Bio-Data Engineering
- 한국과학기술원
- 이도헌
페이스북
트위터
카카오톡
네이버밴드
링크복사
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- 주제분류
- 공학 >컴퓨터ㆍ통신 >컴퓨터과학
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- 강의학기
- 2012년 1학기
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- 조회수
- 3,750
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This course introduces essential concepts and techniques in data engineering fdeveloping bio-information systems. Essential data engineering techniques including operating systems, programming languages, database systems and artificial intelligence are explained. Students are required to develop their own bio-information systems to consolidate their understanding on those techniques.
차시별 강의
| 1. | |
Orientation and Introduction | Introducing course outlines |  |
| 2. | |
Bio-Information Resources | Big data challenges in bio-data mining | |
| 3. | |
Data Dase Design | Several steps and tips for designing data | |
| 4. | |
Entity-Relationship Diagrams | Designing entity-relationship diagram for datas | |
| 5. | |
Relational Data Model | Terminologies and mathmatical definition related to relational data model | |
| 6. | |
Relational Algebra | Data language and algebra, algebra operations | |
| 7. | |
Transforming ER to Relational Schema | Removing multivalued/composite attributes, generalization and weak entities | |
| 8. | |
SQL DDL | SQL data definition language | |
| 9. | |
SQL DML | SQL data manipulation language | |
| 10. | |
Data Storage | Representing and storing various data | |
| 11. | |
Data Manipulation | Instructions and architecture of machine language | |
| 12. | |
Operating Systems | Basic concepts and components of operating system and process | |
| 13. | |
Networking | Connection, communication, and security of networks | |
| 14. | |
Programming Languages | Evolution and examples of programing languages | |
| 15. | |
Data Mining | Definition and types of data mining with related clustering/classification techiniques | |
연관 자료
