3. 강의목표
Course Description:
The interdisciplinary introduction to environmental big data. Focus is placed upon modeling and analyzing big data in built-in environments.
Course Objectives:
The objectives of the course are (1) to introduce basic knowledge of environmental big data for environmental scientists and engineers, (2) to provide a learning experience of advanced statistical techniques to analyze environmental big data, and (3) to demonstrate the analysis and modeling for natural-human coupled systems.
4. 강의선수/수강필수사항
i) Programming and Problem Solutions (CSED101)
ii) or Permission of Instructor is Required.
5. 성적평가
In-class Assignments 10%
Classroom Participation 10%
Writing Assignments/Problem Sets 30%
Term Project 50%
Total 100%
7. 참고문헌 및 자료
Wilks, D.S., 2011. Statistical methods in the atmospheric sciences (Vol. 100). Academic press.
Other references will be provided in class.
8. 강의진도계획
1st week: Introduction to Environmental Big data
2nd week: Climate Data
3rd week: Water Quantity Data
4th week: Water Quality Data
5th week: Air Quality Data
6th week: Introduction to Linear Data Analysis
7th week: Empirical Orthogonal Function Analysis
8th week: Singular Value Decomposition Analysis
9th week: Neural Network Analysis
10th week: Nonliear EOF and SVD
11th-12th week: Practices for Statistical Techniques
13th-14th week: Visual Tool: QGIS
15th-16th week: Term Project Presentations
9. 수업운영
-Lecture Schedule Type
-Face-to-Face Instructional Method
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청