1.
introduction

1.1.
Definition of artificial intelligence
1.2.
History of Artificial Intelligence

2.
Basic principles of artificial intelligence

2.1.
Data and Algorithms
2.1.1.
Data
2.1.2.
Algorithm
2.1.3.
Data and Algorithms
2.2.
Big Data and Machine Learning
2.2.1.
Big data
2.2.2.
machine learning
2.3.
Artificial neural networks and deep learning
2.3.1.
artificial neural network
2.3.2.
Deep Learning (DL)
2.3.3.
Major deep learning models
2.4.
Major Applications of Artificial Intelligence
2.4.1.
Natural Language Processing (NLP)
2.4.2.
Computer Vision

3.
Python and Machine Learning

3.1.
Python programming environment (Colab)
3.2.
Python Basics for Practice
3.2.1.
Declaration, assignment, and reference of variables
3.2.2.
function
3.2.3.
library
3.2.3.
Scikit-learn library and SVM
3.3 Tensorflow Playground

4.
Applications of artificial intelligence

4.1.
Use of artificial intelligence technology in the private sector
4.1.1. Smart Factory
4.1.2 Finance and Economy
4.1.3 Distribution and Retail
4.1.4 Entertainment and Media
4.2.
Utilization of artificial intelligence technology in the defense sector
4.2.1.
USA
4.2.2.
Israel
4.2.3.
Ukraine
4.3.
Case studies of artificial intelligence in South Korea's defense sector
4.3.1.
Defense and military sector
4.3.2.
Smart Factory
4.3.3.
Smart Warehouse
4.3.4.
Vigilance and Surveillance Support System
4.3.5.
Defense Medical Field
4.3.6.
Business innovation
4.3.7.
Training field

5. The Future of Artificial Intelligence

5.1.
Problems with artificial intelligence
5.1.1.
Data issues
5.1.2.
Black box problem
5.1.3.
Overfitting
5.1.4.
lack of flexibility
5.1.5.
ethical and social issues
5.2.
AI ethics
5.2.1 The Importance of AI Ethics
5.2.2 Key Issues in AI Ethics
5.2.3 Guidelines for Artificial Intelligence Ethics