Skip to main content

Introduction to Deep Learning with PyTorch

Learn to create deep learning models with the PyTorch library.

Start Course for Free
4 Hours17 Videos53 Exercises18,851 Learners4300 XPDeep Learning Track

Create Your Free Account



By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA. You confirm you are at least 16 years old (13 if you are an authorized Classrooms user).

Loved by learners at thousands of companies

Course Description

Neural networks have been at the forefront of Artificial Intelligence research during the last few years, and have provided solutions to many difficult problems like image classification, language translation or Alpha Go. PyTorch is one of the leading deep learning frameworks, being at the same time both powerful and easy to use. In this course you will use PyTorch to first learn about the basic concepts of neural networks, before building your first neural network to predict digits from MNIST dataset. You will then learn about convolutional neural networks, and use them to build much more powerful models which give more accurate results. You will evaluate the results and use different techniques to improve them. Following the course, you will be able to delve deeper into neural networks and start your career in this fascinating field.

  1. 1

    Introduction to PyTorch


    In this first chapter, we introduce basic concepts of neural networks and deep learning using PyTorch library.

    Play Chapter Now
    Introduction to PyTorch
    50 xp
    Creating tensors in PyTorch
    100 xp
    Matrix multiplication
    100 xp
    Forward propagation
    50 xp
    Forward pass
    100 xp
    Backpropagation by auto-differentiation
    50 xp
    Backpropagation by hand
    50 xp
    Backpropagation using PyTorch
    100 xp
    Calculating gradients in PyTorch
    100 xp
    Introduction to Neural Networks
    50 xp
    Your first neural network
    100 xp
    Your first PyTorch neural network
    100 xp

In the following tracks

Deep Learning


hadrien-d4e73b49-bc29-46b7-a485-2f598f38e3b9Hadrien Lacroixhillary-green-lermanHillary Green-Lerman
Ismail Elezi Headshot

Ismail Elezi

Researcher PHD Student at Ca' Foscari University of Venice

I am a third year PhD Student of Deep Learning, supervised by professor Marcello Pelillo at Ca' Foscari, University of Venice. During my PhD, I did an exchange period at ZHAW Datalab (Switzerland) working with professor Thilo Stadelmann. From January on, I am visiting professor's Laura Leal-Taixe lab in Technical University of Munich.
See More

What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA