Computer Programming (CMPE102) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Computer Programming CMPE102 2. Semester 2 2 0 3 4
Pre-requisite Course(s)
N/A
Course Language English
Course Type Compulsory Departmental Courses
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
1 2 3 4 5
1 An ability to apply knowledge in mathematics and basic sciences and computational skills to solve manufacturing engineering problems X
2 An ability to define and analyze issues related with manufacturing technologies X
3 An ability to develop a solution based approach and a model for an engineering problem and design and manage an experiment
4 An ability to design a comprehensive manufacturing system based on creative utilization of fundamental engineering principles while fulfilling sustainability in environment and manufacturability and economic constraints
5 An ability to chose and use modern technologies and engineering tools for manufacturing engineering applications
6 An ability to utilize information technologies efficiently to acquire datum and analyze critically, articulate the outcome and make decision accordingly X
7 An ability to attain self-confidence and necessary organizational work skills to participate in multi-diciplinary and interdiciplinary teams as well as act individually
8 An ability to attain efficient communication skills in Turkish and English both verbally and orally X
9 An ability to reach knowledge and to attain life-long learning and self-improvement skills, to follow recent advances in science and technology X
10 An awareness and responsibility about professional, legal, ethical and social issues in manufacturing engineering
11 An awareness about solution focused project and risk management, enterpreneurship, innovative and sustainable development
12 An understanding on the effects of engineering applications on health, social and legal aspects at universal and local level during decision making process

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