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- School of Science
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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- School of Computing
- Instructor(s)
- Kanezaki Asako Tomii Norio Miyake Yoshihiro Ono Isao Nitta Katsumi Kobayashi Takao Koyama Nobuyuki Aoyagi Kenji Igawa Kousaku Tsuchimoto Takayoshi Okada Takashi Kanai Tsukasa Okazaki Yoshitaka Furukawa Kei Tanji Hironori
- Class Format
- Lecture (Livestream)
- Media-enhanced courses
- Day/Period(Room No.)
- Tue7-8()
- Group
- -
- Course number
- XCO.T687
- Credits
- 1
- Academic year
- 2023
- Offered quarter
- 3Q
- Syllabus updated
- 2023/9/27
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This course is designed for students to understand the outline of WEB media systems focusing on the infrastructure of artificial intelligence and data utilization, information retrieval, and machine learning to consider the possibility to utilize artificial intelligence and data science in the field.
The lecturers will explain broad pictures and recent trends of the topic in each class, as shown below.
Student learning outcomes
This course aims to develop ability of each student to be more successful in the real world with the consideration of artificial intelligence and data science, and also through the opportunity for students to describe their own ideas.
Course taught by instructors with work experience
| ✔ Applicable | How instructors' work experience benefits the course |
|---|---|
|
This lectures are given by scientists or engineers from Daiichi-Snakyo, Toppan, Yahoo, Komatsu, Shimizu Construction and Sumitomo Mitsui Trust Bank about application of AI and Data Science to the practical systems. |
Keywords
Data utilization, big data, machine learning, artificial intelligence, data science
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | ✔ Critical thinking skills | Practical and/or problem-solving skills |
Class flow
This course requires students to take an active role in their own learning. It is required to submit a summary report after each class and a total report after the final class.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Data science for new drug development in pharmaceutical industry | How data science can contribute to new drug development in pharmaceutical industry will be explained in this lecture. |
| Class 2 | The applicability of AI and data science in life science | This lecture will discuss how AI and machine learning can contribute to the development of life sciences. |
| Class 3 | Utilization of Data Science and AI in Toppan DX | This lecture will focus on the research and development of image/document R&D and manufacturing data analysis/solution development cases in the printing business. We aim to understand data utilization in the manufacturing industry. |
| Class 4 | Data Utilization at Yahoo! JAPAN | Sharing AI/Data Utilization Cases at Yahoo! JAPAN |
| Class 5 | Creating Customer Value with DX, AI, and IoT: Introduction of Construction Tech Examples | Introduce how ICT is used to solve real business problems through construction tech case examples |
| Class 6 | AI and Data Application in the Construction Industry | Learn the importance of digitalization through examples of AI and data utilization initiatives. |
| Class 7 | Impact Orientation and Scientific Thinking in ESG Finance | Learning from the logical perspective of impact (societal outcomes) and the cutting-edge domain of ESG finance where science and finance merge. |
Out-of-Class Study Time (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.
They should do so by referring to textbooks and other course material.
Textbook(s)
None required
Reference books, course materials, etc.
Materials will be provided on T2SCHOLA in advance and shared in the Zoom lecture
Assessment criteria and methods
Reports at the end of each class and a term-end report will be considered
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 (i.e., required knowledge, skills, courses, etc.)
Only students of doctor course are acceptable.
Other students are required to register XCO.T483 instead of XCO.T687.
Other
This lecture is offered in cooperation with Daiichi Sankyo, Toppan, Yahoo! JAPAN, LINE, Komatsu, and Shimizu Corporation.
