2026 (Current Year) Special graduate degree programs Specially Offered Degree Programs for Graduate Students Center of Data Science and Artificial Intelligence
Progressive Applied Practical Data Science and Artificial Intelligence 1C
- Academic unit or major
- Center of Data Science and Artificial Intelligence
- Instructor(s)
- Asako Kanezaki / Katsumi Nitta / Takayoshi Yokota / Norio Tomii / Kei Miyazaki / Keiji Okumura / Yutaro Tachibana / Yoshihiro Miyake / Jun Sakuma / Isao Ono / Daisuke Hirashima / / Masahiro Akiba / Zaixing Mao / Youdo Naka / Yukihiro Kawano / Yusuke Motegi / Motofumi Fukui / Yoshinori Sato / Hokuto Fujii / Yuki Ohira / Yuki Murata
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Fri (M-B07(H101), J2-302(J233))
- Class
- -
- Course Code
- DSA.P613
- Number of credits
- 100
- Course offered
- 2026
- Offered quarter
- 1Q
- Syllabus updated
- Mar 5, 2026
- 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.
Therefore, in addition to the seven class sessions, this course emphasizes dialogue with company lecturers, and in principle, students shall participate in the DS&AI Forum to be held face-to-face on the Ookayama campus in the afternoon of late May.
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)
In this course, instructors from NGK INSULATORS, LTD., Furukawa Electric Co., Ltd., TOPCON CORPORATION, TAKENAKA CORPORATION, IHI Corporation, Sumitomo Heavy Industries, Ltd., and Institute of Science Tokyo will provide lectures on problem-solving techniques based on their practical business experience
Keywords
Data Science, Artificial Intelligence, Machine Learning, Medical equipment, Manufacturing, Heavy machinery
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 | Digital Transformation Initiatives at NGK INSULATORS, LTD. |
Overview of NGK Insulators' data utilization strategy and practical applications |
| Class 2 | Leveraging AI and Data Science in Manufacturing Operation |
Understanding Digital Transformation through AI and Data Science Case Studies in Manufacturing |
| Class 3 | The True Value of Sensor Technology in the AI Era |
Exploring Advanced Optical Sensing Technologies and Their Innovations in Data Processing |
| Class 4 | AI and Law |
This introduces examples of AI applications in courts and law firms, and considers the challenges of implementing AI in the legal field |
| Class 5 | Utilization of AI and Advanced Technologies in the Construction Industry |
This lecture will explore how AI and other advanced technologies are being implemented in the construction industry through various case studies. |
| Class 6 | Application of AI/Data Analysis Technology in Heavy Industries |
Introducing applications and examples of data science in heavy industries. |
| Class 7 | On the Employment of Data Science and AI in Heavy Machinery Manufacturing Industry |
Sumitomo Heavy Industries engages in the development and production of a wide spectrum of machinery, including construction equipment and industrial robots. In this lecture, we will present how data science (DS) and artificial intelligence (AI) are applied across these various machinery domains. Furthermore, we will outline future directions and prospects for the continued advancement of DS and AI within our company. |
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 term-end report.
The evaluation will also include the results of participation in the DSAI Forum to be held in late May.
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
Only students of doctor curse are acceptable. Other students must take DSA.P411 " Applied Practical Data Science and AI 1C" instead of this course.
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
Katsumi Nitta, 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 GA0D and GA1D.