2025 (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 2A
- Academic unit or major
- Center of Data Science and Artificial Intelligence
- Instructor(s)
- Asako Kanezaki / Norio Tomii / Kei Miyazaki / Keiji Okumura / Jun Sakuma / Isao Ono / Yoshihiro Miyake / Katsumi Nitta / Takayoshi Yokota / Yutaro Tachibana / Koyori Tsunashima / Adrian Jimenez Pascual / Junichi Kosaka / Yusuke Tashiro / Yusuke Nishigata / Yoshiaki Oida / / / Takuya Yoshimura / Arisa Kubota / Daisuke Adachi / Akane Kasakawa / Takuya Jizo / Keisuke Nakamichi
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Tue
- Class
- -
- Course Code
- DSA.P621
- Number of credits
- 100
- Course offered
- 2025
- Offered quarter
- 2Q
- Syllabus updated
- Mar 19, 2025
- 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, lecturers from Mitsubishi UFJ Trust and Banking Corporation, Fujitsu, Team Lab, Sumitomo Corporation, All Nippon Airways will lecture on problem-solving techniques based on their practical experience.
Keywords
Data Science, Artificial Intelligence, Machine Learning, Finance, IT, digital art, general trading company, transportation
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 | Utilization of data and AI in trust banks | In this lecture, we will learn about the connection between financial engineering and real-world business through examples of the use of data and AI at "Mitsubishi UFJ Trust and Banking" and "Mitsubishi UFJ Trust Investment Technology Institute" |
| Class 2 | Design and Execution of AI Implementation Projects | This course introduces multiple real-world examples of practical AI implementation projects and provides an overview of key success factors of the project management. |
| Class 3 | AI Application in Digital Art (1) | Understand the overview of AI-based artwork and how it works. |
| Class 4 | AI Application in Digital Art (2) | Understand the overview of AI-based artwork and how it works. |
| Class 5 | 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 6 | Shaping the Future with Data and AI : ANA's Challenges and Vision(1) | Explore ANA's practical applications of Data and AI, and discover how technologies can be applied to improve customer and employee experiences. |
| Class 7 | Shaping the Future with Data and AI : ANA's Challenges and Vision(2) | Explore ANA's practical applications of Data and AI, and discover how technologies can be applied to improve customer and employee experiences. |
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
Prerequisites
Only students of doctor curse are acceptable. Other students must take DSA.P421 " Applied Practical Data Science and AI 2A" instead of this course.
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
Asako Kanezaki, Katsumi Nitta, Norio Tomii
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 B (XCO.T688), which was offered until FY2023. Students who took Progressive Applied AI and Data Science B may not register for this course.