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Learning Repository

Learn

This folder contains information and learning resources for various Azure and OpenAI technologies. The goal is to provide a comprehensive understanding of these tools, their applications, and how to use them effectively.

##Contents

Azure OpenAI

1. OpenAI on Azure

  • Overview: OpenAI on Azure enables developers to integrate advanced AI models like GPT and Codex into their applications. These models can help with text generation, summarization, code completion, and more.
  • Use Cases:
    • Customer Support: Implement AI-powered chatbots to handle common customer queries.
    • Content Generation: Automate the creation of articles, social media posts, and reports.
    • Coding Assistance: Enhance developer productivity by integrating AI-based coding tools.
  • Key Features:
    • Access to pre-trained OpenAI models such as GPT-4.
    • Fine-tuning capabilities for custom model training.
    • Built-in Azure security and compliance.
  • Resources:

Logic Apps

2. Azure Logic Apps

  • Overview: Azure Logic Apps simplifies the creation of automated workflows by connecting various services and applications. It is a low-code/no-code solution suitable for developers and non-developers alike.
  • Use Cases:
    • Automated Data Processing: Integrate cloud services to process and store data.
    • Alerting Systems: Build workflows that trigger alerts based on specific conditions.
    • Integration: Connect on-premises systems with cloud-based applications.
  • Key Features:
    • Hundreds of pre-built connectors for services like Microsoft 365, SQL Server, and Salesforce.
    • Built-in monitoring and diagnostics tools.
    • Support for complex workflows with conditional logic.
  • Resources:

APIM

3. Azure API Management (APIM)

  • Overview: Azure API Management provides a comprehensive solution for managing, securing, and monitoring APIs. It is designed to help organizations expose their services securely while ensuring scalability and high performance.
  • Use Cases:
    • API Gateways: Centralize API traffic with built-in caching and load balancing.
    • Security: Protect APIs with authentication, authorization, and rate-limiting features.
    • Developer Portals: Provide documentation and tools for developers to interact with your APIs.
  • Key Features:
    • Full lifecycle API management: design, deploy, and retire APIs.
    • Built-in support for OpenAPI Specification.
    • Analytics and insights into API usage.
  • Resources:

SDK

4. Artificial Intelligence (AI) and Machine Learning (ML) on Azure

  • Overview: Azure provides robust tools and frameworks for incorporating artificial intelligence (AI) and machine learning (ML) into business solutions. It supports a wide range of AI use cases, from large-scale language models to advanced deep learning frameworks.
  • Use Cases:
    • Generative AI: Develop applications that create new content such as text, images, or code.
    • Predictive Analytics: Use ML models to forecast trends and improve decision-making.
    • Intelligent Automation: Integrate AI into workflows to enhance efficiency and reduce manual effort.
  • Key Features:
    • Support for popular ML frameworks like TensorFlow and PyTorch.
    • Comprehensive AI services, including Azure Cognitive Services and Azure Machine Learning.
    • Seamless integration with other Azure tools for deployment and monitoring.
  • Resources:

Learning

5. Get started with Azure OpenAI Service (MS Learning) and Design Architectures

  • Overview: This module provides engineers with the skills to begin building an Azure OpenAI Service solution.
  • Learning objectives: By the end of this module, you'll be able to:
    • Create an Azure OpenAI Service resource and understand types of Azure OpenAI base models.
    • Use the Azure AI Studio, console, or REST API to deploy a base model and test it in the Studio's playgrounds.
    • Generate completions to prompts and begin to manage model parameters.
  • Resources: