Udemy

Train & Deploy TFLite Object Detection for Android (2025)

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  • 162 Students
  • Updated 6/2025
4.4
(23 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
8 Hour(s) 11 Minute(s)
Language
English
Taught by
Mobile ML Academy by Hamza Asif
Rating
4.4
(23 Ratings)
1 views

Course Overview

Train & Deploy TFLite Object Detection for Android (2025)

Train custom object detection models and deploy them in Android apps using TensorFlow Lite, Kotlin & Java in Realtime

Mobile AI is shifting from cloud to on-device. With TensorFlow Lite (TFLite) you can run real-time object detection directly on Android phones—no server, zero latency. This course gives you an end-to-end workflow to train, convert, and deploy custom models using Kotlin and Java.


What You’ll Master

  • Data Collection & Annotation
    Capture images and label them with LabelImg, CVAT, or Roboflow to create high-quality datasets.

  • Model Training in TensorFlow / YOLO / EfficientDet / SSD-MobileNet
    Hands-on Colab notebooks show you how to train from scratch or fine-tune pre-trained weights.

  • TFLite Conversion & Optimization
    Quantize, prune, and add metadata for maximum FPS and minimum battery drain.

  • Android Integration (CameraX + ML Model Binding)
    Build apps in Kotlin or Java that detect objects in both images and live camera streams.

  • Using Pre-Trained Models
    Plug in ready-made YOLOv8-Nano, EfficientDet-Lite, or SSD-MobileNet with just a few lines of code.


Included Resources

  • Production-ready Android templates (Kotlin & Java) worth $1,000+

  • Re-usable model-conversion scripts and Colab notebooks

  • Pre-annotated sample dataset to get you started fast

  • Cheatsheets for common TFLite errors and performance tuning


Real-World Use-Cases You’ll Build

  • Smart CCTV with intrusion alerts

  • Industrial defect detection on assembly lines

  • Crowd counting & retail analytics dashboards

  • Prototype modules for self-driving or AR apps


Who Should Enroll?

  • Android developers eager to add on-device AI (beginner to pro)

  • ML engineers targeting mobile deployment and edge-AI optimization

  • Makers, startup founders, or hobbyists who want to build vision-powered apps without a backend


What You Need

  • Basic Android Studio familiarity (layouts, activities, Gradle)

  • Light Python knowledge (all heavy lifting handled in the provided notebooks)

  • A computer with 8 GB RAM—heavy training runs on free Google Colab GPUs


Course Format

  • 1080p HD video lectures (updated for Android Studio 2025 & TensorFlow Lite 3.x)

  • Mini-projects after each section to cement skills

  • Lifetime access, Q&A support, and Udemy’s 30-day money-back guarantee

Ready to build fast, reliable object-detection apps that run entirely on Android devices?
Click Buy Now and start training & deploying your own TFLite models today!

Course Content

  • 10 section(s)
  • 103 lecture(s)
  • Section 1 Introduction
  • Section 2 Dataset Collection and Annotation for Object Detection Model Training
  • Section 3 Training Custom Object Detection models for Android Apps
  • Section 4 Java: Choose or Capture Images in Android
  • Section 5 Kotlin: Choose or Capture Images in Android
  • Section 6 Java: Object Detection with Images for Android App Development
  • Section 7 Kotlin: Object Detection with Images for Android App Development
  • Section 8 Java: Object Detection with Live Camera Footage in Android
  • Section 9 Kotlin: Real Time Object Detection in Android
  • Section 10 Java: EfficientDet Models for Object Detection in Android App Development

What You’ll Learn

  • Train Object Detection Models from Scratch and Convert them to Tensorflow Lite Format
  • Use Trained Object Detection Models in Android (Java / Kotlin) with both Images and Videos
  • Learn to Collect and Annotate Datasets for Training Object Detection Models
  • Learn basics of Object Detection ,its applications and Machine Learning for Training Machine Learning Models for Mobile Devices
  • Learn to use SSD EfficientDet Models in Android (Java / Kotlin) for Object Detection
  • Learn to use SSD MobileNet Models in Android (Java / Kotlin) for Object Detection
  • Learn use of YOLO Models in Android (Java / Kotlin) for Object Detection


Reviews

  • U
    U 2
    1.0

    Some parts of the training are outdated and don't work - I tried to contact the trainer (and I not alone, others have the same probem) but I have zero answer - Avoid this course

  • B
    Brian Aboytes Morales
    1.0

    Titulo del curso engañoso, dice 2025 y todo es del 2022/2023 con librerías obsoletas que ya nofuncionan.

  • N
    Nguyen Minh Hung
    5.0

    thanks

  • J
    Jonathan Cruz
    5.0

    the best

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