Learn to develop smart .NET applications backed by powerful generative AI components

What you'll learn

Understand the Fundamentals of Generative AI

Integrate Azure AI Services with .NET

Work with Natural Language Processing (NLP)

Develop AI-Enhanced Applications

Azure OpenAI Services

Azure AI Cognitive Services

Machine Learning Fundamentals

Azure ML

ML Builder in Visual Studio and Visual Studio Code

Retrieval-Augmented Generation (RAG)

Azure AI Studio

GPT and DALL-E

Requirements

Some experience with C#

Knowledge of basic web development concepts

Description

Unlock the potential of Generative AI and take your .NET applications to new heights with Generative AI for .NET Developers with Azure AI Services. This comprehensive course is designed to equip developers, business leaders, and technical specialists with the tools, knowledge, and confidence to build, deploy, and manage AI-powered applications that drive real value. Whether you're a developer eager to add AI skills to your toolkit or a manager looking to enhance your team's AI capabilities, this course provides a step-by-step pathway to mastering generative AI on Azure.What You'll Learn:In this course, you'll gain hands-on experience with Azure's cutting-edge AI services, from foundational concepts to advanced techniques. Our carefully designed curriculum ensures you not only understand how generative AI works but also why it's transforming industries across the globe. Key takeaways include:Foundational Knowledge of Generative AI and Key Algorithms: Understand the principles behind generative AI, including neural networks, transformers, and models like GANs. Learn how these concepts empower real-world applications like chatbots, image generation, and content automation.Practical Skills with Azure's AI Tools: From Azure OpenAI to Cognitive Services, explore how Azure's robust AI ecosystem makes it possible to integrate advanced AI capabilities without complex setup. Through labs and practical exercises, you'll become fluent in leveraging these tools directly in .NET applications.Real-World Applications of AI in .NET Development: Apply your new skills to projects that simulate business scenarios. Build applications with real value, from automated customer support to intelligent document generation, that demonstrate the impact AI can bring to your business.Scalable and Secure Deployment on Azure: Learn how to deploy AI models in the cloud with Azure's reliable, scalable infrastructure. With best practices in security, cost management, and performance monitoring, you'll be prepared to create AI solutions that are both efficient and sustainable.Responsible and Ethical AI: Get guidance on implementing AI responsibly, with an emphasis on ethics, transparency, and data privacy. Azure's AI tools provide built-in features to ensure your AI applications are fair, secure, and trustworthy.Who Should Enroll?This course is ideal for:Developers and Technical Leads: Gain in-demand skills to build advanced .NET applications powered by Azure's AI services, giving you a competitive edge in the marketplace.Managers and Business Decision Makers: Discover how generative AI can enhance operations, drive innovation, and create value, empowering you to make strategic decisions about AI implementation.Training Specialists and Learning & Development Teams: Equip your workforce with the tools and knowledge to excel in the age of AI, fostering innovation and efficiency within your organization.Why Choose This Course?This is more than just a training program – it's a complete learning journey. You'll benefit from clear, engaging explanations, hands-on labs for every concept, and real-world projects that bring generative AI to life. By the end of this course, you'll not only have a portfolio of AI-driven .NET applications but also the skills to deploy, manage, and innovate with AI solutions confidently.Join us in this transformative learning experience and see how generative AI can reshape your development process, enhance customer engagement, and drive operational success. Together, we'll turn complex AI concepts into actionable business insights and solutions that bring measurable impact.Enroll now and let's start building the intelligent applications of tomorrow!

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Introduction to Machine Learning and AI

Lecture 2 Section Overview

Lecture 3 Overview and History of AI

Lecture 4 Overview of Machine Learning

Lecture 5 What is Generative AI?

Lecture 6 Ethical implications of AI

Lecture 7 Section Review

Section 3: Machine Learning Basics

Lecture 8 Section Overview

Lecture 9 Machine Learning Algorithms

Lecture 10 Types of Machine Learning: Supervised, Unsupervised, Reinforcement

Lecture 11 Key concepts: Training, Testing, Validation

Lecture 12 Understanding Neural Networks

Lecture 13 Section Review

Section 4: Development Environment Setup

Lecture 14 Section Overview

Lecture 15 Visual Studio and .NET Versions Check

Lecture 16 Visual Studio Code Setup

Lecture 17 Section Review

Section 5: Introduction to ML.NET

Lecture 18 Section Overview

Lecture 19 What is ML.NET?

