강의 과목 Course
Unstructured Data Mining Unstructured Data Mining
Unstructured Data Mining 2025-1 · 620089
- 과목 코드Course Code
- 620089
- 학기Semester
- 2025-1
- 시간Schedule
- Tue 3rd / Thu 1st / Thu 2nd period Tue3/Thu1/Thu2
- 학점 / 시수Credits / Hours
- 3/3
- 학년Year
- 3학년 Year 3
- 학과Department
- Business Administration Business Administration
강의 개요Course Description
This course aims to teach methods for handling unstructured data mining, which is at the core of big data. Since modern data environments utilize both structured and unstructured data together, students will review the basics of structured data analysis and expand to unstructured data mining. Students will learn various unstructured data analysis techniques including Python programming basics, web crawling for data collection, text mining, sentiment analysis, and social media analysis. This course aims to teach methods for handling unstructured data mining, which is at the core of big data. Since modern data environments utilize both structured and unstructured data together, students will review the basics of structured data analysis and expand to unstructured data mining. Students will learn various unstructured data analysis techniques including Python programming basics, web crawling for data collection, text mining, sentiment analysis, and social media analysis.
학습 목표Learning Objectives
- Review and deepen understanding of structured data analysis techniques Review and deepen understanding of structured data analysis techniques
- Understand the characteristics and analytical methodologies of unstructured data Understand the characteristics and analytical methodologies of unstructured data
- Acquire skills in unstructured data collection and preprocessing using Python Acquire skills in unstructured data collection and preprocessing using Python
- Learn key unstructured data analysis techniques such as text mining, sentiment analysis, and social media analysis Learn key unstructured data analysis techniques such as text mining, sentiment analysis, and social media analysis
- Understand integrated analysis methods for structured and unstructured data Understand integrated analysis methods for structured and unstructured data
- Strengthen data analysis capabilities through practice-oriented projects Strengthen data analysis capabilities through practice-oriented projects
평가Evaluation
주차별 일정Weekly Schedule
| 주차Week | 주제Topic | 세부 내용Details |
|---|---|---|
| 1 | Course Introduction and Big Data Concepts Course Introduction and Big Data Concepts | Course overview, big data concepts and importance, differences between structured/unstructured data Course overview, big data concepts and importance, differences between structured/unstructured data |
| 2 | Python Programming Basics (1) Python Programming Basics (1) | Python syntax fundamentals, data structures, NumPy basics Python syntax fundamentals, data structures, NumPy basics |
| 3 | Python Programming Basics (2) Python Programming Basics (2) | Pandas, Matplotlib, Seaborn data visualization Pandas, Matplotlib, Seaborn data visualization |
| 4 | Advanced Structured Data Analysis Advanced Structured Data Analysis | Descriptive statistics, exploratory data analysis, correlation analysis Descriptive statistics, exploratory data analysis, correlation analysis |
| 5 | Introduction to Web Data Collection Introduction to Web Data Collection | Understanding web structure, Requests, BeautifulSoup Understanding web structure, Requests, BeautifulSoup |
| 6 | Practical Web Data Collection Practical Web Data Collection | Public data, Open APIs, web scraping ethics Public data, Open APIs, web scraping ethics |
| 7 | Text Preprocessing and Analysis Basics Text Preprocessing and Analysis Basics | Text preprocessing, KoNLPy usage Text preprocessing, KoNLPy usage |
| 8 | Midterm Exam Midterm Exam | |
| 9 | Gaining Insights from Text Gaining Insights from Text | Word frequency analysis, word clouds, TF-IDF Word frequency analysis, word clouds, TF-IDF |
| 10 | Understanding Opinions through Sentiment Analysis Understanding Opinions through Sentiment Analysis | Sentiment analysis, review analysis, social media sentiment analysis Sentiment analysis, review analysis, social media sentiment analysis |
| 11 | Discovering Hidden Topics in Documents Discovering Hidden Topics in Documents | Topic modeling, news article analysis Topic modeling, news article analysis |
| 12 | Understanding Data through Network Relationships Understanding Data through Network Relationships | Network analysis, graph theory, social media influence analysis Network analysis, graph theory, social media influence analysis |
| 13 | Analyzing Multiple Data Types Together Analyzing Multiple Data Types Together | Text-numeric integrated analysis, image data basics Text-numeric integrated analysis, image data basics |
| 14 | Data Storytelling Workshop Data Storytelling Workshop | Data storytelling, effective visualization Data storytelling, effective visualization |
| 15 | Team Project Presentation and Final Exam Team Project Presentation and Final Exam | Final presentations and evaluation Final presentations and evaluation |
교재Textbook
Self-developed PPT materials Self-developed PPT materials