Android apps with artificial Intelligence

Overview

In this course, you will learn how to build Android applications and also learn about MLkit to use artificial intelligen in your application . Here we will make three applications , all of which use mlkit .

You do not need strong experience in programming or artificial intelligence and machine learning , just a simple experience where we will explain from scratch . In each section you will find its own code .

The most important thing is that you apply every example we take in practice to do this, you must download the Android studio program In the course, we will talk a little about Python and how to train models after that we will use Android studio to build applications . we will use kotlin to build these applications . We will also learn how to design the user interface to our app .

The first application will be about classifying the state of the eye, whether it is closed or open the second application will be about how to identify the contents of images the last application will be about identifying objects in any imageEach one of these applications will teach you a lot of things and techniques that you can use elsewhere, for example uploading images or taking photos, in addition to learning the mlkit library.

Syllabus

• Introduction to Android App Development
Setting up Android Studio
Overview of Kotlin for Android
Basics of Android UI Design
• Introduction to Machine Learning and ML Kit
Basics of Machine Learning
Overview of Google's ML Kit
Setting up ML Kit in Android Projects
• Application 1: Eye State Classification
Understanding the Eye State Model
Building the User Interface
Integrating ML Kit for Eye State Detection
Testing and Debugging the Application
• Basics of Python for Machine Learning
Introduction to Python for AI
Overview of Model Training
Training Simple Models with Python
• Application 2: Image Content Identification
Introduction to Image Content Analysis
Designing the App Interface
Implementing ML Kit for Image Content Recognition
Handling Image Uploads and Captures
• Application 3: Object Detection in Images
Object Detection Fundamentals
Creating the User Interface
Utilizing ML Kit for Object Detection
Fine-tuning Model Performance
• Advanced Features and Techniques
Exploring Additional ML Kit Features
Enhancing App Performance
User Experience Design for AI Apps
• Final Project and Course Wrap-up
Building a Custom AI-Driven Android App
Review of Key Concepts and Techniques
Future Trends in AI and Android Development

Taught by

Riad Almadani • 30,000+ Students

Subjects

Programming