Udacity Logo
Log InJoin for Free

Deep Learning

Nanodegree Program

This Nanodegree trains the learner about foundational topics in the exciting field of deep learning, the technology behind state-of-the-art artificial intelligence.

This Nanodegree trains the learner about foundational topics in the exciting field of deep learning, the technology behind state-of-the-art artificial intelligence.


4 months

Real-world Projects

Completion Certificate

Last Updated January 22, 2024

Skills you'll learn:
Generative adversarial networks • Model evaluation • Deep learning techniques • Markov games
Python proficiency • Pandas • Matrix multiplication

Courses In This Program

Course 1 4 weeks

Introduction to Deep Learning

This course covers foundational deep learning theory and practice. We begin with how to think about deep learning and when it is the right tool to use. The course covers the fundamental algorithms of deep learning, deep learning architecture and goals, and interweaves the theory with implementation in PyTorch.

Course 2 4 weeks

Convolutional Neural Networks

This course introduces Convolutional Neural Networks, the most widely used type of neural networks specialized in image processing. You will learn the main characteristics of CNNs that make them so useful for image processing, their inner workings, and how to build them from scratch to complete image classification tasks. You will learn what are the most successful CNN architectures, and what are their main characteristics. You will apply these architectures to custom datasets using transfer learning. You will also learn about autoencoders, a very important architecture at the basis of many modern CNNs, and how to use them for anomaly detection as well as image denoising. Finally, you will learn how to use CNNs for object detection and semantic segmentation.

Course 3 4 weeks

RNNs and Transformers

This course covers multiple RNN architectures and discusses design patterns for those models. You'll also learn about transformer architectures.

Course 4 4 weeks

Building Generative Adversarial Networks

Learn to understand and implement a Deep Convolutional GAN (generative adversarial network) to generate realistic images, with Ian Goodfellow, the inventor of GANs, and Jun-Yan Zhu, the creator of CycleGANs.

Taught By The Best

Photo of Giacomo Vianello

Giacomo Vianello

Principal Data Scientist

Giacomo Vianello is an end-to-end data scientist with a passion for state-of-the-art but practical technical solutions. He is Principal Data Scientist at Cape Analytics, where he develops AI systems to extract intelligence from geospatial imagery bringing, cutting-edge AI solutions to the insurance and real estate industries.

Photo of Nathan Klarer

Nathan Klarer

Head of ML & COO of Datyra

Nathan is a data scientist and entrepreneur. He currently leads a Datyra, a 50-person AI consultancy. He was the first AI team member at $CORZ. Prior to that he founded a VC backed data startup that was acquired. Nathan was named “27 CEO's Under 27” by Entrepreneur.com and has been featured in Inc. and Forbes.

Photo of Erick Galinkin

Erick Galinkin

Principal AI Researcher

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.

Photo of Thomas Hossler

Thomas Hossler

Sr Deep Learning Engineer

Thomas is originally a geophysicist but his passion for Computer Vision led him to become a Deep Learning engineer at various startups. By creating online courses, he is hoping to make education more accessible. When he is not coding, Thomas can be found in the mountains skiing or climbing.

Ratings & Reviews

Average Rating: 4.7 Stars

(909 Reviews)

Page 1 of 181

The Udacity Difference

Combine technology training for employees with industry experts, mentors, and projects, for critical thinking that pushes innovation. Our proven upskilling system goes after success—relentlessly.

Demonstrate proficiency with practical projects

Projects are based on real-world scenarios and challenges, allowing you to apply the skills you learn to practical situations, while giving you real hands-on experience.

  • Gain proven experience

  • Retain knowledge longer

  • Apply new skills immediately

Top-tier services to ensure learner success

Reviewers provide timely and constructive feedback on your project submissions, highlighting areas of improvement and offering practical tips to enhance your work.

  • Get help from subject matter experts

  • Learn industry best practices

  • Gain valuable insights and improve your skills