Benefits of the Self-Paced Format

Step-by-step instruction

Hands-on exercises with automated feedback

Access to MATLAB through your web browser

Shareable progress report and course certificate

About This Course

 Lessons are available in English and Japanese.


Classifying Images with Convolutional Networks

Get an overview of the course. Perform image classification using pretrained networks. Use transfer learning to train customized classification networks.

30 mins


Interpreting Network Behavior

Gain insight into how a network is operating by visualizing image data as it passes through the network. Apply this technique to different kinds of images.

45 mins


Creating Networks

Build convolutional networks from scratch. Understand how information is passed between network layers and how different types of layers work.

45 mins


Training Networks

Understand how training algorithms work. Set training options to monitor and control training.

30 mins


Improving Performance

Choose and implement modifications to training algorithm options, network architecture, or training data to improve network performance.

30 mins



15 mins


Performing Regression

Create convolutional networks that can predict continuous numeric responses.

30 mins


Using Deep Learning for Computer Vision

Train networks to locate and label specific objects within images.

45 mins


Classifying Sequence Data with Recurrent Networks

Build and train networks to perform classification on ordered sequences of data, such as time-series or sensor data.

45 mins


Classifying Categorical Sequences

Use recurrent networks to classify sequences of categorical data, such as text.

30 mins


Generating Sequences of Output

Use recurrent networks to create sequences of predictions.

45 mins



15 mins

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