2025 (Current Year) Special graduate degree programs Specially Offered Degree Programs for Graduate Students Center of Data Science and Artificial Intelligence 2

Applied Practical Data Science and Artificial Intelligence 3A

Academic unit or major: Center of Data Science and Artificial Intelligence
Instructor(s): Asako Kanezaki / Norio Tomii / Yoshihiro Miyake / Isao Ono / Katsumi Nitta / Kei Miyazaki / Keiji Okumura / Jun Sakuma / Takayoshi Yokota / Yutaro Tachibana / Akira Tajima / Sourish Chatterjee / Yusuke Motegi / Yukihiro Kawano / Yuya Kitade / Shinichi Nakano / Junya Morita / Sohei Arisaka
Class Format: Lecture (HyFlex)
Media-enhanced courses: -
Day of week/Period (Classrooms): 7-8 Tue (M-374(H131), G2-202(G221))
Class: -
Course Code: DSA.P431
Number of credits: 100
Course offered: 2025
Offered quarter: 3Q
Syllabus updated: Sep 8, 2025
Language: Japanese

Syllabus

Course overview and goals

The purpose of this class course is to understand the current status and state-of-the-art of social implementation of AI and data science technologies, and to examine the applicability and challenges of these technologies. In each class, lecturers from companies in various fields such as architecture, IT, finance, and materials will introduce case studies of technology and product development using data science and AI.
The goal is for students to gain a broad perspective of the real world by acquiring knowledge about the application of data science and AI technologies in a wide range of fields, and by explaining their considerations about social applications in their assigned reports.
This course emphasizes dialogue with corporate lecturers. In addition to the seven class sessions, students shall, in principle, attend the DS&AI Forum to be held on the afternoon of November 28, 2025 at the Oookayama Campus.　(Added on September 8, 2025)

Course description and aims

This course aims to develop ability of each student to be more successful in the real world with the consideration of social implementation of data science and artificial intelligence.

Student learning outcomes

実務経験と講義内容との関連 (又は実践的教育内容)

This lecture will be given by lecturers from companies such as LINE Yahoo Corp., Takenaka Corp., Topcon Corp., IHI Corp., DIC Corp., Kawasaki Heavy Industries Ltd., Kajima Corp.
The following lecture schedule has been revised to be more specific (September 8, 2025).

Keywords

Data utilization, big data, machine learning, artificial intelligence, data science, heavy industries, construction, materials

Competencies

Specialist skills
Intercultural skills
Communication skills
Critical thinking skills
Practical and/or problem-solving skills

Class flow

This course is classified as a high-flex type, but can only be taken in designated classrooms in Ookayama and Suzukakedai.

Course schedule/Objectives

	Course schedule	Objectives
Class 1	Data Utilization at Yahoo! JAPAN	Share AI/Data Utilization Examples at Yahoo! JAPAN
Class 2	Building Industry in the Age of Advanced AI Technologies.	This lecture would try to motivate the need, understand the challenges, and explore the opportunities of advanced AI technology applications in the building industry
Class 3	Sensor & AI Experience: Medical & Construction Fields	Experience AI programs for eyecare & infrastructure using latest sensors and dataset
Class 4	Application of AI/Data Analysis Technology in Heavy Industries	Introducing applications and examples of data science in heavy industries.
Class 5	The Use of Data Science in Chemical Materials Development	Introducing the Application and Practical Examples of Data Science in Manufacturing Companies
Class 6	Activities to apply AI technology in heavy industries	Explain tips for the success of AI implementation process in the business world
Class 7	Kajima Corporation Singapore's Initiatives Toward Realizing a Data-Driven Society 2025	Learn Key Digital Application Points Using Our Own Building “the GEAR” as an Example

Study advice (preparation and review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.

Textbook(s)

None required.

Reference books, course materials, etc.

Materials will be provided on Science Tokyo LMS in advance.

Evaluation methods and criteria

No final exam will be given. The evaluation will be based on the reports of each assignment and the participation report of the DS&AI Forum scheduled for November 28. Please note that it is not possible to submit assignment reports for missed lectures. Even if a student submits an assignment report for a lecture he/she has missed, it will not be graded. (Added on September 8, 2025)

Related courses

XCO.T487 ： Fundamentals of data science
XCO.T488 ： Exercises in fundamentals of data science
XCO.T489 ： Fundamentals of artificial intelligence
XCO.T490 ： Exercises in fundamentals of artificial intelligence

Prerequisites

Doctoral students must take DSA.P631 "Progressive Applied Practical Data Science and AI 3A".

Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).

Asako Kanezaki, Katsumi Nitta, Norio Tomii, Takayoshi Yokota
lecture_ap[at]dsai.isct.ac.jp

Office hours

Contact by e-mail in advance to schedule an appointment.

Other

・This class is a technical course that can be considered an entrepreneurship course. The GAs that this subject corresponds to are GA0M and GA1M.
・This course corresponds to Applied AI and Data Science A (XCO.T483), which was offered until FY2023. Students who took Applied AI and Data Science A as undergraduates should register for this course. Students who took Applied AI and Data Science A in graduate school may not register for this course.