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 1C
- Academic unit or major
- Center of Data Science and Artificial Intelligence
- Instructor(s)
- Asako Kanezaki / Katsumi Nitta / Norio Tomii / Kei Miyazaki / Keiji Okumura / Jun Sakuma / Yoshihiro Miyake / Isao Ono / Zaixing Mao / Masahiro Akiba / Takehiko Nomura / Shinya Kojima / Kuniharu Ito / Shota Takeshima / Munenobu Hashizume / Kousaku Igawa / Yuichi Goto / Takayoshi Yokota / Yutaro Tachibana
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Fri
- Class
- -
- Course Code
- DSA.P613
- Number of credits
- 100
- Course offered
- 2025
- Offered quarter
- 1Q
- 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.
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 the afternoon of May 28, 2025.
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 Topcon Corporation, Furukawa Electric Company, Denso Corporation, Nippon Steel Corporation, Kanadevia Corporation, and Komatsu Ltd. will lecture on problem-solving techniques based on their practical experience.
Keywords
Data Science, Artificial Intelligence, Machine Learning, Medical equipment, Manufacturing, Heavy machinery
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 | Significance of Sensors for AI Utilization | This lecture introduces sensing technologies based on optics, along with their data generation and processing methods, addressing social challenges in the areas of healthcare, agriculture, and infrastructure. |
| Class 2 | Data Utilization in Manufacturing | Understanding DX through examples of data utilization and digitalization in manufacturing |
| Class 3 | Practical Introduction to Image Recognition | Learning image recognition using machine learning through practical examples of product development. |
| Class 4 | Applications of DS and AI technologies in Nippon Steel Corporation(1) | Digital transformation measures that Nippon Steel Corporation is promoting by utilizing DS and AI technologies |
| Class 5 | Applications of DS and AI technologies in Nippon Steel Corporation(2) | Digital transformation measures that Nippon Steel Corporation is promoting by utilizing DS and AI technologies |
| Class 6 | Challenge to Solve Social Issues in Kanadavia | An opportunity to personally consider environmental issues like waste, energy, and water |
| Class 7 | Creating Customer Value in the Construction Industry through ICT: Product Development with DX, IoT, and AI-Driven Software Development | Learn how knowledge of software development and AI, acquired in university, is utilized in the development of actual commercial products. |
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.
The evaluation will also include the results of participation in the DSAI Forum to be held on May 28, 2025.
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.P411 " Applied Practical Data Science and AI 1C" 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.