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- > The present state of digital transformation (DX) in Bio-industries
- 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
- Graduate major in Life Science and Technology
- Class Format
- Lecture / (Face-to-face)
- Media-enhanced courses
- Day/Period(Room No.)
- Thr7-8(B2-227, （B223）)
- Group
- -
- Course number
- LST.C402
- Credits
- 1
- Academic year
- 2023
- Offered quarter
- 2Q
- Syllabus updated
- 2023/7/31
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
The aim of this course is to develop bio-DX human resources who can deal with real problems in industry and business and who can also create a new key industry "bioeconomy".
Student learning outcomes
To be able to use DS (data science) and AI to build the infrastructure and utilise a wide variety of bio-data necessary for 'promoting the bio-economy', which aims for sustainable economic growth and a recycling-oriented society through the use of biotechnology, and to be able to create new value from data and seek solutions to business issues.
Keywords
Bioeconomy, biotechnology, data science, AI
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | ✔ Communication skills | ✔ Critical thinking skills | Practical and/or problem-solving skills |
Class flow
In addition to class room lectures, the course incorporates Programme Based Learning (PBL).
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Explanation of lecture and presentation of pre-assignment | undecided |
| Class 2 | Lectures and PBL by lecturers dispatched by companies | undecided |
| Class 3 | Lectures and PBL by lecturers dispatched by companies | undecided |
| Class 4 | Lectures and PBL by lecturers dispatched by companies | undecided |
| Class 5 | Lectures and PBL by lecturers dispatched by companies | undecided |
| Class 6 | Lectures and PBL by lecturers dispatched by companies | undecided |
| Class 7 | Lectures and PBL by lecturers dispatched by companies | undecided |
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
Reference books, course materials, etc.
none
Assessment criteria and methods
Evaluation is based on in-class presentations and reports.
Related courses
- none
Prerequisites (i.e., required knowledge, skills, courses, etc.)
none
