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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 November 1, 2023

Skills you'll learn:
Generative adversarial networks • Model evaluation • Deep learning techniques • Markov games
Linear algebra • Deep learning fluency • Neural network basics

Courses In This Program

Course 1 45 minutes

Welcome to the Deep Learning Nanodegree Program

The Deep Learning Nanodegree program offers a solid introduction to the world of artificial intelligence. In this program, you’ll master fundamentals that will enable you to go further in the field, launch or advance a career, and join the next generation of deep learning talent that will help define a beneficial, new, AI-powered future for our world. You will study cutting-edge topics such as Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, and build projects in PyTorch.

Course 2 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 3 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 4 4 weeks

RNNs & Transformers

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

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 | 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.

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)

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Deep Learning


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4 Months

Average time to complete a Nanodegree program

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Discount applies to the first 4 months of membership, after which plans are converted to month-to-month.