AI-Powered E-Commerce App with .NET 9, Angular 20 & RAG

• 10.5 hours on-demand video
• 1 downloadable resource
• Access on mobile and TV
• Certificate of completion

Course Phases

Phase 1 – Building the AI-Enabled Foundation (Completed)

In this phase, you’ll develop a fully functional, AI-ready e-commerce system powered by .NET 9 and Angular 20.
This is not a toy project — you’ll build real, production-grade components and integrate intelligent features end to end.

You will:

• Design a modular backend using Clean Architecture principles and the repository pattern.
• Implement semantic search by generating and storing embeddings using Azure OpenAI or Ollama, backed by PostgreSQL + pgvector.
• Create an AI chatbot assistant capable of natural language understanding and contextual product recommendations.
• Integrate multiple search modes — Catalog, Semantic, and Hybrid — that deliver smart, intent-based results.
• Develop a dynamic Angular 20 frontend using standalone components and Signals API for responsive data binding.
• Add a complete basket and checkout flow with persistent data management.
• Configure Ocelot API Gateway for service routing and Docker Compose for containerized deployment.

By the end of Phase 1, you will have a fully operational AI-driven store capable of handling real-time chat queries, intelligent product discovery, and hybrid semantic search — ready for the next phase of true RAG integration.

Phase 2 – Advancing to RAG-Powered Intelligence (Coming Soon)

In Phase 2, you’ll take your AI assistant to the next level by introducing Retrieval-Augmented Generation (RAG), Voice Assistant Integration, and Web Search Augmentation.

You will:

• Implement a RAG pipeline that combines vector search, document retrieval, and generative AI for context-aware answers.
• Add voice input and output, enabling users to interact naturally through speech.
• Integrate context memory, allowing the assistant to maintain awareness across multiple turns in the conversation.

By the end of Phase 2, your application will evolve into a fully RAG-powered conversational shopping assistant that can reason, retrieve, and respond like a true AI companion.

Tech Stack

• Backend: .NET 9, ASP.NET Core Minimal APIs, C#
• Frontend: Angular 20 with Standalone Components & Signals API
• AI Integration: Azure OpenAI, Ollama, pgvector (PostgreSQL)
• Gateway: Ocelot API Gateway
• Containerization: Docker & Docker Compose
• Hosting: Local or Cloud-based deployment (Azure-ready)

Who Is This Course For

• Developers who want to integrate AI capabilities into real-world applications.
• .NET and Angular engineers looking to master semantic search and RAG-based intelligence.
• Architects designing next-generation, AI-enabled microservices and e-commerce platforms.
• Learners eager to gain hands-on experience in building full-stack, AI-powered systems.

Course Stats

• 10+ hours of in-depth, project-based learning (Phase 1).
• 95+ practical coding sessions, all demonstrated step-by-step.
• Lifetime access, free updates, and new features with every phase.
• Real-world architecture you can extend, deploy, and showcase.

Why This Course

This isn’t a basic chatbot tutorial. By the end of this course, you’ll have:

• Built a production-grade AI e-commerce system powered by .NET 9 and Angular 20.
• Implemented semantic search, vector-based intelligence, and chatbot interaction.
• Deployed a containerized AI stack ready for RAG, voice, and web-integrated intelligence.
• Gained the expertise to design and scale AI-first enterprise applications.

  Your journey to building an AI-Powered E-Commerce Platform starts here.Enroll today and learn to combine software engineering, AI integration, and full-stack development — all in one real-world project.