2025 (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 2B
- 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 / Hiroki Shiraishi / Katsuro Tanaka / Yusuke Ota / Ryo Matsui / / / Motofumi Fukui / Yoshihisa Kiyota / Takaaki Miyauchi
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Wed
- Class
- -
- Course Code
- DSA.P422
- 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)
This lecture is given by cooperate scientists or engineers of Sumitomo Mitsui Card Company, Limited, J-Power Power Development Corporation, Recruit Corporation, Mitsubishi Electric Corporation, Sumitomo Heavy Industries, Ltd. about application of AI and Data Science to the practical systems.
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 | Value Creation with Cashless Data and AI | Learn from Real Examples: Value Creation with Data and AI in Business Settings |
| Class 2 | J-Power's DSAI Application and R&D: Autonomous Flight Drone Development as an Example | This lecture will introduce autonomous flying drone development and electricity price forecasting as examples of DSAI applications at J-Power. |
| Class 3 | Business Applications of Machine Learning and Data Science (1) | This lecture will introduce data science techniques that support critical decision making in business issues and how to think about their use. |
| Class 4 | Business Applications of Machine Learning and Data Science (2) | The difficulties in implementing data science technologies in society and their solutions will be presented with case studies. |
| Class 5 | Industrial application of artificial intelligence technology | In this course, practical application examples of artificial intelligence technology will be introduced. Through the understanding of practical examples, students will acquire appropriate selection skills for algorithms according to the task. |
| Class 6 | Information technology for heavy machinery. | Relationships and issues between heavy machinery, people, and information technology. |
| Class 7 | History of Construction DX and the Digital Human Resources We Seek | Learn about digital technologies used in society and the skills required to use 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.
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
Doctoral students must take DSA.P622 "Progressive Applied Practical Data Science and AI 2B".
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 GA0M and GA1M.
・This course corresponds to Applied AI and Data Science D (XCO.T486), which was offered until FY2023. Students who took Applied AI and Data Science D as undergraduates should register for this course. Students who took Applied AI and Data Science B in graduate school may not register for this course.