Neural Networks and Deep Learning (Coursera)

When you finish this class, you will:

- Understand the major technology trends driving Deep Learning

- Be able to build, train and apply fully connected deep neural networks

- Know how to implement efficient (vectorized) neural networks

- Understand the key parameters in a neural network's architecture

This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions.

Course 1 of 5 in the Deep Learning Specialization.

Syllabus

WEEK 1

Introduction to deep learning

Be able to explain the major trends driving the rise of deep learning, and understand where and how it is applied today.

WEEK 2

Neural Networks Basics

Learn to set up a machine learning problem with a neural network mindset. Learn to use vectorization to speed up your models.

WEEK 3

Shallow neural networks

Learn to 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 it to computer vision.