COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Introduction to Programming
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
SE 113
Fall
2
2
3
6
Prerequisites
None
Course Language
English
Course Type
Required
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Problem Solving
Q&A
Application: Experiment / Laboratory / Workshop
Lecturing / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives The main objective of this course is to provide the students with basic skills of programming. Python programming language will be used. Topics include the following concepts: fundamental types, variables, statements, control flow structures, functions, file operations and classes.
Learning Outcomes The students who succeeded in this course;
  • Will be able to develop programs in Python programming language.
  • Will be able to use control structures (decision and loop statements) in Python language.
  • Will be able to design functions in Python language.
  • Will be able to use several data structures (strings, lists, dictionaries) in Python language.
  • Will be able to handle file input/output operations using Python programming language.
  • Will be able to define classes using Python programming language
Course Description Course Content This course introduces the students to the fundamental concepts of programming using Python programming language.
Related Sustainable Development Goals

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction to programming in Python. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 1.
2 Fundamental data types, constants, variables, operators; LAB#1. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 2.
3 Input statements, algorithm, pseudocode; LAB#2. Severance, Python for Everybody: Exploring Data in Python 3, Chapters 3 and 5.
4 Flow control: Conditional execution; LAB#3. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 3.
5 Flow control: Loop/repetition statements, for, while; LAB#4. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 5.
6 Flow control: Nested loops, break, continue; LAB#5. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 5.
7 Functions; LAB#6, Midterm 1. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 4.
8 Character Strings. Severance, Python for Everybody: Exploring Data in Python 3, Ünite 6
9 Lists; LAB#7. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 8.
10 Dictionaries; LAB#8. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 9.
11 File handling: Input/output operations; LAB#9. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 7.
12 Classes and objects: Using objects; LAB#10. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 14.
13 Midterm 2.
14 Classes and objects: Defining classes. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 14.
15 Review
16 Final Exam
Course Notes/Textbooks

Python for Everybody: Exploring Data in Python 3, Charles Severance, CreateSpace Independent Publishing Platform, 978-1530051120

Suggested Readings/Materials

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
15
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
2
50
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
18
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
2
32
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
2
Study Hours Out of Class
14
6
84
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
2
10
Final Exams
1
12
    Total
180

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Industrial Engineering; to be able to use theoretical and applied information in these areas to model and solve Industrial Engineering problems.

X
2

To be able to identify, formulate and solve complex Industrial Engineering problems by using state-of-the-art methods, techniques and equipment; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to analyze a complex system, process, device or product, and to design with realistic limitations to meet the requirements using modern design techniques. 

X
4

To be able to choose and use the required modern techniques and tools for Industrial Engineering applications; to be able to use information technologies efficiently.

X
5

To be able to design and do simulation and/or experiment, collect and analyze data and interpret the results for investigating Industrial Engineering problems and Industrial Engineering related research areas.

X
6

To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually.

X
7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively; to be able to give and receive clear and comprehensible instructions

8

To have knowledge about contemporary issues and the global and societal effects of Industrial Engineering practices on health, environment, and safety; to be aware of the legal consequences of Industrial Engineering solutions.

9

To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice.

X
10

To have knowledge about business life practices such as project management, risk management, and change management; to be aware of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Industrial Engineering.

X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest