What You'll Learn

17 Chapters · 18 Lessons

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      Introduction to Kotlin and AI in Mobile Apps

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      Understanding Kotlin Basics

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      Deep Dive into Kotlin

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      Building Your First Android App

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      Getting Started with Machine Learning

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      Deep Learning For Mobile Apps

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      Natural Language Processing on Mobile with LiteRT

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      Object Detection and Image Segmentation

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      Recommendation System and Personalization

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      Designing User-Centric AI Apps

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      Project: Sentiment Analysis of User Input with TensorFlow

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      Image Processing Using ML Kit

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      Project: Contextual AI Assistant

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      Testing and Optimization

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      Deploying Your AI App

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      The Future of AI in Mobile Apps

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      Index

About This Course

Don't Just Build Android Apps. Build Apps with Intelligence. AI-powered mobile applications are no longer the domain of specialists — and Android developers who can integrate on-device ML, generative AI, and conversational interfaces are defining the next generation of intelligent apps. Ultimate AI-Powered App Development with Kotlin takes you from Kotlin fundamentals and Android essentials through machine learning (ML), on-device AI, LiteRT, ML Kit, and modern AI services, including Gemini and ChatGPT. The book takes a hands-on approach with practical projects showing how these technologies work together in real Android applications. You build a sentiment analysis app, an on-device recommendation system, and a conversational AI application using Gemini and ChatGPT, learning how to integrate models, work with AI services, optimize applications for mobile devices, and create responsive interfaces with Jetpack Compose throughout. By the end, you will be able to design, build, test, optimize, and deploy AI-powered Android applications with the practical skills needed to bring intelligent features to production mobile products.

Meet Your Instructor

Pankaj Kumar is a Mobile Architect with 15+ years of experience designing secure, scalable mobile applications across Banking, FinTech, and PropTech. His expertise spans Android, Kotlin, mobile architecture, security, performance, LiteRT, model optimization, and AI integration. He has led engineering teams and built AI-powered products, with a focus on AI guardrails and responsible AI integration.