Course title
M02280001
Introduction to Artificial Intelligence

 TROVATO GABRIELE
Course description
The course offers an introduction to Artificial Intelligence at a entry level that can be understood by students who are not familiar with programming. The course will cover the main Machine Learning techniques such as Neural Networks, and illustrate the ethical aspects of AI.
Purpose of class
Nowadays, Artificial Intelligence is entering our daily lives. The understanding of how it works, and the impacts on the society, is crucial in order to face the challenges that will come in the near future. This course gives the basic notions for this purpose.
Goals and objectives

 Goals and objectives Course Outcomes
1. Students can explain the theory behind AI and cognition
A-1
,
A-2
2. Students can explain the main techniques of Machine Learning
A-1
,
A-2
3. Students can explain the ethical aspects in AI
C
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Exam Group work active participation Total.
1. 16% 11% 7% 34%
2. 15% 11% 7% 33%
3. 15% 11% 7% 33%
Total. 46% 33% 21% -
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. History of AI Revise slides and other materials 190分
2. Agents, robots and cognition Revise slides and other materials 190分
3. Machine Learning types Revise slides and other materials 190分
4. Feature space Revise slides and other materials 190分
5. Classifiers Revise slides and other materials 190分
6. Neural Networks Revise slides and other materials 190分
7. Introduction to Deep Learning; Adversarial Learning Revise slides and other materials 190分
8. Introduction to Natural Language Processing Revise slides and other materials 100分
Group work 90分
9. Legal aspects in AI Revise slides and other materials 100分
Prepare for test 180分
Group work 90分
10. Machine Ethics Revise slides and other materials 60分
Prepare for test 140分
Group work 90分
11. Moral dilemmas Revise slides and other materials 60分
Prepare for test 140分
Group work 90分
12. Exam (quiz in computer room) and review Prepare group presentation 190分
13. Group work presentations (I) Evaluate other groups 20分
Prepare group presentation 170分
14. Group work presentations (I) Evaluate other groups 20分
Total. - - 2870分
Goals and objectives (Other Courses)
A:Fundamental Mechanical Engineering B:Advanced Mechanical Engineering C:Environment and Materials Engineering D:Chemistry and Biotechnology E:Electrical Engineering and Robotics G:Advanced Electronic Engineering F:Information and Communications Engineering L:Computer Science and Engineering H:Urban Infrastructure and Environment
Language
English
Evaluation method and criteria
Evaluation method: exam (46%), group work (33%), active participation (21%)
Criteria: at least 60% of total evaluation is required to pass.
The main exam consists in a quiz of True/False questions. The score is integrated by a group work, which is presented in the last weeks.
Active participation in class, such as in Q&A sessions, is also counted.
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback in the class
Textbooks and reference materials
Lectures' material provided in class (pdf). Reference: Ethem Alpaydin, Machine Learning. MIT Press. 2016
Prerequisites
None
Office hours and How to contact professors for questions
  • Office hours: Friday noon, by appointment (gabu@shibaura-it.ac.jp)
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
Active-learning course
More than one class is interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
Applicable Took part in videogame development, and seen how AI is conceived
[Firaxis Games]
Education related SDGs:the Sustainable Development Goals
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
Last modified : Tue Mar 18 04:06:41 JST 2025