[Introduction] The First Step to Data Literacy with AI

[Chapter 1] Understanding Data Literacy and Data Analysis

Questions to consider
1.
Generative AI and Data Literacy
2.
Understanding Data and Data Types
3.
Data Analysis Using Generative AI
4.
Data Analysis Using ChatGPT
Organize

[Chapter 2] Understanding Market Research and Primary Data Collection Methods

Questions to consider
1.
The Difference Between Market Research and Marketing Research
2.
Research Process and Research Design
3.
The relationship between research purpose, data collection, and analysis
4.
Things to keep in mind when filling out the questionnaire
5.
Market Research Using ChatGPT
6.
Survey using Google Forms
Organize

[Chapter 3] Understanding Secondary Data Collection Methods and Data Preprocessing

Questions to consider
1.
Secondary data and public data
2.
Web Data Collection: Web Scraping
3.
Data preprocessing
4.
Public data collection
5.
Web data collection using ChatGPT
6.
Data preprocessing using ChatGPT
7.
Data Preprocessing Using Power Query
Organize

[Chapter 4] Exploratory Data Analysis and Understanding Data Characteristics

Questions to consider
1.
Comparing Exploratory and Confirmatory Data Analysis
2.
Understanding Exploratory Data Analysis
3.
Statistics as an exploratory process for problem solving and decision making
4.
Basic Statistics for Data Analysis
5.
Procedure for conducting exploratory data analysis
6.
Exploratory Data Analysis Using ChatGPT
Organize

[Chapter 5] Understanding Statistical Hypothesis Testing and A/B Testing

Questions to consider
1.
Understanding Statistics: Descriptive and Inferential Statistics
2.
Statistical hypothesis testing
3.
A/B testing
4.
Statistical hypothesis testing using ChatGPT
5.
A/B Testing Analysis Using ChatGPT
Organize

[Chapter 6] Understanding Correlation and Association

Questions to consider
1.
Understanding the relationship between variables
2.
Correlation Analysis: Correlation Analysis
3.
Case Study: Finding Product Relationships Using Purchase History Data
4.
Understanding scatter plots to understand the relationship between two variables
5.
Data collection and data preprocessing for correlation analysis
6.
Correlation Analysis Using ChatGPT
Organize

[Chapter 7] Understanding Causal Relationships and Predictive Analytics

Questions to consider
1.
Understanding Regression Analysis
2.
Regression analysis methods and regression models
3.
Case Study: Causal Relationship Between Store Area and Gross Profit
4.
Regression analysis using ChatGPT
5.
Sales prediction model using ChatGPT
6.
Building a sales prediction model
7.
Predictive model performance evaluation
8.
Predictive model creation and Excel simulation
Organize

[Chapter 8] Understanding Cluster Analysis and Customer Segmentation

Questions to consider
1.
Understanding Cluster Analysis
2.
Key techniques (algorithms) for cluster analysis
3.
Customer segmentation and target marketing
4.
Customer Analysis Model and Segmentation Analysis Process
5.
Cluster Analysis Using ChatGPT
6.
Customer Profiling Using ChatGPT
Organize

[Chapter 9] Understanding Text Data Analysis and Text Mining

Questions to consider
1.
Understanding Text Data Analysis
2.
Morphological analysis
3.
Search trend analysis
4.
Sentiment (positive/negative) analysis
5.
Associated word analysis
6.
Word Cloud Analysis
7.
Text data preprocessing using ChatGPT
8.
Text Clustering and Improvement Using ChatGPT
Organize

[Chapter 10] Understanding Visualization Analysis and Data-Driven Conclusions

Questions to consider
1.
Understanding Data Visualization
2.
Elements and types of charts for data visualization
3.
Data-driven conclusions
4.
Visualization Analysis Using ChatGPT
5.
Creating data analysis reports using ChatGPT and AI tools
6.
Data-driven thinking for problem solving
Organize

[Conclusion] A New Future Opened by Data Literacy

Key points and features of this book

1. Connecting AI and Data: Everything You Need to Know About ChatGPT

ChatGPT is a new data analysis tool that streamlines a variety of data tasks, from data collection to exploratory data analysis (EDA), regression analysis, text mining, and data visualization.
This book will help you systematically perform the following tasks using ChatGPT.

