Full Stack .NET 10 + AI Engineering
Morning Batch | Nov 2026
About This Course
Full Stack .NET 10 + AI Engineering is a hands-on program for building modern web applications with C# and .NET 10, then adding AI features to them. You learn C#, SQL and Entity Framework Core, ASP.NET Core Web APIs, security and a React front end, and then go deep into AI engineering with .NET: Microsoft.Extensions.AI, Semantic Kernel, embeddings and RAG, tool calling and agents, the Model Context Protocol (MCP) and running AI features in production.
The course ends with a capstone project: a full-stack AI application you design, build and deploy yourself.
What You'll Learn
- C# and .NET 10: object-oriented programming, LINQ and async programming
- SQL, Entity Framework Core and data modelling
- ASP.NET Core Web APIs: validation, caching, logging and testing with xUnit
- Security with JWT, ASP.NET Core Identity and policies
- React with TypeScript, including a streaming chat interface
- How large language models work: tokens, context and cost
- Prompt engineering and Microsoft.Extensions.AI
- Semantic Kernel: plugins, prompt templates and memory
- Embeddings, vector search and Retrieval-Augmented Generation (RAG)
- Tool calling, AI agents and the Model Context Protocol (MCP)
- Prompt-injection defence, evaluation and observability for AI features
- Docker, Azure deployment and CI/CD with GitHub Actions
Hands-On Learning
- Live coding in every session
- A weekly lab at the end of each module
- One application built up step by step through the course
- Code reviews
- A capstone project you deploy and present
Projects
AI-Powered Web API
An ASP.NET Core API with chat and structured-output features built on Microsoft.Extensions.AI.
Document Question-Answering (RAG)
Answers questions over your own documents with citations, using embeddings and vector search.
Capstone: Full-Stack AI Application
A deployed .NET + React application with AI features of your choice, presented in a final demo.
Who Should Join?
- BE / B.Tech, BCA, MCA and BSc Computer Science / IT students
- Final-year students and recent graduates
- .NET developers who want to add AI skills
- Anyone aiming for a backend, full-stack or AI engineering role on .NET
Prerequisites
Basic programming knowledge in any language. C# is taught from the fundamentals.
Course Outcome
By the end of the course you can build, secure, test and deploy full-stack .NET applications with AI features such as chat assistants, RAG search and tool-using agents, and you have a deployed capstone project for your portfolio.
Curriculum · 16 modules, 80 lessons
Module 1 — C# Foundations 5 lessons
The language and tools you will use every day.
- Course orientation, the .NET 10 SDK, CLI and IDE setup · 60
- Types, variables, operators and control flow · 60
- Methods, parameters and return values · 60
- Arrays, strings and collections · 60
- Lab: C# fundamentals exercises · 60
Module 2 — Object-Oriented C# 5 lessons
Designing programs with classes and interfaces.
- Classes, records and structs · 60
- Inheritance, interfaces and abstract classes · 60
- Generics · 60
- Exceptions and nullable reference types · 60
- Lab: build a small object-oriented application · 60
Module 3 — Modern C# and Async Programming 5 lessons
The features modern .NET code relies on.
- LINQ for querying data · 60
- Delegates, lambdas and events · 60
- async/await and Tasks · 60
- Pattern matching and newer C# language features · 60
- Lab: LINQ and async exercises · 60
Module 4 — SQL and Data Access 5 lessons
Relational data and Entity Framework Core.
- SQL fundamentals: tables, keys, CRUD and filtering · 60
- Joins, indexes and transactions · 60
- EF Core models and DbContext · 60
- Migrations and relationships · 60
- Lab: data model with EF Core · 60
Module 5 — ASP.NET Core Web API – Part 1 5 lessons
Building HTTP APIs the .NET way.
- Hosting, dependency injection and configuration · 60
- Minimal APIs and controllers · 60
- Validation and error handling · 60
- API documentation with OpenAPI · 60
- Lab: build a CRUD Web API · 60
Module 6 — ASP.NET Core Web API – Part 2 5 lessons
Production-quality API design and testing.
