Skip to content
MathWorks

Self-Paced Online Courses

  • Self-Paced Content
  • MathWorks
  • MATLAB Help Center
  • Community
  • Learning
  • Get MATLAB MATLAB
  • Sign In
    • My Account
    • My Community Profile
    • Link License

    • Sign Out
  • Contact MathWorks Support
  • Visit mathworks.com
  • Online Courses
MathWorks MathWorks

Select a Web Site

Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .

  • (English)
  • (Deutsch)
  • (Français)
  • (简体中文)
  • (English)

You can also select a web site from the following list

How to Get Best Site Performance

Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.

Americas

  • América Latina (Español)
  • Canada (English)
  • United States (English)

Europe

  • Belgium (English)
  • Denmark (English)
  • Deutschland (Deutsch)
  • España (Español)
  • Finland (English)
  • France (Français)
  • Ireland (English)
  • Italia (Italiano)
  • Luxembourg (English)
  • Netherlands (English)
  • Norway (English)
  • Österreich (Deutsch)
  • Portugal (English)
  • Sweden (English)
  • Switzerland
    • Deutsch
    • English
    • Français
  • United Kingdom (English)

Asia Pacific

  • Australia (English)
  • India (English)
  • New Zealand (English)
  • 中国
    • 简体中文
    • English
  • 日本 (日本語)
  • 한국 (한국어)

Contact your local office

image for course Deep Learning Onramp

Deep Learning Onramp

Learn the basics of deep learning for image classification problems in MATLAB®. Use a deep neural network that experts have trained and customize the network to group your images into predefined categories.

Course modules

Introduction

Familiarize yourself with deep learning concepts and the course.

Lessons:
  • Course Overview
  • Outline and Learning Outcomes

Use Pretrained Networks

Perform classifications using an existing network that was previously trained.

Lessons:
  • View Image Files
  • Make Predictions
  • Obtain Pretrained Networks
  • What is a CNN?
  • Examine Predictions

Manage Collections of Image Data

Organize and process images to use them with a pretrained network.

Lessons:
  • What is a Datastore?
  • Create and Classify a Datastore
  • Adjust Input Images
  • Workflow for Processing Images
  • Resize Images in a Datastore
  • Preprocess Color Using a Datastore
  • Augmented Training Data
  • Create a Datastore Using Subfolders

Prepare Inputs for Transfer Learning

Create all of the components needed to update a pretrained network to classify a new image data set.

Lessons:
  • What is Transfer Learning?
  • Components Needed for Transfer Learning
  • Label Images in a Datastore
  • Split Data for Training and Testing
  • CNN Layers
  • Set the Number of Classes
  • Set Training Options

Perform Transfer Learning

Train and evaluate a deep network.

Lessons:
  • Perform Training
  • Train the Network
  • Investigate the Trained Network
  • Evaluate the Test Performance
  • Improve Performance
  • On Your Own: Classify Roundworms

Conclusion

Learn next steps and give feedback on the course.

Lessons:
  • Summary
  • More Deep Learning Applications
  • Survey

Format:Self-paced

Language:English

Language

  • Hands-on exercises with automated feedback
  • Access to MATLAB through your web browser
  • Shareable progress report and course certificate

Machine Learning Onramp

Learn the basics of practical machine learning methods for classification problems.

Reinforcement Learning Onramp

Master the basics of creating intelligent controllers that learn from experience.

MATLAB Onramp

Get started quickly with the basics of MATLAB.

  • Trust Center
  • Trademarks
  • Privacy Policy
  • Preventing Piracy
  • Application Status
  • Contact Us

© 1994-2025 The MathWorks, Inc.