Deep Learning with MATLAB Online Course Overview

In this course, you'll use MATLAB to implement common deep learning workflows using real-world image and signal data sets. Deep learning can be used with a variety of applications, like identifying flower species, face detection, and text completion. You'll dive into some of ideas behind deep learning algorithms. You'll create standard network architectures and troubleshoot common training issues. You'll also use deep networks to classify signal data.

This course includes two projects where you'll implement a full workflow using all the techniques you've learned. You'll train networks that classify clothing items from images and use ultrasound sensors to help a robot navigate around a room. This course assumes a basic understanding of transfer learning for image classification. If you've never done deep learning before, or if you'd like a refresher, we recommend you first take Deep Learning Onramp to get you up to speed quickly.

To get started, all you need is a web browser. You'll interact with a web-based version of MATLAB, where you'll receive step-by-step instructions and instant feedback. You can also experiment and try things out on your own. You can do this course at your own pace. Your progress is saved, so you can leave anytime and come back later. And when you're done, you can download a shareable certificate of completion. Start the course today.