Lecture 20 Installing ML.NET Model Builder (Visual Studio)

Lecture 21 Project Creation

Lecture 22 Data Preparation and Loading

Lecture 23 Data Loading and Training Overview

Lecture 24 Training the Model

Lecture 25 Using Visual Studio Code (Linux, Mac and Windows alternative)

Lecture 26 Consume a model in a .NET console app

Lecture 27 Consume a model in a .NET API

Lecture 28 Section Source Code

Lecture 29 Next steps in your ML.NET journey (community, resources)

Lecture 30 Section Review

Section 6: Generative AI Tools and Copilots

Lecture 31 Section Overview

Lecture 32 What is generative AI?

Lecture 33 Different language models

Lecture 34 Using Azure OpenAI models

Lecture 35 Understanding Copilots

Lecture 36 Using Microsoft Copilot

Lecture 37 Effective prompting

Lecture 38 Understanding GitHub Copilot

Lecture 39 Create GitHub Copilot Account

Lecture 40 Using GitHub Copilot with VS Code

Lecture 41 Developing copilots

Lecture 42 Section Review

Section 7: Azure AI Services Fundamentals

Lecture 43 Section Overview

Lecture 44 Overview of Microsoft Azure

Lecture 45 Understanding Azure AI Services

Lecture 46 Provision Azure AI Services

Lecture 47 Exploring Content Safety Studio

Lecture 48 Create a Moderated Text Analyser

Lecture 49 Section Source Code

Lecture 50 Delete Your Azure Resources

Lecture 51 Section Review

Section 8: Creating smart solutions with .NET and Azure AI Cognitive Services

Lecture 52 Section Overview

Lecture 53 Understanding Natural Language Processing

Lecture 54 Text classification with ML

Lecture 55 Text Analysis with Azure AI

Lecture 56 Using Azure AI Language Studio

Lecture 57 Create a Sentiment Analysis Application

Lecture 58 Understanding Computer Vision

Lecture 59 Image processing using Machine Learning

Lecture 60 Transformers and Multi-modal Models

Lecture 61 Understanding Azure AI Vision

Lecture 62 Using Azure AI Vision Studio

Lecture 63 Build Image Classification Application

Lecture 64 Understanding Document Intelligence

Lecture 65 Using Azure Document Intelligence Studio

Lecture 66 Build Receipt Analysis Application - Part 1

Lecture 67 Build Receipt Analysis Application - Part 2

Lecture 68 Delete Your Azure Resources

Lecture 69 Section Overview

Section 9: Azure Machine Learning

Lecture 70 Section Overview

Lecture 71 What is Microsoft Azure Machine Learning?

Lecture 72 Provisioning the Azure ML Resource

Lecture 73 Sample Data

Lecture 74 Using Automated ML To Train a Model

Lecture 75 Deploy and Test the Model

Lecture 76 Test Endpoint in Console App

Lecture 77 Sample Test Data Model

Lecture 78 Section Review

Section 10: Creating GenAI Solutions using .NET and Azure OpenAI

Lecture 79 Section Overview

Lecture 80 Introducing Azure OpenAI

Lecture 81 Provisioning Azure OpenAI

Lecture 82 Exploring Azure AI Studio

Lecture 83 Different generative AI models

Lecture 84 Prompt Engineering Fundamentals

Lecture 85 Additional prompt engineering tips

Lecture 86 Create Chat Agent with Azure OpenAI model

Lecture 87 Understanding code generation from natural language

Lecture 88 Code generation with AI Studio

Lecture 89 Create a programming assistant

Lecture 90 Review the Dall-E Model

Lecture 91 Generating images with a DALL-E model

Lecture 92 Understanding Retrieval Augmented Generation (RAG)

Lecture 93 Retrieval Augmented Generation (RAG) with AI Studio

Lecture 94 Using Retrieval Augmented Generation (RAG) in an application

Lecture 95 Section Review

Section 11: Conclusion

Lecture 96 Delete Your Azure Resources

Lecture 97 Final Thoughts

Developers,Technical Leads,Business Managers