Device-based Models with TensorFlow Lite

DeepLearning.AI studies model execution on devices through TensorFlow Lite. Android and iOS modules connect a trained model with mobile application code, followed by other device scenarios. The course is useful for comparing on-device inference with a remote model request.

What you will learn

• Explain a device-based model workflow.
• Integrate model inference with an Android application.
• Compare the corresponding iOS or other-device setup.

Who this suits

Intermediate learners with a basic understanding of Kotlin or Swift.

Before you enroll

Check the TensorFlow and Keras versions used by the notebooks. APIs and model formats can change; reproduce a small example before investing time in a larger project.

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Put it into practice

Measure a small on-device model’s latency and memory use. Test how the interface behaves before model loading finishes or when an input is invalid.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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