Course title
R26751001
Data　Science Literacy

 ICHIKAWA Manabu

MOCHINAGA Dai

HARADA Takuya
Course description
In this class, you will learn about the history of data science and what fields of society and research are currently using data science.
You will also learn about the ethics and laws that are necessary when handling data.
Purpose of class
Data handling is an essential part of most engineering research.
In addition, data science is an inseparable part of current and future engineering.
The purpose of this class is to provide you with the knowledge of the history and current status of data science in engineering research so that you can acquire literacy in your graduation research.
Goals and objectives
  1. To be able to learn about the use of data in society and changes resulting from its use.
  2. To be able to learn about the fields of data and AI utilization and the technologies for their utilization.
  3. "To be able to learn the current status of data and AI applications.
  4. "To be able to learn the rules for handling data and AI.
Language
Japanese
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. Changes that are happening in society Read the Consortium's materials for review 90minutes
Review and do assignments 60minutes
2. Data being used in society Read the Consortium's materials for review 90minutes
Review and do assignments 60minutes
3. Areas of data and AI utilization Read the Consortium's materials for review 90minutes
Review and do assignments 60minutes
4. Data and AI Application Areas and Technologies for AI Utilization Read the Consortium's materials for review 90minutes
Review and do assignments 60minutes
5. The field of data and AI utilization Read the Consortium's materials for review 90minutes
Review and do assignments 60minutes
6. Latest trends in data and AI utilization Read the Consortium's materials for review 90minutes
Review and do assignments 60minutes
7. Ethics and laws in handling data and AI Read the Consortium's materials for review 90minutes
Review and do assignments 335minutes
8. This course ends in 7. None 0minutes
9. This course ends in 7. None 0minutes
10. This course ends in 7. None 0minutes
11. This course ends in 7. None 0minutes
12. This course ends in 7. None 0minutes
13. This course ends in 7. None 0minutes
14. This course ends in 7. None 0minutes
Total. - - 1325minutes
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 reports or mini exams Total.
1. 30% 30%
2. 30% 30%
3. 25% 25%
4. 15% 15%
Total. 100% -
Evaluation method and criteria
Evaluation will be made based on reports or mini exams in each class.
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Textbooks and reference materials
教科書：教養としてのデータサイエンス　内田誠一など著　講談社
参考資料：コンソーシアム教材資料
Prerequisites
None
Office hours and How to contact professors for questions
  • Ask your classroom teacher
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
Active-learning course
About half of the classes are interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
N/A 該当しない
Education related SDGs:the Sustainable Development Goals
  • 1.NO POVERTY
  • 2.ZERO HUNGER
  • 3.GOOD HEALTH AND WELL-BEING
  • 4.QUALITY EDUCATION
  • 5.GENDER EQUALITY
  • 6.CLEAN WATER AND SANITATION
  • 7.AFFORDABLE AND CLEAN ENERGY
  • 8.DECENT WORK AND ECONOMIC GROWTH
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
  • 10.REDUCED INEQUALITIES
  • 11.SUSTAINABLE CITIES AND COMMUNITIES
  • 12.RESPONSIBLE CONSUMPTION & PRODUCTION
  • 13.CLIMATE ACTION
  • 14.LIFE BELOW WATER
  • 15.LIFE ON LAND
  • 16.PEACE, JUSTICE AND STRONG INSTITUTIONS
  • 17.PARTNERSHIPS FOR THE GOALS
Last modified : Sat Sep 09 07:53:22 JST 2023