2020 Faculty Courses School of Computing Major courses
Practical Artificial Intelligence and Data Science B
- Academic unit or major
- Major courses
- Instructor(s)
- Tsuyoshi Murata / Ryo Inokuchi / Hirohisa Tasaki / Hirohito Okuda / Masamitsu Kitase / Akihiro Terada / Naoki Nishimura
- Class Format
- Lecture
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - Class
- -
- Course Code
- XCO.T494
- 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 of technological and product development in the fields of IT, finance, manufacturing, and services.
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, IT, finance, manufacturing, services
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 | Financial Data Analytics in Practice (Mizuho–DL Financial Technology: Akira Iguchi) | Instructions will be given during the lecture. |
| Class 2 | AI of Manufacturing (Fanuc Corporation: Akihiro Terada) | Instructions will be given during the lecture. |
| Class 3 | What Skills and Abilities Are Required for Corporate AI Engineers to Achieve Success in Product Development (Konica Minolta: Hirohito Okuda) | Instructions will be given during the lecture. |
| Class 4 | Introduction to New Business Development (1) (NEC Corporation: Seiko Kitase) | Instructions will be given during the lecture. |
| Class 5 | Introduction to New Business Development (2) (NEC Corporation: Seiko Kitase) | Instructions will be given during the lecture. |
| Class 6 | Industrial Applications of Artificial Intelligence Technology (Mitsubishi Electric Corporation: Hirohisa Tasaki) | Instructions will be given during the lecture. |
| Class 7 | Business Application Workshop on Machine Learning and Data Utilization (Recruit: Naoki Nishimura) | 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