Course Objectives
Can explain an overview and application examples of information technology, such as IoT, machine learning, and artificial intelligence.
Can explain an overview of computers and networks.
Can explain an overview of information security and examples of cyberattacks and defense.
Can execute data utilization and analysis from big data and IoT, using a data processing language (Python).
Rubric
| Ideal Level | Standard Level | Unacceptable Level |
| Achievement 1 | Can fully explain an overview and application examples of information technology, such as IoT, machine learning, and artificial intelligence | Can explain an overview and application examples of information technology, such as IoT, machine learning, and artificial intelligence | Cannot explain an overview and application examples of information technology, such as IoT, machine learning, and artificial intelligence |
| Achievement 2 | Can fully explain an overview of computers and networks | Can explain an overview of computers and networks | Cannot explain an overview of computers and networks |
| Achievement 3 | Can fully explain an overview of information security and examples of cyberattacks and defense | Can explain an overview of information security and examples of cyberattacks and defense | Cannot explain an overview of information security and examples of cyberattacks and defense |
Assigned Department Objectives
Teaching Method
Outline:
The aim is to develop the knowledge and skills for the appropriate and effective use of information and information technology, to develop the ability to use them practically, and to develop an attitude toward proactively participating in an information society. The course will be held as an early introductory education to foster human resources capable of utilizing, analyzing, and evaluating real data such as "IoT," "big data," and "AI" following their acquisition of knowledge on "mathematics/data science/AI." Students will learn about real-world issues and how to resolve them appropriately through exercises, using real data and issues, and other practical examples in society by utilizing mathematics, data science, and AI. This lecture will be conducted by a faculty member who has been engaged at a company in middleware (database) research and development.
Style:
Students will learn information technology literacy (knowledge through lectures, and study of practical examples). Quizzes will be conducted every lesson to test students' understanding. Students will be evaluated based on quizzes and submitted work which serve as tests.
Notice:
Students who miss 1/3 or more of classes will not be eligible for a passing grade.
Characteristics of Class / Division in Learning
Course Plan
|
|
|
Theme |
Goals |
| 1st Semester |
| 1st Quarter |
| 1st |
The relationship between information technology and each department, and the components of information technology |
Can explain the rules for using information systems in schools. Can explain application examples of information technology, such as IoT, machine learning, and artificial intelligence in each department (MECA). Can explain the components of information technology and relevant laws and regulations.
|
| 2nd |
Application examples of information technology in MECA and an overview of the information technology used (1) |
Can explain examples in Department M (automatic driving-related technology: traffic sign recognition), Department E (Go using deep learning), etc., and an overview of the information technology used
|
| 3rd |
Application examples of information technology in MECA and an overview of the information technology used (2) |
Can explain examples in Department C (infrastructure maintenance using IoT: motorway turbines and GIS), Department A (building security and contemporary art), etc., and an overview of the information technology being used
|
| 4th |
Application examples of information technology in MECA and an overview of the information technology used (3) |
Can explain the details of the information technology used in MECA cases
|
| 5th |
Supervised and unsupervised learning |
Can explain machine learning with or without labeled data
|
| 6th |
Regression analysis |
Can explain regression analysis
|
| 7th |
Review |
Reflection on studies so far
|
| 8th |
Mutual Evaluations between students |
Mutual Evaluations between students
|
| 2nd Quarter |
| 9th |
Computer fundamentals (1) |
Understand the structure of a computer, and what "calculation" by computer means.
|
| 10th |
Computer fundamentals (2) |
Understand the role of an operating system.
|
| 11th |
Network fundamentals (1) |
Understand the roles of information and communication networks in society.
|
| 12th |
Network fundamentals (2) |
Understand network configurations and mechanisms.
|
| 13th |
Information security fundamentals |
Understand the need for information security.
|
| 14th |
Cyberattacks and defense (1) |
Understand the major attack tactics.
|
| 15th |
Cyberattacks and defense (2) |
Understand defense tactics against attacks.
|
| 16th |
Final exam |
None
|
Evaluation Method and Weight (%)
| Examination | Presentation | Mutual Evaluations between students | Behavior | Portfolio | Other | Total |
| Subtotal | 0 | 0 | 0 | 0 | 100 | 0 | 100 |
| Basic Proficiency | 0 | 0 | 0 | 0 | 40 | 0 | 40 |
| Specialized Proficiency | 0 | 0 | 0 | 0 | 40 | 0 | 40 |
| Cross Area Proficiency | 0 | 0 | 0 | 0 | 20 | 0 | 20 |