Overview

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this comprehensive course, you'll learn how to build AI-powered applications using .NET. By exploring both foundational concepts and advanced tools, you'll gain the skills to integrate machine learning models, generative AI, and Azure AI services into .NET-based applications. You’ll also work with popular tools like ML.NET, Microsoft Copilot, and Azure Machine Learning to craft solutions that enhance your projects and workflows. You’ll begin by exploring the evolution of AI and machine learning, covering both foundational theory and real-world applications. From there, you'll dive into the development environment, setting up Visual Studio and ML.NET to train models and integrate them into .NET applications. As you progress, you'll discover powerful tools such as Azure AI and OpenAI, leveraging these technologies to build intelligent applications, including sentiment analysis tools and image classifiers. This course is ideal for developers who want to integrate cutting-edge AI techniques into their applications. With practical exercises on creating and deploying AI models, you'll not only understand the theory but also be able to implement AI solutions across multiple platforms.

Syllabus

Introduction

In this module, we will introduce the course, providing an overview of how to build AI-powered applications using .NET. You’ll gain insight into the course structure, tools, and technologies you’ll learn throughout.

Introduction to Machine Learning and AI

In this module, we will dive into the core concepts of AI and machine learning, discussing their history, applications, and ethical considerations. You'll also gain a deeper understanding of how these fields have evolved and their current state.

Machine Learning Basics

In this module, we will cover the fundamentals of machine learning, including algorithms, training procedures, and types of machine learning. This will lay the groundwork for understanding how to develop and deploy machine learning models.

Development Environment Setup

In this module, we will guide you through setting up the development environment for AI-powered applications using .NET. You'll ensure the right tools and configurations are in place to begin building your AI solutions.

Introduction to ML.NET

In this module, we will explore ML.NET, its features, and its role in machine learning development. You’ll learn to create projects, load data, train models, and integrate them into .NET applications.

Generative AI Tools and Copilots

In this module, we will dive into generative AI tools like Azure OpenAI and GitHub Copilot. You’ll learn to use these tools to improve productivity and create smarter AI-driven solutions.

Azure AI Services Fundamentals

In this module, we will introduce Microsoft Azure’s AI services and demonstrate how to set them up for your projects. You’ll also explore tools for content moderation and safety using Azure services.

Azure Machine Learning

In this module, we will explore Azure Machine Learning, its capabilities, and the process of deploying and testing machine learning models. You’ll also learn to integrate them into .NET applications for real-world use cases.

Creating Smart Solutions with .NET and Azure AI Cognitive Services

In this module, we will show you how to leverage Azure AI Cognitive Services to create intelligent applications. You’ll work with text and image processing tools to build real-world AI-powered solutions.

Creating GenAI Solutions Using .NET and Azure OpenAI

In this module, we will dive into the world of generative AI with Azure OpenAI, teaching you how to build intelligent chat agents, create code with AI, and generate images using advanced AI models.

Conclusion

In this final module, we will provide important guidance on managing Azure resources and review the key takeaways from the course. You’ll be ready to apply your new AI development skills confidently.