Description
AI-Powered E-Commerce App with .NET 9, Angular 20 & RAG. This hands-on course takes you step-by-step through the development of a modern, AI-powered e-commerce app using .NET 9 and Angular 20. The main goal is to create a standard e-commerce store that becomes a fully integrated and intelligent system with advanced capabilities such as semantic search and an intelligent chatbot. Along the way, you will build an AI-ready infrastructure that covers everything from the basic architecture to the implementation of advanced manufacturing intelligence, all in a clean, scalable, and production-ready framework. In the first and completed phase of the course, a fully operational e-commerce system is developed using .NET 9 and Angular 20, where the real-world, production-level components are built and the intelligent capabilities are fully and seamlessly implemented. In the next phase, the focus will be on AI assistant enhancements, and key concepts such as Retrieval-Based Augmented Generation (RAG), voice assistant integration, and web search enhancements will be introduced and implemented using tools such as Azure OpenAI and PostgreSQL with the pgvector extension. This training is not just theory, but you will gain direct practical experience in transforming a regular application into an AI-powered, user-intent-aware platform by actively building, implementing, and integrating these technologies.
What you will learn
- Building the complete program:
- Building a fully operational, production-grade AI-powered e-commerce app using .NET 9 and Angular 20.
- Semantic search and vector databases:
- Integrate semantic search using vector embeddings with Azure OpenAI or Ollama and pgvector in PostgreSQL.
- Backend architecture and structuring:
- Design and structure a modular backend following the principles of Clean Architecture and the Repository Pattern.
- Angular components and API signals:
- Build dynamic and responsive Angular components using the new Standalone architecture and Signals API.
- Advanced AI capabilities:
- Implement an assistant chatbot that understands natural language queries and suggests products contextually.
- Adding a hybrid search capability that combines traditional catalog search with semantic intelligence.
- Preparing the system for Recovery-based Augmented Manufacturing (RAG) to combine recovery and manufacturing logic.
- Deployment and Infrastructure:
- Containerize backend, database, and frontend services using Docker Compose for easy local deployment.
- Configure Ocelot API Gateway for routing and orchestration of services.
- Real world experience:
- Gain real-world experience connecting microservices, AI models, and cloud infrastructure into a cohesive solution.
This course is suitable for people who:
- .NET developers who want to add AI and RAG features to enterprise-level applications.
- Angular engineers looking to master semantic search and RAG-based intelligence.
- Architects who design next-generation microservices and e-commerce platforms powered by AI.
- Full-Stack developers interested in building intelligent, production-ready web applications.
- Backend engineers curious about semantic search, vector databases, and LLM (Large Language Model) integration.
- Cloud engineers exploring Docker, containerization, and Azure OpenAI Service integration.
- Professionals looking to transition into AI-based full-stack development roles.
- Anyone who wants to specialize in practical integration of AI and RAG using familiar .NET and Angular tools.
Course details
- Publisher: Udemy
- Instructor: Rahul Sahay
- Training level: Beginner to advanced
- Training duration: 8 hours and 21 minutes
- Number of lessons: 70
Course topics
Prerequisites for the AI-Powered E-Commerce App with .NET 9 Angular 20 & RAG course
- Basic understanding of C# and the .NET ecosystem.
- Familiarity with Angular, TypeScript, or any frontend framework.
- Knowledge of RESTful APIs, JSON, and HTTP methods.
- A working knowledge of databases such as SQL Server or PostgreSQL.
- Basic Git/GitHub familiarity for project versioning.
- No prior AI or OpenAI experience is required — all concepts are covered step by step.
Course images
Sample course video
Installation Guide
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Subtitles: None
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
3.7 GB
