3. 강의목표
The goal of this course is to study concepts and techniques for data analysis and exercise with open source tools such as Python and data analysis libraries.
4. 강의선수/수강필수사항
- Prerequisites: CSED233 Data structure (or some knowledge on basic data structure and algorithms) and some level of programming skills.
- 수강 정원이 찼을 경우, POSTECH 컴공과 학부생 및 컴공지망 무은재학부생만 추가 등록 가능.
5. 성적평가
Assignments 28%
Exam 72% (Midterm 36%, Final 36%)
Written exam on Tuesday 11:00am~12:15pm (18%)
Tuesday exam will test you how well you understand the lecture materials.
Programming exam on Thursday 11:00am~12:15pm (18%)
Thursday exam will test you how well you did Exercises and HWs by yourself.
Students must bring a laptop with a fully charged battery.
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
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There is no required textbook for this class, and you should be able to learn everything from lecture notes and public websites.
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0000
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7. 참고문헌 및 자료
There is no required textbook for this class, and you should be able to learn everything from lecture notes and public websites.
8. 강의진도계획
W01 Big data concepts, data models (HW1 out - Python, Numpy, Pandas)
W02 Relational algebra, SQL
W03 SQL, SQLite (HW2 out - SQLite)
W04 MapReduce
W05 Exploratory data analysis (HW3 out - EDA with sklearn)
W06 Data preprocessing
W07 Statistics4BigData (one class)
W08 Midterm
W09 Machine learning concepts, evaluation measures (HW4 out - Kaggle1 on two tables)
W10 Decision trees, naive Bayes, rule Learning, kNN
W11 Ensembles, neural networks (HW5 out - Kaggle2 on two tables)
W12 Support vector machines (SVM)
W13 Clusterings (HW6 out)
W14 PageRank and link analysis
W15 Recommender systems (HW7 out)
W16 Final exam
9. 수업운영
- This semester, face-to-face classes will be held in the classroom, except for the first two weeks of online lectures using PLMS Zoom.
- There is no required textbook for this class, so it is important to take notes during class.
- Lecture notes will be posted to the PLMS prior to class.
10. 학습법 소개 및 기타사항
You must write up HWs and code from scratch independently. The following are considered to be honor code violations:
Looking at the writeup or code of another student.
Showing your writeup or code to another student.
Discussing homework problems in such detail that your solution (writeup or code) is almost identical to another student's answer.
Uploading your writeup or code to a public repository (e.g. github, bitbucket, pastebin) so that it can be accessed by other students.
Looking at solutions from previous years' homeworks - either official or written up by another student.
Anyone violating the honor code will get F no matter what.
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