Module 1. - Deep Learning
 - Neual Network 구조이해
 - Deep Learning 이론/구성 요소
 - 딥러닝 프레임워크 개요

Module 2. - TensorFlow
 - TensorFlow 기본 구조
 - TensorFlow 활용한 Liner Regression 실습
 - TensorFlow vs Keras

Module 3. - ANN
 - ANN (Artificial Neural Networks) 개념 / 특징 / 구조 
 - Perceptron & Backpropagation
 - Vanishing Gradient Problem
 - Activation Functions
 - Optimization
 - Loss function

Module 4. - CNN
 - CNN (Convolutional Neural Networks) 개념 / 특징 / 구조
 - Convolutional layers, Activation, Pooling, Batch Normalization, Dropout
 - RNN (Recurrent Neural Network) 개념 / 특징 / 구조
 - LSTM Architecture 개념 