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