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 1B
- 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 / Keiko Nakagawa / Yoshihiro Ota / Ryota Tonoue / Hiroyuki Hishida / Yoshiyuki Kajiwara / Kento Yamada / Tetsu Hayakawa / Takumi Koga / Wataru Murata / Takuma Shibahara / / Hiroki Shiraishi / Daisuke Okamoto
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Wed (M-B07(H101), J2-302(J233))
- Class
- -
- Course Code
- DSA.P612
- 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 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.e.
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 JERA Co., Inc., Insight Edge, Inc. , Acroquest Technology Co., Ltd., Kawasaki Heavy Industries, Ltd., Daiichi Sankyo Co., Ltd., Dai-ichi Life Insurance Company, Limited, and Sumitomo Mitsui Card Co., Ltd. will provide lectures on problem-solving techniques based on their practical business experience.
Keywords
Data Science, Artificial Intelligence, Machine Learning, Pharmaceutical manufacture, IT, General Trading Company
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
This course is a live class by Zoom.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | From the Frontlines of JERA, a Global Energy Leader －Mathematical Modeling Supporting Power Supply through LNG Procurement － |
Discuss the challenges faced by our advanced modeling organization within the energy business division |
| Class 2 | DX Strategies for "Sogo Shosha", General Trading Company, Learning from the Fields— Practical Examples of Data Analysis and AI Utilization. |
Understanding DX strategies and use cases of data science and AI in a general trading company. |
| Class 3 | Societal Transformation Brought by Generative AI and Cutting-Edge System Development |
This course examines how generative AI is reshaping society and the IT industry, |
| Class 4 | AI Technologies Enhancing Societal Infrastructure: Research, Development, and Societal Deployment |
This lecture covers research, development, and real-world applications of optimization and machine learning technologies, which contribute to the enhancement of societal infrastructure. |
| Class 5 | Is an AI-Ready Society Achievable? The Dual Challenge of Human Literacy and System Transformation |
Learning the simultaneous transformation of people and systems required to realize an AI-ready society. |
| Class 6 | Driving Digital Transformation and Leveraging AI and Data Science in the Life Insurance Industry |
This lecture explains, with real-world examples, how AI and data science can be utilized in promoting digital transformation within life insurance companies. |
| Class 7 | Value Creation with Cashless Data and AI(1) |
Learn from Real Examples: Value Creation with Data and AI in Business Settings |
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.
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.P412 " Applied Practical Data Science and AI 1B" 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.
・This course corresponds to Progressive Applied AI and Data Science C2 (XCO.T689-2), which was offered until FY2023. Students who have taken Progressive Applied AI and Data Science C2 may not take this course.