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Generative Ai For .Net Developers With Azure Ai Services - AD-TEAM - 12-15-2024
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Generative Ai For .Net Developers With Azure Ai Services
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.79 GB | Duration: 6h 36m
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
evelopers 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
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