Hiroshima University Syllabus

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Academic Year 2024Year School/Graduate School Liberal Arts Education Program
Lecture Code 30106004 Subject Classification Information and Data Science Courses
Subject Name ゼロからはじめるプログラミング[1教造]
Subject Name
Subject Name in
Starting Programming from Scratch
アイザワ ヒロアキ,フルイ アキラ
Campus Higashi-Hiroshima Semester/Term 1st-Year,  Second Semester,  3Term
Days, Periods, and Classrooms (3T) Weds1-4:Online
Lesson Style Lecture Lesson Style
(More Details)
Course materials of videos are provided.  
Credits 2.0 Class Hours/Week   Language of Instruction J : Japanese
Course Level 1 : Undergraduate Introductory
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 02 : Information Science
Eligible Students
Keywords Computer programming, Python, Data science, AI 
Special Subject for Teacher Education   Special Subject  
Class Status within
Liberal Arts Education
To equip students with the basic knowledge and skills necessary to use data in today’s advanced information society, develop their understanding of the usefulness and problems of computers and information-related ethical issues, so as to ensure the proper 
Expected Outcome1. To acquire basic knowledge, skills, and attitudes regarding information science and data science, and thereby to be able to process data and receive and send information appropriately.
2. To understand and be able to explain information ethics necessar 
Class Objectives
/Class Outline
The objective of this course is to learn the art of Python programming and knowledge and skills for using computers. At the same time, students are expected to improve their logical thinking and mathematical sense. We use Python programming language because it is easy to understand and recently used for AI and data science. 
Class Schedule Lesson1: Introduction
Lesson2: Variables (lecture)
Lesson3: Variables (exercise)
Lesson4: Conditional statements (lecture)
Lesson5: Conditional statements (exercise)
Lesson6: Loops (lecture)
Lesson7: Loops (exercise)
Lesson8: Functions (lecture)
Lesson9: Functions (exercise)
Lesson10: Classes (lecture)
Lesson11: Classes (exercise)
Lesson12: Introduction to data analysis (lecture)
Lesson13: Introduction to data analysis (exercise)
Lesson14: Introduction to machine learning (lecture)
Lesson15: Introduction to machine learning (exercise) 
Videos will be provided. 
PC or AV used in
(More Details) Google Colaboratory will be used for Python programming, Microsoft Stream for video streaming, and Microsoft Teams for answering questions and submitting assignments. Lecture materials and announcements will be centralized on support pages on GitHub Pages. 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Reading and understanding many good programs would be a best way of mastering programming skills. Do not hesitate to ask instructor or TA a question during exercises. Do not just understand the contents in your head, but actually write and run the program. 
Requirements A Google account is required to use Google Colaboratory. 
Grading Method Based on programming assignments in the exercise sessions (excluding advanced problems) and a final exam (online). 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
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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