Use PyTorch to implement your first deep neural network
Build cutting-edge AI projects supported by dedicated mentors.
In this course, you’ll learn the basics of deep learning, and build your own deep neural networks using PyTorch. You’ll get practical experience with PyTorch through coding exercises and projects implementing state-of-the-art AI applications such as style transfer and text generation.
Rich Learning Content
Taught by Industry Pros
With the skills you learn in this course, you’ll be ready to take on the complex challenges in our Deep Learning Nanodegree program, as you build towards a career in data science or machine learning.
Learn the basics of deep learning and implement your own deep neural networks with PyTorch.
To succeed in this course, you’ll need to be comfortable with Python and data processing libraries such as NumPy and Matplotlib. Basic knowledge of linear algebra and calculus is recommended, but isn’t required to complete the exercises.
See the Technology Requirements for using Udacity.
Deep learning is driving the AI revolution and PyTorch is making it easier than ever for anyone to build deep learning applications. In this course, you’ll gain practical experience building and training deep neural networks using PyTorch. You’ll be able to use these skills on your own personal projects.
Learn more about AI Skill gapsDownload Report