2026 (Current Year) Special graduate degree programs Specially Offered Degree Programs for Graduate Students Center of Data Science and Artificial Intelligence
Applied Practical Data Science and Artificial Intelligence 3A
- Academic unit or major
- Center of Data Science and Artificial Intelligence
- Instructor(s)
- Katsumi Nitta / Takayoshi Yokota / Kei Miyazaki / Keiji Okumura / Yutaro Tachibana / Yoshihiro Miyake / Jun Sakuma / Isao Ono / Nanami Matsuzaki / Yohei Onishi / Ken Sumida / Hiroe Sakai / Sayuri Iwashita / Adrian Jimenez Pascual / Tetsu Hayakawa / Yuki Saito / Miki Okuma / Hirokazu Takagi / Yusuke Hazui
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Tue (M-374, G2-202)
- Class
- -
- Course Code
- DSA.P431
- Number of credits
- 100
- Course offered
- 2026
- Offered quarter
- 3Q
- Syllabus updated
- Sep 17, 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.
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 in late November at the Oookayama Campus.
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 course features guest lecturers from various companies, including Rakuten Group, Inc., Insight Edge, Inc., Acroquest Technology Co., Ltd., Sompo Holdings, Inc. and Mitsubishi Heavy Industries, Ltd.
Keywords
Data Utilization, Big Data, Machine Learning, Artificial Intelligence, Data Science, IT Companies, General Trading Companies, Insurance Companies, Heavy Industries
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 | User Experience Design Leveraging Data and AI(1) |
This course provides practical learning on the design processes and methodologies for creating user experiences that leverage AI and data in internet services. |
| Class 2 | User Experience Design Leveraging Data and AI(2) |
This course provides practical learning on the design processes and methodologies for creating user experiences that leverage AI and data in internet services. |
| Class 3 | DX Strategies for a General Trading Company - Learning from the Fields |
Business Problem Solving through Generative AI and Data Analysis |
| Class 4 | Next-Generation Software Development Methods in the Era of Generative AI and Experiencing a Practical Development Process(1) |
Experience a practical development process in which you build a product while communicating your development intentions and decision-making criteria to generative AI. |
| Class 5 | Next-Generation Software Development Methods in the Era of Generative AI and Experiencing a Practical Development Process(2) |
Experience a practical development process in which you build a product while communicating your development intentions and decision-making criteria to generative AI. |
| Class 6 | Data Science in Practice and the Data Value Chain at SOMPO Group |
This session will help you understand the structure of corporate data utilization, drawing on examples from insurance and nursing care fields. |
| Class 7 | AI Technologies Driving Both “Building” and “Operating” Machines Supporting Social Infrastructure |
Learn the process of applying technologies to products and operations based on theoretical foundations and practical constraints |
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 late November. 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.
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
As this course practical exercises, the following prerequisites are assumed for students.
・Have basic programming skills (any programming language is acceptable).
・Have a personal ChatGPT account. (If you do not have one, please create one in advance.)
・Have a laptop computer that can connect to Wi-Fi.
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).
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 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.