K5318010 Engineering Computer Programming

Hiroshima University Syllabus

Japanese

Academic Year 2026Year School/Graduate School School of Engineering

Lecture Code K5318010 Subject Classification Specialized Education

Subject Name 工学プログラミング応用

Subject Name
（Katakana）コウガクプログラミングオウヨウ

Subject Name in
English Engineering Computer Programming

Instructor CHEN CHEN,SAKUNO YUJI

Instructor
(Katakana) チン　シン,サクノ　ユウジ

Campus Higashi-Hiroshima Semester/Term 3rd-Year,  First Semester,  2Term

Days, Periods, and Classrooms (2T) Weds5-8：ENG 220

Lesson Style Lecture Lesson Style
(More Details) Face-to-face, Online (on-demand)

Basically face-to-face (in certain cases, some lessons will be conducted on-demand). Exercise using indispensable PC.

Credits 2.0 Class Hours/Week 4 Language of Instruction B : Japanese／English

Course Level 3 : Undergraduate High-Intermediate

Course Area（Area） 25 : Science and Technology

Course Area（Discipline） 10 : Integrated Engineering

Eligible Students

Keywords SDG_09, Programming, Data Processing, Python, Windows

Special Subject for Teacher Education 　 Special Subject 　

Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) This course relates to the evaluation item in the Education Program of for Transportation Systems Engineering.
-Knowledge and Understanding (3): To acquire understanding and basic knowledge required for engineers and researchers.
-Abilities and Skills (3): Information processing ability based on mathematics and mechanics.
Related cources
- Fundamental course: Introduction to Information and Data Sciencies, Basic Engineering Computer Programming, Calculus, Linear Algebra, General Mechanics
- Application course: Graduation Thesis.
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) Program of Transportation Systems
（Knowledge and Understanding）
・Information engineering subjects: To acquire understanding and basic knowledge required for engineers and researchers.
（Abilities and Skills）
・Information engineering subjects: Information processing ability based on mathematics and mechanics.

Class Objectives
/Class Outline The objective of this class is to learn programming techniques, which are the basis of computer simulation technology and data science technology, which are indispensable for the development and design of transportation equipment such as ships, aircraft, and automobiles, and for the evaluation of energy and environmental problems, through lectures and exercises.

Class Schedule lesson1 Guidance & development environment (VS Code, Jupyter, virtual environments)
lesson2 Python fundamentals (1): variables, data types, operators, and conditional branching
lesson3 Python fundamentals (2): loops and function basics
lesson4 I/O fundamentals: text and CSV input/output
lesson5 Function design and modular programming
lesson6 Exception handling, logging, and debugging
lesson7 Midterm test
lesson8 Mathematical computing: NumPy library
lesson9 Data visualization: Matplotlib library
lesson10 DataFrames: pandas library
lesson11 Data analysis: time series
lesson12 Data analysis: statistics
lesson13 Fundamentals of image processing
lesson14 Applications of image processing
lesson15 Fundamentals and applications of AI processing

Text/Reference
Books,etc. Handouts will be provided as text, which will be distributed electronically via moodle. No specific reference books are specified, but it is recommended to prepare a reference book each for the Python languages. Reference books will be introduced in the lectures as necessary.

PC or AV used in
Class,etc. Text, Handouts, Microsoft Teams, Microsoft Stream, moodle

(More Details) Text, PC, handouts, lecture video and others
Handouts (pdf files of power point and the related contents) are distributed using moodle. URL of lecture video for on-demand lecture (if it will be done) also will be announced at moodle.

Learning techniques to be incorporated Quizzes/ Quiz format, Post-class Report

Suggestions on
Preparation and
Review Preparation and review of each lecture  is required. Practical programming exercise using your own computer is also important.

Requirements It is necessary to install the programming environment using the Python languages on the indispensable PCs according to the prior instructions (Momiji, moodle).　

Grading Method Reports and mini-test (~50%), term-end examination(~50%) -> 60% or more in total is required. The style of term-end-examination will be announced later.

Practical Experience

Summary of Practical Experience and Class Contents based on it

Message Students who attend less than 2/3 of the lessons will be graded as absent. Note that attendance may not be counted depending on the tardiness or early dismissal of students.

