Month 6: Deep Learning Fundamentals

Week 1: Introduction to Deep Learning

• Recap of Machine Learning and Neural Networks
• Deep Learning architectures and applications
• Overview of Deep Learning frameworks (TensorFlow, Keras, PyTorch)

Week 2: Neural Networks

• Introduction to Neural Networks
• Activation Functions
• Loss Functions
• Backpropagation Algorithm

Week 3: Convolutional Neural Networks (CNNs)

• Introduction to CNNs
• Convolution Layers
• Pooling Layers
• Architecture of CNNs
• Image Classification using CNNs

Week 4: Recurrent Neural Networks (RNNs)

• Introduction to RNNs
• Architecture of RNNs
• Long Short-Term Memory (LSTM) Networks
• Applications of RNNs (e.g., Speech Recognition, Language Modeling)