Course Objectives
Students can understand the technologies for utilizing AI and data.
Students can understand the usefulness of data used in society based on actual examples from companies.
Students can understand that AI and data science have the potential to create new value by combining knowledge from various fields.
Rubric
| Ideal Level | Standard Level | Unacceptable Level |
| Achievement 1
(Technologies for utilizing AI and data) | Students can fully understand the technologies for utilizing AI and data. | Students can understand the technologies for utilizing AI and data. | Students cannot understand the technologies for utilizing AI and data. |
| Achievement 2
(Usefulness of data in society) | Students can fully understand the usefulness of data in society. | Students can understand the usefulness of data in society. | Students cannot understand the usefulness of data in society. |
| Achievement 3
(Creation of new value) | Students can fully understand that AI and data science have the potential to create new value by combining knowledge from various fields. | Students can understand that AI and data science have the potential to create new value by combining knowledge from various fields. | Students cannot understand that AI and data science have the potential to create new value by combining knowledge from various fields. |
Assigned Department Objectives
Teaching Method
Outline:
Students acquire basic skills to utilize AI and data, and learn from actual examples that data in a wide range of domains utilized in society is a useful tool to solve daily life and social issues in the midst of social changes aimed at Society 5.0.
Students learn that AI and data science can create new value by combining with knowledge from various fields through examples of data utilization in corporate settings.
Style:
The class will be conducted mainly through lectures and excercises.
Notice:
Evaluation will be based on reports and presentation.
In order to check the achievement of the objectives, questions may be asked on the submitted reports.
Can take makeup exam in need aid up to maximum of 60 points.
The class plan is subject to change depending on progress.
Characteristics of Class / Division in Learning
Course Plan
|
|
|
Theme |
Goals |
| 2nd Semester |
| 3rd Quarter |
| 1st |
Technology for AI applications 1 |
Students can understand the mathematics required for AI applications.
|
| 2nd |
Technology for AI applications 2 |
Students can understand the history and application fields of AI.
|
| 3rd |
Technology for AI applications 3 |
Students can understand business models that utilize AI.
|
| 4th |
Technology for AI applications 4 |
Students can understand the construction and operation of AI.
|
| 5th |
Management of Technology 1 |
Students can understand corporate management and management of technology.
|
| 6th |
Management of Technology 2 |
Students can understand the concept of innovation.
|
| 7th |
Management of Technology 3 |
Students can understand research and development management.
|
| 8th |
Report Writing |
Students write a report on the contents and assignments for weeks 1 through 7.
|
| 4th Quarter |
| 9th |
Examples of Management of Technology in Companies 1 |
Students can understand technologies and businesses that use AI and data.
|
| 10th |
Report Writing |
Students discuss and report on technologies and businesses that use AI and data.
|
| 11th |
Examples of Management of Technology in Companies 2 |
Students can understand technologies and businesses that use AI and data.
|
| 12th |
Report Writing |
Students discuss and report on technologies and businesses that use AI and data.
|
| 13th |
Create Ideas Based on Data |
Studentsn attempt to create and express new ideas by connecting a wide range of data used in society with various fields of application.
|
| 14th |
Report Writing |
Students discuss and report on the creation of idea using data.
|
| 15th |
Presentation |
Students give a presentation on the created idea.
|
| 16th |
Questionnaire |
|
Evaluation Method and Weight (%)
| Report | Presentation | Mutual Evaluations between students | Behavior | Portfolio | Other | Total |
| Subtotal | 80 | 20 | 0 | 0 | 0 | 0 | 100 |
| Basic Proficiency | 40 | 10 | 0 | 0 | 0 | 0 | 50 |
| Specialized Proficiency | 20 | 10 | 0 | 0 | 0 | 0 | 30 |
| Cross Area Proficiency | 20 | 0 | 0 | 0 | 0 | 0 | 20 |