- Data collection: How to efficiently collect data by collecting web data or through Google Forms.
- Data preprocessing: Converting data into a form suitable for analysis through data cleaning and quality improvement.
Exploratory Data Analysis (EDA): Visually explore data to discover insights.
- Regression analysis and predictive modeling: Analyzing relationships and predicting the future based on data.
Text Mining: Use unstructured text data to analyze sentiment, analyze related words, and discover trends.
- Data visualization: Create charts and graphs to intuitively convey analysis results.

With real-world examples and cases using ChatGPT, even complex processes can be easily understood and followed.

2.
Hands-on Learning: Data Analysis Learned by Doing

We maximize learning effectiveness by providing practical examples and materials that can be applied immediately in practice, as well as theory.


Case study using movie audience data: Understanding market trends and deriving insights through data.
- Sentiment Analysis Practice Using Text Data: Positive/Negative Sentiment Analysis Using Customer Review Data
Visualization Analysis Using Real Data: Learn how to clearly and effectively present analysis results.

The practice materials are organized step by step so even beginners can follow along without difficulty.

3.
Discovering Innovative Insights Through Data

This book goes beyond simple data interpretation, and guides you through discovering hidden meaning and patterns in data.
Data is a key resource for making better decisions in today's businesses and daily lives.
This book provides practical guidance on how to leverage insights gained through AI and data to solve business problems and drive innovative results.

4.
Data literacy that anyone can easily start

This book is structured so that even beginners with no data analysis experience can easily understand it.
We focus on lowering the barriers to AI technology and data analysis by covering the basics step by step and utilizing familiar tools like ChatGPT.
With this book, data analysis is no longer the domain of experts.

What you'll learn: The entire process of data analysis

This book systematically organizes the entire process of handling data, helping even data beginners grow to expert level.

1.
Data collection and preprocessing
Leveraging public data and web scraping
Collecting data with Google Forms and ChatGPT
Cleanse and prepare data into a format suitable for analysis

2.
Exploratory Data Analysis (EDA)
Visualize data, explore patterns, and discover insights.
Solve problems by combining basic statistics and visualization.

3.
Regression analysis and predictive modeling
Understand relationships between data and predict the future
Learning from real-world examples, such as store sales and customer behavior prediction.

4.
Text Mining and Sentiment Analysis
Trend and sentiment analysis using text data
Analytical practice based on customer reviews and social media data

5.
Data visualization and reporting
Communicate data effectively by visually representing it
Reporting with ChatGPT and AI Tools


This book is recommended for these people!

- Complete beginner who is new to data
- Employees who want to improve work performance by utilizing AI technology and data.
- College students and researchers who require data analysis skills for projects and research.
- Managers and practitioners who must make data-driven decisions
- Those who want to easily start data analysis using ChatGPT and AI

What you can gain from reading this book

1.
You can learn analytical skills using data and AI.

2.
It can enhance your data-driven decision-making capabilities.

3. You can develop the data literacy skills necessary to survive in the AI ​​era.
4.
Learn practical data analysis skills that can be immediately applied in your work and business.

Harness the power of data and AI to prepare for the future!

"Data Literacy with ChatGPT" provides methods for developing AI- and data-driven analytical capabilities and applying them to real-life situations and businesses.
This book is more than just a textbook; it's a guidebook and practical guide to the new world of data analysis. Discover growth opportunities in your business and daily life through AI and data, and create a better future.
Become a data expert in the AI ​​era with this book!

[ Free download of practice materials ]
The data files and document files used in the text can be downloaded from Google Drive and the publisher's website.
* https://bit.ly/3UNvWtw
* https://www.pub365.co.kr
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