PART 01 Big Data Analysis - Understanding

Chapter 01 The Fourth Industrial Revolution and Data Science
01 Understanding the Fourth Industrial Revolution
02 Data Science for the Fourth Industrial Revolution
03 Fourth Industrial Revolution Service Cases
summation
Practice problems

Chapter 02 Understanding and Utilizing Big Data
01 Understanding Big Data
02 Utilization of Big Data
summation
Practice problems

Chapter 03 Big Data Analysis Based on Data Science
01 Understanding the Big Data Industry
02 Big Data Analysis Methods and Approaches
03 Data Science Methodology for Big Data Analysis
summation
Practice problems

PART 02 Big Data Analysis - Preparation

Chapter 04 Python Programming Basics
01 Getting Started with Python
02 Variables and Objects
03 Data types and operators
04 Conditional statements and loops
05 Function
06 File Processing
07 Key Libraries for Data Analysis
summation
Practice problems

Chapter 05 Big Data Crawling Using Open API
01 Crawling using Naver API
1 What is crawling?
2. Sign up as a Naver developer
3 Naver News Crawling
02 Crawling based on public data API
1. Application for use of public data
2. Public data crawling
summation
Practice problems

Chapter 06 Big Data Crawling Based on Web Page Analysis
01 Crawling static web pages
1. Preparing to crawl static web pages
2. Static Web Page Crawling Practice
02 Dynamic Web Page Crawling
1. Preparing to crawl dynamic web pages
2. Practice crawling dynamic web pages
summation
Practice problems

PART 03 Big Data Analysis - Basic Project

Chapter 07 Statistical Analysis
01 [Technical Statistics Analysis + Graph] Predicting Wine Quality Grades
02 [Correlation Analysis + Heatmap] Analyzing the Titanic's Survival Rates

Chapter 08 Text Frequency Analysis
01 [English Analysis + Word Cloud] Keyword Analysis of English Document Titles
02 [Korean Analysis + Word Cloud] Keyword Analysis of Korean News Articles

Chapter 09 Geographic Information Analysis
01 [Address Data Analysis + Geomap] Creating a Map After Analyzing Geographic Information
02 [Data Analysis by Administrative District + Block Map] Analyzing the Status of Medical Institutions by Administrative District

PART 04 Big Data Analysis - Machine Learning/Deep Learning Projects

Chapter 10 Regression Analysis
01 [Regression Analysis + Scatterplot/Linear Regression Graph] Predicting Vehicle Fuel Efficiency by Item
02 [Linear Regression Analysis + Scatterplot/Linear Regression Graph] Analyzing the Correlation Between Air Pollution Data and Fine Dust

Chapter 11 Classification Analysis
01 [Logistic Regression Analysis] Diagnosing Breast Cancer Using Feature Data
02 [Decision Tree Analysis + Scatterplot/Linear Regression Graph] Classifying Movements Using Sensor Data

Chapter 12 Cluster Analysis
01 [K-Means Clustering Analysis + Graph] Analyzing Consumer Clusters for Targeted Marketing

Chapter 13 Text Mining
01 [Sentiment Analysis Modeling] Modeling Sentiment Analysis Using Movie Review Data
02 [Sentiment Analysis + Bar Chart] Sentiment Analysis of News Text with ChatGPT
03 [Topic Analysis + LDA Topic Model] Analyzing G Chat PT Topics in News Text

Chapter 14 Deep Learning-Based Analysis
01 [LSTM Time Series Analysis] Analyzing Stock Price Time Series
02 [Prophet Time Series Analysis] Predicting Stock Prices 100 Days Ahead
03 [CNN Image Analysis] Classifying Numeric Images
04 [CNN Image Analysis] Classifying Dog Breeds

supplement
01 Installing and Using Anaconda Jupyter Notebook
02 Using Developer Mode
03 Installing the KoNLPy Library

Part 1.
Understanding Big Data Analytics (Chapters 1-3)

Understand the relationship between the Fourth Industrial Revolution, data science, and big data, and understand big data analysis that applies data science methodology.

Part 2.
Big Data Analysis - Preparation (Chapters 4-6)

Learn Python programming required for data science-based big data analysis.
In particular, data crawling using Python is a useful big data collection method, so it is important to learn it well.

Part 3.
Big Data Analysis - Basic Project (Chapters 7-9)

Perform basic big data analysis projects based on an understanding of data science methodology and big data.
We will conduct statistical analysis, text frequency analysis, and geographic information analysis with visualization techniques as a Python project.

Part 4.
Big Data Analysis - Machine Learning/Deep Learning Projects (Chapters 10-14)

First, we carry out a machine learning-based big data analysis project.
We will cover regression analysis and classification analysis, which are supervised learning methods of machine learning, and K-means clustering, which is an unsupervised learning method, as projects, and carry out text mining projects.
In deep learning-based big data analysis, we perform time series analysis using LSTM models and image classification projects using CNN models.

supplement

This guide will guide you through installing and using Anaconda Jupyter Notebook, which is required for project practice.
It also provides how to use developer mode in a web browser and how to install the KoNLPy library for Korean text analysis.