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 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 Knowledge of mathematics, natural sciences, engineering fundamentals, computing, and topics specific to the relevant engineering discipline; the ability to use this knowledge in the solution of complex engineering problems. X
2 The ability to identify, formulate, and analyze complex engineering problems using knowledge of basic sciences, mathematics, and engineering, and considering the UN Sustainable Development Goals relevant to the problem. X
3 The ability to design creative solutions for complex engineering problems; the ability to design complex systems, processes, devices, or products to meet current and future requirements, considering realistic constraints and conditions.
4 The ability to select and use appropriate techniques, resources, and modern engineering and IT tools, including prediction and modeling, for the analysis and solution of complex engineering problems, with an awareness of their limitations. X
5 The ability to use research methods for the investigation of complex engineering problems, including literature search, designing and conducting experiments, collecting data, and analyzing and interpreting results.
6 Knowledge of the effects of engineering practices on society, health and safety, the economy, sustainability, and the environment within the scope of the UN Sustainable Development Goals; awareness of the legal consequences of engineering solutions.
7 Acting in accordance with engineering professional principles, knowledge of ethical responsibility; awareness of acting impartially without discrimination on any grounds and being inclusive of diversity. X
8 The ability to work effectively individually and in intra-disciplinary and multi-disciplinary teams (face-to-face, remote, or hybrid) as a team member or leader. X
9 "The ability to communicate effectively orally and in writing on technical topics, considering the various differences of the target audience (such as education, language, profession).
10 Knowledge of practices in business life such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation.
11 The ability to engage in life-long learning, including independent and continuous learning, adapting to new and emerging technologies, and thinking inquisitively regarding technological changes.

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