli, Kodlab, 12.Baskı , 2023.

Evaluation System

Requirements	Number	Percentage of Grade
Attendance/Participation	-	-
Laboratory	2	20
Application	-	-
Field Work	-	-
Special Course Internship	-	-
Quizzes/Studio Critics	-	-
Homework Assignments	-	-
Presentation	-	-
Project	-	-
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	2	50
Final Exam/Final Jury	1	30
Toplam	5	100

Percentage of Semester Work	70
Percentage of Final Work	30
Total	100

Course Category

Core Courses
Major Area Courses
Supportive Courses	X
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	An ability to apply knowledge of mathematics, science, and engineering.
2	An ability to design and conduct experiments, as well as to analyze and interpret data.
3	An ability to design a system, component, or process to meet desired needs.
4	An ability to function on multi-disciplinary teams.
5	An ability to identify, formulate, and solve engineering problems.
6	An understanding of professional and ethical responsibility.
7	An ability to communicate effectively.
8	The broad education necessary to understand the impact of engineering solutions in a global and societal context.
9	Recognition of the need for, and an ability to engage in life-long learning.
10	Knowledge of contemporary issues.
11	An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.
12	Skills in project management and recognition of international standards and methodologies

ECTS/Workload Table

Activities	Number	Duration (Hours)	Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)	16	2	32
Laboratory	12	2	24
Application
Special Course Internship
Field Work
Study Hours Out of Class	16	2	32
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury	2	4	8
Prepration of Final Exams/Final Jury	1	4	4
Total Workload			100