Certificate of Completion

What You Learned

• Explain how neural networks process data through layers, weights, and activation functions
• Describe how backpropagation and gradient descent train a neural network
• Compare the four main architectures — feedforward, CNN, RNN, and transformer — by use case
• Apply regularization techniques (dropout, batch normalization) to prevent overfitting
• Evaluate when to use transfer learning vs training from scratch
• Design a learning path for a deep learning career based on current market demands