FACULTY OF ENGINEERING

Department of Genetics and Bioengineering

SE 113 | Course Introduction and Application Information

Course Name
Introduction to Programming
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
SE 113
Spring
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
Lecture / 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 This course introduces the students to the fundamental concepts of programming using Python programming language.

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
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 exam 1. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 4.
8 Midterm exam.
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 Classes and objects: Defining classes. Severance, Python for Everybody: Exploring Data in Python 3, Chapter 14.
14 Lab quiz.
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
1
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
1
25
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
1
25
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
3
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
2
32
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
2
32
Study Hours Out of Class
14
6
84
Field Work
0
Quizzes / Studio Critiques
1
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
10
10
Final Exam
1
12
12
    Total
170

 

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 Genetics and Bioengineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

2

To be able to identify, define, formulate, and solve complex Genetics and Bioengineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Genetics and Bioengineering applications; to be able to use information technologies effectively.

X
5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Genetics and Bioengineering research topics.

6

To be able to work efficiently in Genetics and Bioengineering disciplinary and multi-disciplinary teams; to be able to work individually.

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 global and social impact of Genetics and Bioengineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Genetics and Bioengineering solutions.

9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in Genetics and Bioengineering applications.

10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Genetics and Bioengineering, and to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language 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 Genetics and Bioengineering.

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

 


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