Lesson 1: Introduction to Deep Learning
Lesson 2: Artificial Neural Networks (ANNs)
Lesson 3: Activation Functions
Lesson 4: Cost Functions
Lesson 5: Backpropagation Algorithm
Lesson 6: Optimization Algorithms (Gradient Descent, Adam, RMSprop)
Lesson 7: Convolutional Neural Networks (CNNs)
Lesson 8: Recurrent Neural Networks (RNNs)
Lesson 9: Long Short-Term Memory (LSTM) Networks

Lesson 1: Regularization Techniques: Dropout, L2 Regularization
Lesson 2: Batch Normalization
Lesson 3: Transfer Learning
Lesson 4: Autoencoders Variational Autoencoders (VAEs)
Lesson 5: Generative Adversarial Networks (GANs)
Lesson 6: Deep Reinforcement Learning

Lesson 1: Image Classification
Lesson 2: Object Detection
Lesson 3: Semantic Segmentation
Lesson 4: Instance Segmentation
Lesson 5: Face Recognition
Lesson 6: Image Generation
Lesson 7: Style Transfer

Lesson 1: Word Embeddings (Word2Vec, GloVe)
Lesson 2: Recurrent Neural Networks (RNNs) for Sequence Modeling
Lesson 3: Long Short-Term Memory (LSTM) Networks for Text Generation
Lesson 4: Attention Mechanisms
Lesson 5: Named Entity Recognition (NER)
Lesson 6: Sentiment Analysis
Lesson 7: Machine Translation