Pieter Nijs
Microsoft MVP, .NET Consultant @ Xebia, Published author
Zoutleeuw, Belgium
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Pieter Nijs is .NET Consultant at Xebia Microsoft Services where he helps customers with 'everything mobile and cloud'.
He has a keen interest in mobile and cloud development and has played a key role in numerous projects, ranging from expansive customer facing healthcare, telecom and media applications to smaller LOB applications.
Currently, Pieter is diving into the fascinating realms of artificial intelligence, exploring how these cutting-edge technologies can bring added value to customer projects and solve complex problems in innovative ways.
Pieter is passionate about constantly exploring and experimenting with new and innovative technologies both at work and in his spare time, which he eagerly shares with others. He is a seasoned speaker at conferences, trainer, and blogger at blog.pieeatingninjas.be. He has been awarded the Microsoft MVP Award since 2017, reflecting his unwavering passion and expertise in serving the community. His first book, 'The MVVM Pattern in .NET MAUI' (published by Packt Publishing), was recently released and has been very well received.
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Down the rabbit hole: non-nullable reference types
Imagine a wonderland where reference types aren't implicitly 'nullable'... Somewhere where you explicitly need to define them as nullable, just like you do with value types. Imagine no unnecessary null-checks, while getting warnings in your IDE where you should check for nulls. No more NullReferenceExceptions!
Since C# 8 you can opt-in for this utopian experience!
Let's go down the rabbit hole of the non-nullable reference types and discover all of its goodness. It's more than just adding a '?' here or a '!' there.
From Zero to AI Hero: Transform Your Data into Generative AI with Azure and C#
Want to build a Generative AI application without being a data scientist or AI expert? In this talk, Pieter shares the knowledge and insights he gained while setting up an AI solution for a customer using Azure's OpenAI Service, Azure AI Search, and C#. This talk will demonstrate how anyone with a basic understanding of C# can create a RAG (Retrieval Augmented Generation) solution that leverages their own data.
By the end of this talk, you should have a practical understanding of some of Azure's AI capabilities, RAG and the confidence to create your own Generative AI application infused with the knowledge from your own data. Whether you're an experienced developer looking to expand your AI skill set, or a curious tech enthusiast seeking to understand the potential of AI, this talk will give you some insights and tools necessary to get a grasp of what Generative AI can do.
Building a Copilot for Your Own Application with Semantic Kernel
Ever wondered how intelligent 'copilot' features are being integrated into applications? This talk will guide you through leveraging Generative AI (GPT4) and Semantic Kernel to transform your applications. Whether you're aiming to improve user experience, boost efficiency, or innovate in your field, you'll get to see how to create AI assistants that integrate seamlessly with your software. We'll be focussing on a demo where we add a copilot to an existing application, showcasing the step-by-step process and the immediate impact it has. Get ready to explore the seamless fusion of AI with C# through Semantic Kernel, and leave equipped to create your own intelligent application enhancements!
Building Intelligent .NET MAUI Apps with ML.NET and Azure ML Studio
Machine Learning is no longer exclusively reserved for Python or some of the more ‘hipster’ languages. In this session, we’ll see how to create a sentiment analysis model and use C# with ML.NET to perform inference on it in a .NET MAUI app, enabling offline AI analysis directly on a mobile device.
We’ll also explore how Azure ML Studio can simplify the process of training a model. By combining Azure’s power with .NET tools, you’ll learn how to efficiently train models in the cloud and use ML.NET for inference in your mobile apps.
By the end of the session, you’ll have a solid understanding of how to tackle classification problems, perform inference using ML.NET, and deploy pre-trained models in .NET MAUI apps.
Faster .NET MAUI Development Through Efficient Testing
As .NET MAUI developers, we know how frustrating it can be to deal with slow iteration cycles. Constantly deploying to devices or simulators for every little change eats up time and drags down productivity.
In this session, we’ll look at how designing your app with testability in mind can break this cycle. By separating your business logic from your UI code and adopting smarter testing practices, you can validate most of your app’s functionality directly in the IDE. In other words: no endless deployments or manual clicks required.
Through real-world examples and practical tips, we’ll see how better testing gives faster iterations, better code, and happier developers.
Building Secure .NET MAUI Apps and APIs with Entra ID and MSAL
Let’s face it: authentication and authorization can feel like a headache. But with the right tools and approach, it doesn’t have to be! Using Microsoft Entra ID and the Microsoft Authentication Library (MSAL), you can easily add secure and flexible user authentication and authorization to your .NET MAUI apps and APIs.
In this session, Pieter will walk you through setting up Entra ID, integrating it into your .NET MAUI app, and leveraging MSAL to manage user authentication and enforce user permissions. You’ll also learn how to restrict API access to authorized users with confidence.
With practical demos, you’ll see how to set up user flows, handle secure token-based authentication, and lock down API endpoints. By the end, you’ll have the tools and knowledge to implement a rock-solid authentication strategy for your apps.
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Pieter Nijs
Microsoft MVP, .NET Consultant @ Xebia, Published author
Zoutleeuw, Belgium
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