Course Outline


  • ML Kit vs TensorFlow vs other machine learning services
  • Overview of ML Kit features and components

Getting Started

  • Setting up the ML Kit SDK
  • Exploring APIs and sample apps

Implementing ML Kit Vision APIs

  • Automating data entry (Text Recognition)
  • Detecting faces for selfies and portraits (Face Detection)
  • Interpreting body positions (Pose Detection)
  • Adding background effects (Selfie Segmentation)
  • Integrating Barcode Scanning
  • Identifying objects, places, species, etc. (Image Labeling)
  • Locating prominent objects in an image (Object Detection and Tracking)
  • Recognizing handwritten texts (Digital Ink Recognition)

Working with Natural Language APIs

  • Identifying languages
  • Translating texts
  • Generating smart replies
  • Using entity extraction

Optimizing Existing Apps with ML Kit

  • Using custom models with ML Kit
  • Migrating from Firebase to the new ML Kit SDK
  • Migrating from Mobile Vision to ML Kit SDK
  • Reducing app size for deployment
  • Refactoring apps to use dynamic feature modules

Troubleshooting Tips

Summary and Next Steps


  • An understanding of machine learning
  • Experience with mobile development


  • Software Engineers
  • Mobile App Developers
 14 Hours

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