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 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
1 2 3 4 5
1 Has the ability to apply scientific knowledge gained in the undergraduate education and to expand and extend knowledge in the same or in a different area
2 Can apply gained knowledge and problem solving abilities in inter-disciplinary research
3 Has the ability to work independently within research area, to state the problem, to develop solution techniques, to solve the problem, to evaluate the obtained results and to apply them when necessary
4 Takes responsibility individually and as a team member to improve systematic approaches to produce solutions in unexpected complicated situations related to the area of study
5 Can develop strategies, implement plans and principles on the area of study and can evaluate obtained results within the framework X
6 Can develop and extend the knowledge in the area and to use them with scientific, social and ethical responsibility
7 Has the ability to follow recent developments within the area of research, to support research with scientific arguments and data, to communicate the information on the area of expertise in a systematically by means of written report and oral/visual presentation
8 To have an oral and written communication ability in at least one of the common foreign languages ("European Language Portfolio Global Scale", Level B2)
9 Has software and hardware knowledge in the area of expertise, and has proficient information and communication technology knowledge
10 Follows scientific, cultural, and ethical criteria in collecting, interpreting and announcing data in the research area and has the ability to teach.
11 Has professional ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications.

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