Course overview
Description generated based on course syllabus and open data.
C#/.NET is an ecosystem for building desktop, mobile, and web applications. The program covers C#, Git, SQL, Entity Framework Core, ASP.NET Core, and AI integration (LLM, API, prompting), focusing on practical tasks and applied .NET patterns.
C#/.NET + AI curriculum
- C# Starter: syntax, data types, collections, error handling.
- Git Basics: branching, pull/merge/pull requests, code review, Git-flow.
- C# Essential: OOP, delegates, events, LINQ, asynchrony (async/await).
- C# Professional: SOLID, patterns, reflection, attributes, diagnostics.
- SQL: data modeling, JOINs, aggregation, indexes, transactions.
- Entity Framework Core: Code First, migrations, tracking, querying, optimization.
- ASP.NET Core: REST APIs, middleware, DI, configuration, security, OpenAPI.
- AI Skills: LLM, prompt engineering, test and docs automation, AI API integration.
.NET back end and web
Building REST APIs, working with data via EF Core, validation, logging, environment configuration, minimal APIs or MVC.
AI integrations in .NET
Developing services using LLMs for text generation, code analysis, testing, and documentation; connecting AI providers via HTTP/API SDKs.
Who C#/.NET Developer + AI fits; who it does not
Suitable
- Beginners seeking a structured path in C#/.NET with foundational AI tools.
- Engineers switching from other languages to .NET and ASP.NET Core.
- QA/analysts needing C#, SQL, and AI integration for automation.
- Those building internal business apps in the Microsoft ecosystem.
Not suitable
- Those expecting purely theoretical material without practice.
- Those not planning to use Git, SQL, web APIs, or AI tools.
- Those seeking a narrow specialization without full .NET stack coverage.
Problem → outcome in C#/.NET and AI
- Problem: fragmented C# learning → Outcome: a sequence from syntax to ASP.NET Core and AI.
- Problem: lack of hands-on data work → Outcome: SQL and EF Core with real CRUD, migrations, optimization.
- Problem: difficulty building REST APIs → Outcome: ASP.NET Core with middleware, DI, and OpenAPI documentation.
- Problem: unclear LLM capabilities → Outcome: proper prompting and AI API integration in .NET projects.
Comparison with C#/.NET alternatives
- Self-learning: flexible, but risks gaps in Git/SQL/EF Core/ASP.NET Core and AI integrations.
- Academic programs: solid fundamentals, often without up-to-date AI practices and cloud APIs.
- Courses without AI: cover .NET but omit prompting, LLMs, and API integration examples.
What you will gain in C#/.NET Developer + AI
- C# syntax, OOP, collections, LINQ, async/await.
- Git workflow: branching, reviews, pull requests.
- Data design and SQL queries; EF Core for persistence.
- Building REST APIs on ASP.NET Core with DI and middleware.
- Testing (xUnit/NUnit), logging, environment configuration.
- Working with LLMs: prompt engineering, tools, and API integrations.
