Stop building simple API wrappers. Learn to build intelligent, context-aware AI applications that run natively on Android.

In the era of Generative AI, the most valuable skill isn't just "calling an API"—it's creating applications that understand your data. This comprehensive, project-based course takes you on a journey from zero to a deployed Android application. You will learn how to build a Retrieval-Augmented Generation (RAG) system that allows users to chat with their own PDF documents, company policies, or custom knowledge bases.

We don't just stop at the Python script. We bridge the gap between AI and Mobile Development, teaching you how to connect a powerful Python FastAPI backend to a sleek, professional React Native Android app.

🎯 What You Will Learn

• Master RAG Architecture: Understand the core concepts of ingestion, chunking, embeddings, and vector retrieval.

• Build a Robust AI Backend: Use Python, FastAPI, and LangChain to build a server that can process documents and answer questions accurately.

• Vector Database Implementation: Learn to use Pinecone to store and retrieve semantic data efficiently.

• Professional Mobile Development: Build a responsive chat interface using React Native and Expo, specifically optimized for Android devices.

• Full-Stack Integration: Connect your mobile frontend to your Python backend using REST APIs.

• Advanced Features: Implement "Typewriter" streaming effects and chat history memory for a natural user experience.

• Deployment: Go from localhost to the real world by deploying your API to the cloud and building a shareable Android APK.

👨‍💻 Who Is This Course For?

• React Native Developers who want to break into the AI industry and add "RAG Development" to their resume.

• Python Developers who have built AI scripts but want to showcase them in a real-world mobile application.

• Entrepreneurs & Indie Hackers looking to build and launch their own SaaS or AI wrapper products on the Google Play Store.

🛠️ Tech Stack

• Frontend: React Native (Expo), React Native Gifted Chat

• Backend: Python, FastAPI

• AI & Data: LangChain, OpenAI GPT-4, Pinecone Vector DB

• Tools: Postman, Android Studio Emulator

📚 Course Requirements

• Basic understanding of JavaScript/React Native.

• Basic familiarity with Python syntax.

• A computer capable of running Android Studio Emulator (or an Android device for testing).

• No prior AI or Machine Learning experience required—we start from the basics!

📝 Detailed Curriculum Breakdown

Phase 1: The Brain (Backend)

We start by building the engine. You'll learn why LLMs hallucinate and how RAG fixes it. You will write scripts to ingest PDF documents, split them into manageable chunks, and store them as mathematical vectors. By the end of this phase, you will have a running API that can answer questions like "What is the vacation policy?" based solely on your uploaded document.

Phase 2: The Body (Mobile App)

Next, we move to mobile. We will set up a React Native environment and build a chat interface that looks and feels like WhatsApp or Messenger. You'll learn how to handle network requests, manage loading states, and handle the specific quirks of testing local backends on Android emulators.

Phase 3: The Polish (Deployment)

Finally, we make it production-ready. We will refactor our code to support streaming (seeing the text appear word-by-word), implement voice-to-text features, and deploy our backend to the cloud. You will finish the course by generating a real .apk file that you can install on your phone or share with friends.