- EF Core in the API with service layers · 60
- Paging, filtering and caching · 60
- Logging and health checks · 60
- Unit and integration tests with xUnit · 60
- Lab: harden and test the API · 60
Module 7 — Security 5 lessons
Protecting APIs and users.
- Authentication and authorization concepts · 60
- JWT and refresh tokens · 60
- ASP.NET Core Identity · 60
- Roles, policies, CORS and OWASP basics · 60
- Lab: secure the API · 60
Module 8 — React – Part 1 5 lessons
A modern front end in React with TypeScript.
- JavaScript and TypeScript essentials · 60
- Components, props and state · 60
- Hooks and effects · 60
- Forms and validation · 60
- Lab: React screens for the application · 60
Module 9 — React – Part 2 and Full Stack 5 lessons
Connecting the React front end to the .NET API.
- Routing · 60
- Calling the .NET API and the sign-in flow · 60
- State management · 60
- Building a streaming chat interface · 60
- Lab: full-stack integration · 60
Module 10 — AI Fundamentals for .NET 5 lessons
How large language models work and how to use them from C#.
- How LLMs work: tokens, context windows and cost · 60
- Prompt engineering patterns · 60
- Microsoft.Extensions.AI and the IChatClient abstraction · 60
- Streaming and structured output · 60
- Lab: first AI features in the API · 60
Module 11 — Semantic Kernel 5 lessons
Orchestrating AI features with Semantic Kernel.
- Kernel, plugins and functions · 60
- Prompt templates · 60
- Chat history and memory · 60
- Azure OpenAI and other model providers · 60
- Lab: AI assistant with Semantic Kernel · 60
Module 12 — Embeddings and RAG 5 lessons
Answers grounded in your own documents and data.
- Embeddings and vector search · 60
- Vector stores: pgvector and Azure AI Search · 60
- Document ingestion and chunking · 60
- Building a RAG API with citations · 60
- Lab: document question-answering · 60
Module 13 — Tool Calling and AI Agents 5 lessons
Models that act through your code and data.
- Function and tool calling · 60
- Building agents in .NET · 60
- Model Context Protocol (MCP) servers and clients in C# · 60
- Multi-step workflows and guardrails · 60
- Lab: an agent that uses your APIs · 60
Module 14 — Production AI 5 lessons
Running AI features reliably, safely and affordably.
- Cost, latency and caching · 60
- Prompt injection and protecting personal data · 60
- Testing and evaluating AI features · 60
- Observability with OpenTelemetry · 60
- Lab: production-ready AI features · 60
Module 15 — Cloud and DevOps 5 lessons
Shipping the application.
- Docker for .NET and React · 60
- Deploying to Azure App Service and Container Apps · 60
- CI/CD with GitHub Actions · 60
- Configuration and secrets management · 60
- Lab: deploy the full-stack application · 60
Module 16 — Capstone Project 5 lessons
Design, build and deploy your own full-stack AI application.
- Capstone design: requirements and architecture · 60
- Capstone build: backend and data · 60
- Capstone build: AI features · 60
- Capstone build: front end and deployment · 60
- Capstone demo and review · 60
Cancellation & refund policy
Refund Policy
- If a cancellation request is received 7 days or more before the batch start date, 25% of the course fee will be deducted as cancellation charges and the remaining amount will be refunded.
- If a cancellation request is received between 3 and 6 days before the batch start date, 50% of the course fee will be deducted as cancellation charges and the remaining amount will be refunded.
- If a cancellation request is received less than 3 days before the batch start date, no refund will be applicable.
- No refund will be provided once the batch has started.
- If the batch is cancelled by ConfidentHire, the full course fee paid by the student will be refunded.
- Course fees are non-transferable to another student.
- Approved refunds will be processed within 7–10 working days.
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