Department of Global and Interdisciplinary Studies

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MAN300ZA(経営学 / Management 300)
Impact of Artificial Intelligence

Maymay HO

Class code etc
Faculty/Graduate school Department of Global and Interdisciplinary Studies
Attached documents
Year 2022
Class code A6329
Previous Class code
Previous Class title
Term 春学期授業/Spring
Day/Period 水3/Wed.3
Class Type
Campus 市ヶ谷 / Ichigaya
Classroom name 各学部・研究科等の時間割等で確認
Grade 3~4
Credit(s) 2
Open Program
Open Program (Notes)
Global Open Program
Interdepartmental class taking system for Academic Achievers
Interdepartmental class taking system for Academic Achievers (Notes) 制度ウェブサイトの3.科目別の注意事項 (1) GIS主催科目の履修上の注意を参照すること。
Class taught by instructors with practical experience
Urban Design CP
Diversity CP
Learning for the Future CP
Carbon Neutral CP
Chiyoda Campus Consortium
Duplicate Subjects Taken Under Previous Class Title
Category (commenced 2024 onwards)
Category (commenced 2020-2023)
Category (commenced 2016-2019)

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Outline and objectives

Artificial Intelligence (AI) has a profound impact on the business world in many ways, changing the way cities are run, the way we live and socialise through to the way we do business. This course focuses on how businesses use AI to make their businesses more profitable and customer experience better. In case-studies we will cover during this course we will analyse the impact and thereby also understanding businesses better. We will also observe that businesses employ data scientists to analyse data. These scientists use machine learning as part of their implementation of AI. So in the later part of the course we will delve deeper into Machine Learning so that we can better understand what data scientists do. Hence we are able to understand the “mechanics” of AI.


Using the critical thinking exercises and class discussions, students will be able to apply their knowledge to case-studies and group work. The skills they acquire through this course should prepare them to understand key technical terms and give a better understanding of the world.

Which item of the diploma policy will be obtained by taking this class?

Will be able to gain “DP 1”, “DP 2”, “DP 3”, and “DP 4”.

Default language used in class

英語 / English

Method(s)(学期の途中で変更になる場合には、別途提示します。 /If the Method(s) is changed, we will announce the details of any changes. )

At the beginning of class, feedback for the previous class is given using some comments from submitted reaction papers. Method of instruction will be a mixture of lecture, group presentation and discussions.

Submission of assignments and feedback will be via the Learning Management System.

Active learning in class (Group discussion, Debate.etc.)

あり / Yes

Fieldwork in class

なし / No


授業形態/methods of teaching:対面/face to face



Introduction to Artificial Intelligence.

2[対面/face to face]:Robotics in Business

Introduction to Robotics in Business.

3[対面/face to face]:AI to Improve Customer Experience

Discuss on how AI improves customer experience.

4[対面/face to face]:AI to Allow Entrepreneurship

Discuss on how AI encourages entrepreneurship.

5[対面/face to face]:Review of Class Materials

Review of class materials.

6[対面/face to face]:AI to Drive Business Performance

Discuss how AI drives business performance.

7[対面/face to face]:AI in Healthcare

Discuss how AI drives in healthcare industry.

8[対面/face to face]:Hacking, Fraud and Cybercrime

Discuss the impact on hacking, fraud and cybercrime.

9[対面/face to face]:Machine Learning In Business and Regression Revisited

Revise the regression. Discuss machine learning in business.

10[対面/face to face]:Hands on Demonstration of R Language

Perform demonstration of R language.

11[対面/face to face]:Hands on Demonstration on Microsoft Machine Learning

Perform demonstration on microsoft machine learning.

12[対面/face to face]:AI and Current Affairs

Discuss AI and current affairs.

13[対面/face to face]:Discussion and Review

Discussion and review.

14[対面/face to face]:Wrap-up & Review of Class Materials.

Review of Class Materials.

Work to be done outside of class (preparation, etc.)

Students are expected to read the assigned readings and slides of the next class before each class. Also, in addition to the preparation for the final presentation, there will be homework during the course. Preparatory study and review time for this class are 2 hours each. Additional reading on the daily news and related research articles are highly recommended.


Electronic slides will be provided.


References will be provided in class slides.

Grading criteria

15% Quizzes
15% Projects / homework
35% Midterm exam
35% Final examination

Changes following student comments


Equipment student needs to prepare