Other

Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching.

Academic Year	2026Year	School/Graduate School	School of Engineering
Lecture Code	K5318010	Subject Classification	Specialized Education
Subject Name	工学プログラミング応用
Subject Name （Katakana）	コウガクプログラミングオウヨウ
Subject Name in English	Engineering Computer Programming
Instructor	CHEN CHEN,SAKUNO YUJI
Instructor (Katakana)	チン　シン,サクノ　ユウジ
Campus	Higashi-Hiroshima	Semester/Term	3rd-Year, First Semester, 2Term
Days, Periods, and Classrooms	(2T) Weds5-8：ENG 220
Lesson Style	Lecture	Lesson Style (More Details)	Face-to-face, Online (on-demand)
Basically face-to-face (in certain cases, some lessons will be conducted on-demand). Exercise using indispensable PC.
Credits	2.0	Class Hours/Week	4	Language of Instruction	B : Japanese／English
Course Level	3 : Undergraduate High-Intermediate
Course Area（Area）	25 : Science and Technology
Course Area（Discipline）	10 : Integrated Engineering
Eligible Students
Keywords	SDG_09, Programming, Data Processing, Python, Windows
Special Subject for Teacher Education		Special Subject
Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students)	This course relates to the evaluation item in the Education Program of for Transportation Systems Engineering. -Knowledge and Understanding (3): To acquire understanding and basic knowledge required for engineers and researchers. -Abilities and Skills (3): Information processing ability based on mathematics and mechanics. Related cources - Fundamental course: Introduction to Information and Data Sciencies, Basic Engineering Computer Programming, Calculus, Linear Algebra, General Mechanics - Application course: Graduation Thesis.
Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students)	Program of Transportation Systems （Knowledge and Understanding）・Information engineering subjects: To acquire understanding and basic knowledge required for engineers and researchers. （Abilities and Skills）・Information engineering subjects: Information processing ability based on mathematics and mechanics.
Class Objectives /Class Outline	The objective of this class is to learn programming techniques, which are the basis of computer simulation technology and data science technology, which are indispensable for the development and design of transportation equipment such as ships, aircraft, and automobiles, and for the evaluation of energy and environmental problems, through lectures and exercises.
Class Schedule	lesson1 Guidance & development environment (VS Code, Jupyter, virtual environments) lesson2 Python fundamentals (1): variables, data types, operators, and conditional branching lesson3 Python fundamentals (2): loops and function basics lesson4 I/O fundamentals: text and CSV input/output lesson5 Function design and modular programming lesson6 Exception handling, logging, and debugging lesson7 Midterm test lesson8 Mathematical computing: NumPy library lesson9 Data visualization: Matplotlib library lesson10 DataFrames: pandas library lesson11 Data analysis: time series lesson12 Data analysis: statistics lesson13 Fundamentals of image processing lesson14 Applications of image processing lesson15 Fundamentals and applications of AI processing
Text/Reference Books,etc.	Handouts will be provided as text, which will be distributed electronically via moodle. No specific reference books are specified, but it is recommended to prepare a reference book each for the Python languages. Reference books will be introduced in the lectures as necessary.
PC or AV used in Class,etc.	Text, Handouts, Microsoft Teams, Microsoft Stream, moodle
(More Details)	Text, PC, handouts, lecture video and others Handouts (pdf files of power point and the related contents) are distributed using moodle. URL of lecture video for on-demand lecture (if it will be done) also will be announced at moodle.
Learning techniques to be incorporated	Quizzes/ Quiz format, Post-class Report
Suggestions on Preparation and Review	Preparation and review of each lecture is required. Practical programming exercise using your own computer is also important.
Requirements	It is necessary to install the programming environment using the Python languages on the indispensable PCs according to the prior instructions (Momiji, moodle).
Grading Method	Reports and mini-test (~50%), term-end examination(~50%) -> 60% or more in total is required. The style of term-end-examination will be announced later.
Practical Experience
Summary of Practical Experience and Class Contents based on it
Message	Students who attend less than 2/3 of the lessons will be graded as absent. Note that attendance may not be counted depending on the tardiness or early dismissal of students.
Other
Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching.

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