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 2B
- 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 / Akira Tajima
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Wed (M-B07(H101), J2-303(J234))
- Class
- -
- Course Code
- DSA.P622
- 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 MUFG Bank, Ltd., LY Corporation, Toyo Engineering Corporation, Tokyo Electron Limited, All Nippon Airways Co., Ltd., Mitsubishi Corporation, and Fujitsu Limited will provide lectures on the social implementation of AI and data science technologies, based on their respective corporate experiences.
Keywords
artificial intelligence, data science, machine learning, finance, AI business, electric power, heavy machinery, construction
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 | AI Technology in the Financial Industry: Deployment in Real-World Business |
This course provides an overview of the current state and future prospects of AI utilization within the financial sector. We will explore the evolution from enhancing existing operations and efficiency to transforming business models and building cross-industrial AI frameworks. Furthermore, from the unique perspective of a joint researcher engaged in both academia and industry, the lecturer will share firsthand experiences and the practical challenges of bridging the gap between theoretical research and real-world business application. |
| Class 2 | Data Utilization at LY Corporation |
Share AI/Data Utilization Examples at LY Corporation |
| Class 3 | Data Challenges and Utilization Approaches in the Construction Project Business |
This lecture outlines key challenges in data utilization for construction projects with unique characteristics and introduces basic approaches and technologies to address them. |
| Class 4 | The Future of Semiconductor Manufacturing Equipment Driven by AI and Data Science |
Artificial intelligence, such as machine learning and deep learning, is increasingly being used in semiconductor manufacturing processes. This lecture will introduce state-of-the-art semiconductor manufacturing processes, explain the high technological barriers that stand in the way, and explain how artificial intelligence can be used to overcome these barriers |
| Class 5 | "Digital by Default" × "Human Premium": Maximizing Value through "Digital" × "The Power of People" – ANA's Challenge in Data and AI Utilization |
Exploring technology applications to enhance Customer and Employee Experience、 based on practical examples of Data and AI utilization transforming ANA's business. |
| Class 6 | AI-Driven Corporate Transformation at Mitsubishi Corporation: Strategy and Challenges |
AI Strategy and Organizational Change at Mitsubishi Corporation: A Practitioner’s Perspective |
| Class 7 | Design and Execution of AI Implementation Projects |
This course introduces multiple case studies of real-world AI implementation projects. It provides an overview of the uncertainties encountered at each stage—from concept and design to execution—and discusses effective strategies for addressing them. |
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.
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 Advanced Artificial Intelligence and Data Science A
Prerequisites
Only students of doctor curse are acceptable. Other students must take DSA.P422 " Applied Practical Data Science and AI 2B" 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 D (XCO.T690), which was offered until FY2023. Students who took Progressive Applied AI and Data Science D may not register for this course.