
Course 1: Neural Networks and Deep Learning
In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning.
By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications.
Week 1: Introduction to Deep Learning
Understand the significant technological trends driving deep learning development and where and how it’s applied.
Week 2: Neural Networks Basics
Set up a machine learning problem with a neural network mindset and use vectorization to speed up your models.
Week 3: Shallow Neural Networks
Build a neural network with one hidden layer using forward propagation and backpropagation.
Week 4: Deep Neural Networks
Understand the key computations underlying deep learning, use them to build and train deep neural networks, and apply them to computer vision.