KA237001 Informatics and Data Science Exercise III（Computer Science Program）

Hiroshima University Syllabus

Japanese

Academic Year 2024Year School/Graduate School School of Informatics and Data Science

Lecture Code KA237001 Subject Classification Specialized Education

Subject Name 情報科学演習III（計算機科学プログラム）

Subject Name
（Katakana）ジョウホウカガクエンシュウ３（ケイサンキカガクプログラム）

Subject Name in
English Informatics and Data Science Exercise III（Computer Science Program）

Instructor KONDO TOHRU

Instructor
(Katakana) コンドウ　トオル

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

Days, Periods, and Classrooms (3T) Mon5-7：IMC-Main 2F PC Rm

Lesson Style Seminar Lesson Style
(More Details) 　

Exercise

Credits 1.0 Class Hours/Week 　 Language of Instruction B : Japanese／English

Course Level 3 : Undergraduate High-Intermediate

Course Area（Area） 25 : Science and Technology

Course Area（Discipline） 02 : Information Science

Eligible Students

Keywords Programing, IoT, Digital circuit design

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）
・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.
・D3. Knowledge of hardware and software and programming ability to process data efficiently.

Data Science Program
（Knowledge and Understanding）
・D1. Knowledge and ability to understand the theoretical framework of statistics and data analysis and to analyze qualitative/quantitative information of big data accurately and efficiently.
（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.
（Comprehensive Abilities）
・D3. Ability to grasp complexly intertwined social needs and issues from a bird's-eye view and solve issues with a multifaceted perspective and analytical ability based on a wide range of knowledge in intelligent science.

Class Objectives
/Class Outline This exercise will includes two themes based on the knowledge learned through Informatics and data science, Exercises I-II.  The goal is to acquire the ability to find a solution to a given exercise or problem, address it, and report the results.

Class Schedule Lesson1   Guidance

Lesson2 to Lesson7
　Hands on exercises on two different topics, three weeks each.

* Topic1: IoT exercise by the Raspberry Pi
    1. Setup Raspberry Pi and learning the basic usage of Raspberry Pi.
    2. Visualize sensor data through a web server.
    3. Control embedded system using GPIO interface

* Topic2: Digital Circuit Design
    1. Combinational Circuit design, Verilog HDL and FPGA Programming.
    2. Flip-Flops, Counters and Digit 7-segment display.
    3. Counters and Chattering removal.

Lesson 8  Examination

Text/Reference
Books,etc. handouts

PC or AV used in
Class,etc. 　

(More Details) handouts, PC (including BYOD)

Learning techniques to be incorporated 　

Suggestions on
Preparation and
Review   (Topic1) IoT exercise by the Raspberry Pi
    You can use Raspberry Pi only during exercises, so it is difficult to prepare and learn by yourself. Handouts will be provided in advance, so read carefully before class and prepare for the day of the exercise.

Requirements

Grading Method Evaluated by reports and examinations.

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	2024Year	School/Graduate School	School of Informatics and Data Science
Lecture Code	KA237001	Subject Classification	Specialized Education
Subject Name	情報科学演習III（計算機科学プログラム）
Subject Name （Katakana）	ジョウホウカガクエンシュウ３（ケイサンキカガクプログラム）
Subject Name in English	Informatics and Data Science Exercise III（Computer Science Program）
Instructor	KONDO TOHRU
Instructor (Katakana)	コンドウ　トオル
Campus	Higashi-Hiroshima	Semester/Term	3rd-Year, Second Semester, 3Term
Days, Periods, and Classrooms	(3T) Mon5-7：IMC-Main 2F PC Rm
Lesson Style	Seminar	Lesson Style (More Details)
Exercise
Credits	1.0	Class Hours/Week		Language of Instruction	B : Japanese／English
Course Level	3 : Undergraduate High-Intermediate
Course Area（Area）	25 : Science and Technology
Course Area（Discipline）	02 : Information Science
Eligible Students
Keywords	Programing, IoT, Digital circuit design
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）・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. ・D3. Knowledge of hardware and software and programming ability to process data efficiently. Data Science Program （Knowledge and Understanding）・D1. Knowledge and ability to understand the theoretical framework of statistics and data analysis and to analyze qualitative/quantitative information of big data accurately and efficiently. （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. （Comprehensive Abilities）・D3. Ability to grasp complexly intertwined social needs and issues from a bird's-eye view and solve issues with a multifaceted perspective and analytical ability based on a wide range of knowledge in intelligent science.
Class Objectives /Class Outline	This exercise will includes two themes based on the knowledge learned through Informatics and data science, Exercises I-II. The goal is to acquire the ability to find a solution to a given exercise or problem, address it, and report the results.
Class Schedule	Lesson1 Guidance Lesson2 to Lesson7 　Hands on exercises on two different topics, three weeks each. * Topic1: IoT exercise by the Raspberry Pi 1. Setup Raspberry Pi and learning the basic usage of Raspberry Pi. 2. Visualize sensor data through a web server. 3. Control embedded system using GPIO interface * Topic2: Digital Circuit Design 1. Combinational Circuit design, Verilog HDL and FPGA Programming. 2. Flip-Flops, Counters and Digit 7-segment display. 3. Counters and Chattering removal. Lesson 8 Examination
Text/Reference Books,etc.	handouts
PC or AV used in Class,etc.
(More Details)	handouts, PC (including BYOD)
Learning techniques to be incorporated
Suggestions on Preparation and Review	(Topic1) IoT exercise by the Raspberry Pi You can use Raspberry Pi only during exercises, so it is difficult to prepare and learn by yourself. Handouts will be provided in advance, so read carefully before class and prepare for the day of the exercise.
Requirements
Grading Method	Evaluated by reports and examinations.
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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