KA240901 Advanced Programming

Hiroshima University Syllabus

Japanese

Academic Year 2025Year School/Graduate School School of Informatics and Data Science

Lecture Code KA240901 Subject Classification Specialized Education

Subject Name アドバンスドプログラミング

Subject Name
（Katakana）アドバンスドプログラミング

Subject Name in
English Advanced Programming

Instructor VICTOR PARQUE

Instructor
(Katakana) ヴィクター　パルケ

Campus Higashi-Hiroshima Semester/Term 3rd-Year, Second Semester, Intensive

Days, Periods, and Classrooms (Int) Inte

Lesson Style Lecture Lesson Style
(More Details) Face-to-face

Credits 2.0 Class Hours/Week 　 Language of Instruction J : Japanese

Course Level 3 : Undergraduate High-Intermediate

Course Area（Area） 25 : Science and Technology

Course Area（Discipline） 02 : Information Science

Eligible Students 3rd year student, School of Informatics and Data Science

Keywords WebAPI, HTTP, OpenAPI, Python, Linux, supercomputers, HPC, high-performance computing, system software

Special Subject for Teacher Education 　 Special Subject 　

Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students)
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) Computer Science Program
（Abilities and Skills）
・D3. Knowledge of hardware and software and programming ability to process data efficiently.

Data Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.

Intelligence Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.

Class Objectives
/Class Outline * Exercises on the design and implementation of WebAPI (first half)
An API (Application Programming Interface) is an interface for programs to call information and functions from each other, of which Web API generally refers to a web service on the Internet that provides functions to users. In this lecture, students learn the design of Web APIs and gain practical programming skills by implementing them in exercises.
* Exercises on large-scale parallel computing and AI application technology (second half)
This lecture explains the fundamental software technology for large-scale parallel computing at Fujitsu, and provides practical exercises on development techniques utilising AI and LLM to support timely research and development.

Class Schedule Lesson 1 Guidance
Lesson 2 Web API overview
Lesson 3 Designing endpoint response data models
Lesson 4 Security of Web API
Lesson 5 OpenAPI and Web API development framework (Flask-RESTX will be used)
Lesson 6 Web API programming exercises
Lesson 7 Web API programming exercises
Lesson 8 8th Web API programming exercise
Lesson 9 Outline of supercomputers
Lesson 10 Configuration of high-performance computing cluster (HPC) systems
Lesson 11 Large-scale AI and supercomputers
Lesson 12 System software supporting supercomputers
Lesson 13 System software programming exercises
Lesson 14 System software programming exercises
Lesson 15 System software programming exercises

Report

Text/Reference
Books,etc. Handouts

PC or AV used in
Class,etc. Handouts, moodle

(More Details)

Learning techniques to be incorporated

Suggestions on
Preparation and
Review Knowledge of basic Linux operation, development environment (Visual Studio Code recommended), Python and C programming is desirable.

Requirements This class will be held on weekends in December and January. Details will be posted on Momiji as soon as they are fixed.

Grading Method Grades are determined comprehensively by exercises and reports.

Practical Experience

Summary of Practical Experience and Class Contents based on it

Message

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	2025Year	School/Graduate School	School of Informatics and Data Science
Lecture Code	KA240901	Subject Classification	Specialized Education
Subject Name	アドバンスドプログラミング
Subject Name （Katakana）	アドバンスドプログラミング
Subject Name in English	Advanced Programming
Instructor	VICTOR PARQUE
Instructor (Katakana)	ヴィクター　パルケ
Campus	Higashi-Hiroshima	Semester/Term	3rd-Year, Second Semester, Intensive
Days, Periods, and Classrooms	(Int) Inte
Lesson Style	Lecture	Lesson Style (More Details)	Face-to-face

Credits	2.0	Class Hours/Week		Language of Instruction	J : Japanese
Course Level	3 : Undergraduate High-Intermediate
Course Area（Area）	25 : Science and Technology
Course Area（Discipline）	02 : Information Science
Eligible Students	3rd year student, School of Informatics and Data Science
Keywords	WebAPI, HTTP, OpenAPI, Python, Linux, supercomputers, HPC, high-performance computing, system software
Special Subject for Teacher Education		Special Subject
Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students)
Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students)	Computer Science Program （Abilities and Skills）・D3. Knowledge of hardware and software and programming ability to process data efficiently. Data Science Program （Abilities and Skills）・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value. ・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis. Intelligence Science Program （Abilities and Skills）・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value. ・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.
Class Objectives /Class Outline	* Exercises on the design and implementation of WebAPI (first half) An API (Application Programming Interface) is an interface for programs to call information and functions from each other, of which Web API generally refers to a web service on the Internet that provides functions to users. In this lecture, students learn the design of Web APIs and gain practical programming skills by implementing them in exercises. * Exercises on large-scale parallel computing and AI application technology (second half) This lecture explains the fundamental software technology for large-scale parallel computing at Fujitsu, and provides practical exercises on development techniques utilising AI and LLM to support timely research and development.
Class Schedule	Lesson 1 Guidance Lesson 2 Web API overview Lesson 3 Designing endpoint response data models Lesson 4 Security of Web API Lesson 5 OpenAPI and Web API development framework (Flask-RESTX will be used) Lesson 6 Web API programming exercises Lesson 7 Web API programming exercises Lesson 8 8th Web API programming exercise Lesson 9 Outline of supercomputers Lesson 10 Configuration of high-performance computing cluster (HPC) systems Lesson 11 Large-scale AI and supercomputers Lesson 12 System software supporting supercomputers Lesson 13 System software programming exercises Lesson 14 System software programming exercises Lesson 15 System software programming exercises Report
Text/Reference Books,etc.	Handouts
PC or AV used in Class,etc.	Handouts, moodle
(More Details)
Learning techniques to be incorporated
Suggestions on Preparation and Review	Knowledge of basic Linux operation, development environment (Visual Studio Code recommended), Python and C programming is desirable.
Requirements	This class will be held on weekends in December and January. Details will be posted on Momiji as soon as they are fixed.
Grading Method	Grades are determined comprehensively by exercises and reports.
Practical Experience
Summary of Practical Experience and Class Contents based on it
Message
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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