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Fundamentals of Deep Learning for Computer Vision

Nvidia and Nvidia Deep Learning Institute via Independent


In this hands-on course, you will learn the basics of deep learning by training and deploying neural networks. You will:

- Implement common deep learning workflows such as Image Classification and Object Detection.
- Experiment with data, training parameters, network structure, and other strategies to increase performance and capability.
- Deploy your networks to start solving real-world problems

On completion of this course, you will be able to start solving your own problems with deep learning.

What You'll Learn

  • Identify the ingredients required to start a Deep Learning project.
  • Train a deep neural network to correctly classify images it has never seen before.
  • Deploy deep neural networks into applications.
  • Identify techniques for improving the performance of deep learning applications.
  • Assess the types of problems that are candidates for deep learning.
  • Modify neural networks to change their behavior.


  • Unlocking New Capabilities 
    1. Big Bang in Deep Learning: Introduction 
    2. Deep Neural Networks: 45 minutes 
    3. The GPU:20 minutes 
    4. Big Data: 45 minutes 
  • Creating Applications that Use Deep Learning 
    1. A Deep Learning Project: Introduction 
    2. Simple Deployment: 45 minutes 
  • Measuring and Improving Performance 
    1. Categories of Performance 
    2. Deploying Pretrained Networks 
    3. Beyond Image Classification 
    4. End Of Course 
  • Assessment 
    1. Train and deploy a deep neural network. 
  • Next Steps 
    1. Next Steps 


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