2025Year

First Semester

Practical Data Analysis and Utilization for Digital Exchange

Lecture

Practical Data Analysis and Utilization for Digital Exchange

Z0400016 Practical Data Analysis and Utilization for Digital Exchange

MIKI Yoshio

2.0Credits

Mon.2Period

Shinjuku Remote

B-0753DX実践ラボ,.

A) A high degree of specialized expertise　50%
B) The skills to use science and technology　50%
C) The ability to conduct research independently, knowledge pertaining to society and occupations, and sense of ethics required of engineers and researchers　0%
D) Creative skills in specific areas of specialization　0%

In this class, students will acquire the ability to solve real-world problems by analyzing real-world data. Specifically, students will learn the basics of real-world modeling, which are lacking in statistics and artificial intelligence methods.

It is desirable for students to have studied statistics, machine learning, etc. at the undergraduate level. It is also recommended that students take “Advanced Data Analysis and Applications,” which is offered in the first semester. In addition, since real data from real companies are used in this class, students are required to sign a nondisclosure agreement individually.

Project Based Learning／Discussion Debate／Group Work／Presentation／Practice Fieldwork／Support for self-learning using ICT

1. Guidance
2. Statistical modeling, limitations of machine learning and real world modeling
3. Data Analysis Objectives and Problem Setting
4. Retail Industry Issues and Sales Data Analysis
5. Machine Learning, Time Series Data Analysis and Problem Solving Potential
6. Modeling of consumer behavior
7. Public transportation issues and analysis of user data
8. Data collection necessary for modeling such as GIS
9. Human mobility and the state of transportation
10. Manufacturing issues and sensor data analysis
11. Sensing data and analysis accuracy
12. Modeling of physical phenomena and defect determination
13. Personal information protection, intellectual property strategy
14. Invention and visualization
15. Review (explanation of final report and presentation)

Grades of A+, A, B, C, D, and F will be determined based on a comprehensive evaluation of the in-class reports and the final report (sometimes a presentation, etc.). The weight of the in-class report and the final report will be determined to reduce the disadvantage of the student, although the final is heavier.

The final grades will be made public through the university's grade disclosure system. In addition, the usual reports will be given in class to share information with students.

Not specified

To be introduced in class as appropriate.

After class,　Or, make an appointment with the e-mail address “mikiyo@cc.kogakuin.ac.jp”.

In accordance with the policy of the DX Practice Lab, we will lecture on how the knowledge learned in college can be applied to real problems. We hope you will take this course!

Applicable

Established a data science team and implemented a service business at a general electronics manufacturer.

Informatics Program