Course title
Y01560003
Artificial Intelligence

 UCHIDA Kaoru
Middle-level Diploma Policy (mDP)
Program / Major mDP Goals
Department of Design Engineering E 専門分野の知識・技術を継続的・自主的に修得して、意匠・設計力を身に付け、それらを応用して課題を解決できる。
Purpose of class
To understand fundamentals of the artificial intelligence and experience practical machine leraning through Python programming.
Course description
Artificial intelligence; from fundamental classical techniques to up-to-date machine leraning techniques
Goals and objectives
  1. To Understand fundamentals of artificial intelligence
  2. to understand machine leraning and to apply it for simple applications
  3. To improve Python programing skills
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 ものづくりの場で応用して課題を解決できる。 Total.
1. 100% 100%
Total. 100% -
Evaluation method and criteria
Submitted reports and programming outcomes: 100%. When the score is more than 60 pts, the unit of this lecture is approved.
Language
Japanese(English accepted)
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. What is Aritificial Intelligence?
Its history 		Learn about airtificial intelligence and its history 90minutes
2. Search Learn problem solving by search 90minutes
3. Basic search algorithms Learn basic search algorithms and the lecture contents of the last time 90minutes
4. Advanced search algorithms Learn advanced search algorithms and the lecture contents of the last time 90minutes
5. Application of search techniques Learn applications of search techniques and the lecture contents of the last time 90minutes
6. Machine leraning Learn machine lerning and the lecture contents of the last time 90minutes
7. Classification Learn classification and the lecture contents of the last time 90minutes
8. Application of classification Learn classification applications and the lecture contents of the last time 90minutes
9. Regression Learn regression and the lecture contents of the last time 90minutes
10. Unsupervised learning Learn unsupervised learning and the lecture contents of the last time 90minutes
11. Application of unsupervised learning Learn unsupervised learning applications and the lecture contents of the last time 90minutes
12. Machine leraning applications Learn machine learning applications and the lecture contents of the last time 90minutes
13. Future of Artificial Intelligence Learn future of artificial intelligence and the lecture contents of the last time 90minutes
14. Summary Learn the overall of artificial intelligence and the lecture contents of the last time 90minutes
Total. - - 1260minutes
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback in the class
Textbooks and reference materials
人工知能入門，小高知宏，共立出版
ゼロから作るDeep Learning ―Pythonで学ぶディープラーニングの理論と実装, 斎藤 康毅 著，O’Reilly

Bring youe own notebook PC for in-class programming
Prerequisites
Office hours and How to contact professors for questions
  • Meet at the time of the lecture the end of the question
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
  • Course that cultivates a basic self-management skills
  • Course that cultivates a basic problem-solving skills
Active-learning course
Most classes are interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
Applicable The instructor has experience of practicing and teaching the contents of this lecture in business and other universities.
Education related SDGs:the Sustainable Development Goals
  • 3.GOOD HEALTH AND WELL-BEING
  • 4.QUALITY EDUCATION
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
  • 13.CLIMATE ACTION
Last modified : Wed Apr 29 10:54:12 JST 2026