2021 Faculty Courses School of Computing Major courses
Practical Artificial Intelligence and Data Science A
- Academic unit or major
- Major courses
- Instructor(s)
- Tsuyoshi Murata / Katsumi Nitta / Takao Kobayashi / Hiroshi Nagahashi / Yoshiyuki Kobayashi / Takayuki Nakata / Masashi Okada / Hirohisa Tasaki / Daisuke Kitayama / Takeshi Kida / Yukihiro Kawano
- Class Format
- Lecture
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - Class
- -
- Course Code
- XCO.T493
- Number of credits
- 100
- Course offered
- 2021
- Offered quarter
- 1Q
- Syllabus updated
- Jul 10, 2025
- Language
- Japanese
Syllabus
Course overview and goals
The purpose of this course is to understand the current status of social implementation of AI and data science technologies and cutting-edge technologies, and to examine the applicability and challenges of these technologies. Trends and issues in technology and product development in the fields of IT, materials, manufacturing, heavy industry, etc. will be explained in each class as shown in the course schedule.
Course description and aims
The goal of this course is for students to acquire knowledge of AI and data science technologies in various fields, and to gain a broader perspective that will enable them to play an active role in the real world by discussing social applications and explaining new ideas in assignment reports.
Keywords
Data Science, Artificial Intelligence, Deep Learning, Machine Learning, Material, Manufacturing Industry, Heavy Industry
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Class1－Class7： Lectures
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Promotion and Application of Deep Learning at Sony (1) (Sony Group Corporation: Yuki Kobayashi) | Instructions will be given during the lecture. |
| Class 2 | Promotion and Application of Deep Learning at Sony (2) (Sony Group Corporation: Yuki Kobayashi) | Instructions will be given during the lecture. |
| Class 3 | AI and Data Science in Materials Development and Manufacturing (Asahi Kasei Corporation: Takayuki Nakata) | Instructions will be given during the lecture. |
| Class 4 | Machine Learning with Differentiability and Uncertainty and Industrial Applications (Panasonic Corporation: Masashi Okada) | Instructions will be given during the lecture. |
| Class 5 | Industrial Applications of Artificial Intelligence Technology (Mitsubishi Electric Corporation: Hirohisa Tasaki) | Instructions will be given during the lecture. |
| Class 6 | Examples of Data Science and AI Applications in Manufacturing Industry (AGC Inc: Daisuke Kitayama, Takeshi Kida) | Instructions will be given during the lecture. |
| Class 7 | Application of AI/Data Analysis Technology in Heavy Industries (IHI Corporation: Yukihiro Kawano) | Instructions will be given during the lecture. |
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.
They should do so by referring to textbooks and other course material.
Textbook(s)
none
Reference books, course materials, etc.
Materials will be provided on T2SCHOLA in advance and shared in the Zoom lecture
Evaluation methods and criteria
Mainly short report required in each class 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
- XCO.T483 ： Advanced Artificial Intelligence and Data Science A
- XCO.T484 ： Advanced Artificial Intelligence and Data Science B
- XCO.T485 ： Advanced Artificial Intelligence and Data Science C
- XCO.T486 ： Advanced Artificial Intelligence and Data Science D
Prerequisites
Priority may be given to students enrolled in the Progressive Graduate Minor in Data Science and Artificial Intelligence.
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
Please see http://www.dsai.titech.ac.jp/jissen.html .
Other
Slide distribution and report acceptance will be done by T2SCHOLA. For more information, please refer to the following site.
http://www.dsai.titech.ac.jp/jissen.html