Android Development Using Machine Learning

Core Periods Modules

The Android Development Using Machine Learning Specialization is structured into several modules that progressively build knowledge and skills. The program begins with an introduction to Android development, where participants learn the fundamentals of building Android apps and the Android Studio environment. Following this, the program dives into machine learning concepts, introducing tools and techniques like TensorFlow Lite for integrating machine learning models into Android apps. Participants will also cover key topics such as image recognition, speech-to-text, and natural language processing (NLP) within mobile applications. As the program progresses, participants will explore advanced Android development techniques and learn how to optimize machine learning models for mobile devices to ensure efficient and effective performance. The specialization emphasizes hands-on learning, allowing students to work on projects that involve building real-world applications like chatbots, image classifiers, and recommendation systems. By the end of the program, learners will complete a capstone project to demonstrate their mastery of Android development and machine learning integration, preparing them for professional roles in the mobile development and AI industries.

1. Period 0

   Introduction to Android Development

   This module covers the basics of Android development, including setting up Android Studio, understanding the architecture of Android apps, and the fundamental components like Activities, Fragments, and Views. Learners will build simple applications to get familiar with the development environment.

2. Period 1

   Integrating Machine Learning with Android

   In this module, participants learn how to integrate machine learning models into Android apps using TensorFlow Lite. They'll explore how to convert pre-trained models into a mobile-friendly format and use them to add intelligent features such as image and text recognition.

3. Period 2

   Image Recognition with Android

   This module focuses on integrating image recognition capabilities into Android apps. Learners will use machine learning techniques to classify and label images in real-time using TensorFlow Lite, exploring object detection and image classification for various use cases.

4. Period 3

   Speech Recognition and Natural Language Processing (NLP)

   learn how to implement speech-to-text and text-to-speech functionalities, as well as how to use NLP for tasks like sentiment analysis and language translation. They will use Android's speech recognition APIs and external libraries like TensorFlow to enhance app capabilities.

5. Period 4

   Optimizing Machine Learning Models for Mobile

   This module teaches participants how to optimize machine learning models for mobile devices. They will explore techniques such as quantization and pruning to make models smaller and faster, ensuring efficient performance on Android devices without compromising accuracy.

6. Period 5

   Building an AI-Powered Android App

   In this final module, You will apply their knowledge to develop a complete Android application that leverages machine learning. They will work on a real-world project, such as a chatbot, recommendation system, or AI-based photo editor, and demonstrate their skills in integrating AI with Android development.