| Academic Year |
2025Year |
School/Graduate School |
Liberal Arts Education Program |
| Lecture Code |
30840001 |
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法夜,1経夜] |
Subject Name (Katakana) |
|
Subject Name in English |
Starting Programming from Scratch |
| Instructor |
FUKUSHIMA MAKOTO |
Instructor (Katakana) |
フクシマ マコト |
| Campus |
Higashi-Senda |
Semester/Term |
1st-Year, Second Semester, Second Semester |
| Days, Periods, and Classrooms |
(2nd) Mon13-14:Online |
| Lesson Style |
Lecture |
Lesson Style (More Details) |
Online (on-demand) |
| Online (on-demand style) lectures |
| Credits |
2.0 |
Class Hours/Week |
2 |
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 |
Programing, Python |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status within Liberal Arts Education | Participants will learn the basics of Python programming knowledge and skills. |
|---|
| Expected Outcome | 1. To understand the basic concepts of programming. 2. To acquire the skills to perform simple programming using Python. |
Class Objectives /Class Outline |
The objectives of this course are to understand the basic concepts of programming and to acquire the skills to perform simple programming using Python. |
| Class Schedule |
Lesson1: Class Orientation/How to Use Google Colaboratory Lesson2: Variables and Types (Lecture) Lesson3: Variables and Types (Exercises) Lesson4: Conditions (Lecture) Lesson5: Conditions (Exercises) Lesson6: Loops (Lecture) Lesson7: Loops (Exercises) Lesson8: Functions (Lecture) Lesson9: Functions (Exercises) Lesson10: Classes (Lecture) Lesson11: Classes (Exercises) Lesson12: An Introduction to Data Analysis (Lecture) Lesson13: An Introduction to Data Analysis (Exercises) Lesson14: An Introduction to Machine Learning (Lecture) Lesson15: An Introduction to Machine Learning (Exercises) |
Text/Reference Books,etc. |
Lecture materials and videos will be provided. |
PC or AV used in Class,etc. |
Microsoft Teams, Other (see [More Details]) |
| (More Details) |
Google Colaboratory is used for Python programming. Information on how to access lecture materials and videos will be posted on the class bulletin board. |
| Learning techniques to be incorporated |
|
Suggestions on Preparation and Review |
Use lecture materials and videos for review. |
| Requirements |
Participants must have their own Google account to use Google Colaboratory. |
| Grading Method |
Evaluation is based on the grades for the assignments required to be submitted. |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
This course is designed for students who are new to programming. A few data science topics are also covered at the end of the course. |
| 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. |