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 2C
- 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 / Hiroki Shiraishi / Daisuke Okamoto
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Fri (M-B07(H101), J2-303(J234))
- Class
- -
- Course Code
- DSA.P623
- Number of credits
- 100
- Course offered
- 2026
- Offered quarter
- 2Q
- 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.
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 JFE Engineering Corporation, Sumitomo Mitsui Card Co., Ltd., EARTHBRAIN Ltd., TOPPAN Inc., SHIMIZU CORPORATION, EXEO Group, Inc., and Mitsubishi Electric Corporation will provide lectures based on their practical business experience.
Keywords
Data science, AI, machine learning, materials, general trading companies, engineering companies, IT services
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 | Utilizing Data & AI technologies in Plant Engineering |
This lecture will introduce how data and artificial intelligence are being utilized in Plant Engineering to solve business challenges, by presenting case studies. |
| Class 2 | Value Creation with Cashless Data and AI (2) |
Learn from Real Examples: Value Creation with Data and AI in Business Settings |
| Class 3 | AI-Driven Software Development and Value Creation in Construction for the Physical AI Era |
Learn how knowledge of software development and AI, acquired in university, is utilized in the development of actual commercial products. |
| Class 4 | Data Science and AI Utilization at TOPPAN |
Understanding the social implementation of academic research and AI-driven solutions for industrial challenges. |
| Class 5 | AI and Data Utilization in the Construction Industry |
AI Use Cases for Solving Challenges in the Construction Industry |
| Class 6 | Toward a New Collaboration Between Humans, AI, and Robots |
What kind of future will be created by humans, AI, robots, and IT? What value is expected from data science and data management? |
| Class 7 | Industrial Applications of Artificial Intelligence |
By analyzing case studies of AI implementation, students will acquire the skills to select appropriate algorithms based on specific industrial challenges. |
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.
They should do so by referring to textbooks and other course material.
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.
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.P423 " Applied Practical Data Science and AI 2C" instead of this course.
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
Katsumi Nitta, Takao 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.