2020 Faculty Courses School of Computing Major courses
Practical Artificial Intelligence and Data Science A
- Academic unit or major
- Major courses
- Instructor(s)
- Tsuyoshi Murata / Hiroshi Masumoto / Nobuyuki Koyama / Shun Zhenming / Yoshiyuki Kobayashi / Yuzuru Yamakage / Hideaki Nishimoto / Takayuki Nakata
- Class Format
- Lecture
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - Class
- -
- Course Code
- XCO.T493
- Number of credits
- 100
- Course offered
- 2020
- Offered quarter
- 4Q
- 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. As shown in the class plan, each class session will explain the trends and issues in technology and product development in the fields of pharmaceuticals, IT, life insurance, materials, and so on.
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, AI, Pharma, Deep Learning, Life Insurance, Materials
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 | Data science in pharmaceutical industry (1) (Daiichi Sankyo Company: Hiroshi Masumoto, Nobuyuki Koyama, Zhenming Shun) | Instructions will be given during the lecture. |
| Class 2 | Data science in pharmaceutical industry (2) (Daiichi Sankyo Company: Hiroshi Masumoto, Nobuyuki Koyama, Zhenming Shun) | Instructions will be given during the lecture. |
| Class 3 | Promotion and Application of Deep Learning at Sony (1) (Sony Corporation: Yuki Kobayashi) | Instructions will be given during the lecture. |
| Class 4 | Promotion and Application of Deep Learning at Sony (2) (Sony Corporation: Yuki Kobayashi) | Instructions will be given during the lecture. |
| Class 5 | What we want to tell everyone who wants to use technology as a weapon for business innovation (Fujitsu: Yuzuru Yamakage) | Instructions will be given during the lecture. |
| Class 6 | The Use of Data Science in Life Insurance Company (The Dai-ichi Life Insurance Company: Hideaki Nishimoto) | Instructions will be given during the lecture. |
| Class 7 | AI and Data Science in Materials Development and Manufacturing (Asahi Kasei Corporation: Takayuki Nakata) | 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.
none
Evaluation methods and criteria
Students' course scores are based on reports (100%).
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
none
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