Lesson 1
Course Introduction
Meet your instructors, get a short overview of what you'll be learning, check your prerequisites, and learn how to use the workspaces and notebooks found throughout the lessons.
Introduction to Neural Networks with PyTorch
Course
Learn the fundamentals of neural networks with Python and PyTorch, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classify new images.
Learn the fundamentals of neural networks with Python and PyTorch, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classify new images.
Skills
Gradient descent
AI algorithms in Python
Training neural networks
NumPy
Beginner
4 weeks
Real-world Projects
Completion Certificate
Last Updated June 8, 2023
Basic descriptive statistics
Python for data science
Course Lessons
Lesson 2
Introduction to Neural Networks
In this lesson, Luis will give you solid foundations on deep learning and neural networks. You'll also implement gradient descent and backpropagation in Python right here in the classroom.
Lesson 3
Implementing Gradient Descent
Mat will introduce you to a different error function and guide you through implementing gradient descent using numpy matrix multiplication.
Lesson 4
Training Neural Networks
Now that you know what neural networks are, in this lesson you will learn several techniques to improve their training.
Lesson 5
Deep Learning with PyTorch
Learn how to use PyTorch for building deep learning models.
Lesson 6 • Project
Create Your Own Image Classifier
In this project, you'll create your own image classifier and then train—and evaluate its performance—using one of the most classic and well-studied computer vision data sets, CIFAR-10.
Taught By The Best
Luis Serrano
Instructor
Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Mat Leonard
Content Developer
Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
Erick Galinkin
Principal AI Researcher | Rapid7
Erick Galinkin is a hacker and computer scientist, leading research at the intersection of security and artificial intelligence at Rapid7. He has spoken at numerous industry and academic conferences on topics ranging from malware development to game theory in security.
Taught By The Best
Luis Serrano
Instructor
Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Mat Leonard
Content Developer
Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
Erick Galinkin
Principal AI Researcher | Rapid7
Erick Galinkin is a hacker and computer scientist, leading research at the intersection of security and artificial intelligence at Rapid7. He has spoken at numerous industry and academic conferences on topics ranging from malware development to game theory in security.
Get Started Today
Introduction to Neural Networks with PyTorch