Udemy – The Complete Android 16 Course [Part 3] – Become a Master 2025-12

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Description

The Complete Android 16 Course [Part 3] – Become a Master. This course is the third part of the Android App Development series and covers advanced Android engineering and machine learning on the device. This course is designed for developers who want to go beyond traditional apps and develop intelligent, production-grade Android apps that include mapping systems, real-time data, and machine learning models. Students will first learn advanced Google Maps integration and learn how to build Uber-like apps that handle live location tracking, camera movement, markers, linear routing, and UI optimization. The course then dives deeper into machine learning on Android, focusing on end-to-end workflows, dataset preparation, custom model training, model optimization in TensorFlow Lite, and efficient deployment on Android devices. Another major focus of this course is on machine vision and object recognition using industry standard architectures such as SSD MobileNet and YOLO. Learners will also learn critical optimization techniques for mobile performance, model size reduction, and resource management. The course is project-based, and all core concepts are implemented directly on Android to provide a clear understanding of how machine learning, machine vision, and Android development work in real products.

What you will learn

Building advanced map-based Android applications
Implementing AI-based capabilities using machine learning on the device
Creating and deploying custom TFLite object recognition models
Develop real-time, production-ready AI-powered Android apps
Significantly improving Android and AI skill sets

This course is suitable for people who:

Intermediate Android developers who know the basics of Android and want to move on to advanced real-world app development.
Android programmers interested in machine learning, machine vision, and AI-powered mobile apps.
Developers who want to integrate Google Maps and build location-based apps similar to Uber.
Beginners in machine learning who want to apply machine learning concepts practically in Android apps.
Developers who want to create, train, and deploy custom machine learning models using TensorFlow Lite.
Android engineers who plan to build object recognition applications, including custom models of YOLO and SSD MobileNet.