This course is designed for students to understand the outline of artificial intelligence and data science in the digital art and manufacturing industry 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.
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.
✔ Applicable | How instructors' work experience benefits the course |
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This lecture is given by cooperate scientists or engineers of Team-Labo Inc., Toyota Inc., Kyocela Inc., Eisai Inc. and Tokyo Electron Inc., about application of AI and Data Science to the practical systems. |
artificial intelligence, data science, AI business, digital art, manufacturing
✔ Specialist skills | Intercultural skills | Communication skills | ✔ Critical thinking skills | ✔ Practical and/or problem-solving skills |
This course requires students to take an active role in their own learning. It is required to attend each class.
Course schedule | Required learning | |
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Class 1 | AI application in digital art (1) | Understand the overview of AI-based artwork and how it works |
Class 2 | AI application in digital art (2) | Understand the overview of AI-based artwork and how it works |
Class 3 | AI and Data Science in the Automotive Enterprise (1) | Understand the application of AI and data science in a automotive company |
Class 4 | AI and Data Science in the Automotive Enterprise (2) | Understand the application of AI and data science in a automotive company |
Class 5 | Human Augmentation | Human augmentation, which enhances human potential and enables the acquisition of new abilities using IT technologies such as AI and IoT, will be explained with various examples. |
Class 6 | AI and Data Science in the Pharmaceutical Industry | Repport assignment: In the future, how advanced will the use of data science in drug discovery research be, and what kind of relationship will be established between human researchers and research AI? |
Class 7 | AI and Data Science Create the Future of Semiconductor Manufacturing Equipment | Artificial intelligence, such as machine learning and deep learning, is increasingly being used in semiconductor manufacturing processes. This lecture will introduce state-of-the-art semiconductor manufacturing processes, explain the high technological barriers that stand in the way, and explain how artificial intelligence can be used to overcome these barriers. |
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.
None required
Materials will be provided on T2SCHOLA in advance and shared in the Zoom lecture
Based on reports evaluating students' understanding at the end of each class.
Students of the doctor course are required to register XCO.T690 "Progressive Applied Artificial Intelligence and Data Science D" instead of XCO.T486.
This lecture is supported by Team-labo Inc, Toyota Inc., Kyocela Inc., Esai Inc., and Tokyo Electron Inc.
Online lecture using Zoom.