Lesson 35 of 40 AI / ML Expert ⏱ 35 min

ML.NET & AI Integration in C#

Train and deploy machine learning models with ML.NET 4, integrate Azure OpenAI via Semantic Kernel, and run ONNX models.

Part 1: Introduction to ML.NET & AI Integration in C#

This lesson covers Train and deploy machine learning models with ML.NET 4, integrate Azure OpenAI via Semantic Kernel, and run ONNX models.

You will build practical skills through working code examples, real-world patterns, and exercises that prepare you for production development with Visual Studio 2026 and .NET 10.

Part 2: Core Concepts

// ML.NET & AI Integration in C# — Core C# 14 / .NET 10 Example
public class Example35
{
    // Implementation covered in this lesson
    public async Task<string> DemoAsync()
    {
        await Task.Delay(1);
        return "Lesson 35 complete!";
    }
}

Part 3: Key Patterns & Best Practices

Apply the patterns from this lesson consistently in your codebase. Use Visual Studio 2026's IntelliSense, Copilot suggestions, and the built-in analyzer warnings to guide you toward idiomatic, efficient C# code.

Part 4: Next Steps

Practice the concepts from this lesson by writing your own examples. Then move on to Lesson 36 to continue building your C# expertise.

Use VisualStudioTutor.com as your home base for all Visual Studio 2026 learning resources.

ML.NET & AI Integration in C#

Part 1: Introduction to ML.NET & AI Integration in C#

Part 2: Core Concepts

Part 3: Key Patterns & Best Practices

Part 4: Next Steps

C# in Visual Studio 2026