AI-102T00 Develop AI solutions in Azure

Introduction:

AI-102: Develop AI solutions in Azure is intended for software developers wanting to build AI infused applications that leverage Azure AI Foundry and other Azure AI services. Topics in this course include developing generative AI apps, building AI agents, and solutions that implement computer vision and information extraction. The course will use C# or Python as the programming language.

Objectives:

Course Outline:

1 – Plan and prepare to develop AI solutions on Azure

  • What is AI?
  • Azure AI services
  • Azure AI Foundry
  • Developer tools and SDKs
  • Responsible AI
  • Module assessment

2 – Choose and deploy models from the model catalog in Azure AI Foundry portal

  • Explore the model catalog
  • Deploy a model to an endpoint
  • Optimize model performance
  • Module assessment

3 – Develop an AI app with the Azure AI Foundry SDK

  • What is the Azure AI Foundry SDK?
  • Work with project connections
  • Create a chat client
  • Module assessment

4 – Get started with prompt flow to develop language model apps in the Azure AI Foundry

  • Understand the development lifecycle of a large language model (LLM) app
  • Understand core components and explore flow types
  • Explore connections and runtimes
  • Explore variants and monitoring options
  • Module assessment

5 – Develop a RAG-based solution with your own data using Azure AI Foundry

  • Understand how to ground your language model
  • Make your data searchable
  • Create a RAG-based client application
  • Implement RAG in a prompt flow
  • Module assessment

6 – Fine-tune a language model with Azure AI Foundry

  • Understand when to fine-tune a language model
  • Prepare your data to fine-tune a chat completion model
  • Explore fine-tuning language models in Azure AI Studio
  • Module assessment

7 – Implement a responsible generative AI solution in Azure AI Foundry

  • Plan a responsible generative AI solution
  • Map potential harms
  • Measure potential harms
  • Mitigate potential harms
  • Manage a responsible generative AI solution
  • Module assessment

8 – Evaluate generative AI performance in Azure AI Foundry portal

  • Assess the model performance
  • Manually evaluate the performance of a model
  • Automated evaluations
  • Module assessment

9 – Get started with AI agent development on Azure

  • What are AI agents?
  • Options for agent development
  • Azure AI Foundry Agent Service
  • Module assessment

10 – Develop an AI agent with Azure AI Foundry Agent Service

  • What is an AI agent
  • How to use Azure AI Foundry Agent Service
  • Develop agents with the Azure AI Foundry Agent Service
  • Module assessment

11 – Integrate custom tools into your agent

  • Why use custom tools
  • Options for implementing custom tools
  • How to integrate custom tools
  • Module assessment

12 – Develop an AI agent with Semantic Kernel

  • Understand Semantic Kernel AI agents
  • Create an Azure AI agent with Semantic Kernel
  • Add plugins to Azure AI agent

13 – Orchestrate a multi-agent solution using Semantic Kernel

  • Understand the Semantic Kernel Agent Framework
  • Create an agent group chat
  • Design an agent selection strategy
  • Define a chat termination strategy

14 – Analyze text with Azure AI Language

  • Provision an Azure AI Language resource
  • Detect language
  • Extract key phrases
  • Analyze sentiment
  • Extract entities
  • Extract linked entities
  • Module assessment

15 – Create question answering solutions with Azure AI Language

  • Understand question answering
  • Compare question answering to Azure AI Language understanding
  • Create a knowledge base
  • Implement multi-turn conversation
  • Test and publish a knowledge base
  • Use a knowledge base
  • Improve question answering performance
  • Module assessment

16 – Build a conversational language understanding model

  • Understand prebuilt capabilities of the Azure AI Language service
  • Understand resources for building a conversational language understanding model
  • Define intents, utterances, and entities
  • Use patterns to differentiate similar utterances
  • Use pre-built entity components
  • Train, test, publish, and review a conversational language understanding model
  • Module assessment

17 – Create a custom text classification solution

  • Understand types of classification projects
  • Understand how to build text classification projects
  • Module assessment

18 – Custom named entity recognition

  • Understand custom named entity recognition
  • Label your data
  • Train and evaluate your model
  • Module assessment

19 – Translate text with Azure AI Translator service

  • Provision an Azure AI Translator resource
  • Specify translation options
  • Define custom translations
  • Module assessment

20 – Create speech-enabled apps with Azure AI services

  • Provision an Azure resource for speech
  • Use the Azure AI Speech to Text API
  • Use the text to speech API
  • Configure audio format and voices
  • Use Speech Synthesis Markup Language
  • Module assessment

21 – Translate speech with the Azure AI Speech service

  • Provision an Azure resource for speech translation
  • Translate speech to text
  • Synthesize translations
  • Module assessment

22 – Develop an audio-enabled generative AI application

  • Deploy a multimodal model
  • Develop an audio-based chat app
  • Module assessment

23 – Analyze images

  • Provision an Azure AI Vision resource
  • Analyze an image
  • Module assessment

24 – Read text in images

  • Explore Azure AI options for reading text
  • Read text with Azure AI Vision Image Analysis
  • Module assessment

25 – Detect, analyze, and recognize faces

  • Plan a face detection, analysis, or recognition solution
  • Detect and analyze faces
  • Verify and identify faces
  • Responsible AI considerations for face-based solutions
  • Module assessment

26 – Classify images

  • Azure AI Custom Vision
  • Train an image classification model
  • Create an image classification client application
  • Module assessment

27 – Detect objects in images

  • Use Azure AI Custom Vision for object detection
  • Train an object detector
  • Develop an object detection client application
  • Module assessment

28 – Analyze video

  • Understand Azure Video Indexer capabilities
  • Extract custom insights
  • Use Video Analyzer widgets and APIs
  • Module assessment

29 – Develop a vision-enabled generative AI application

  • Deploy a multimodal model
  • Develop a vision-based chat app
  • Module assessment

30 – Generate images with AI

  • What are image-generation models?
  • Explore image-generation models in Azure AI Foundry portal
  • Create a client application that uses an image generation model
  • Module assessment

31 – Create a multimodal analysis solution with Azure AI Content Understanding

  • What is Azure AI Content Understanding?
  • Create a Content Understanding analyzer
  • Use the Content Understanding REST API
  • Module assessment

32 – Create an Azure AI Content Understanding client application

  • Prepare to use the AI Content Understanding REST API
  • Create a Content Understanding analyzer
  • Analyze content
  • Module assessment

33 – Use prebuilt Document intelligence models

  • Understand prebuilt models
  • Use the General Document, Read, and Layout models
  • Use financial, ID, and tax models
  • Module assessment

34 – Extract data from forms with Azure Document intelligence

  • What is Azure Document Intelligence?
  • Get started with Azure Document Intelligence
  • Train custom models
  • Use Azure Document Intelligence models
  • Use the Azure Document Intelligence Studio
  • Module assessment

35 – Create a knowledge mining solution with Azure AI Search

  • What is Azure AI Search?
  • Extract data with an indexer
  • Enrich extracted data with AI skills
  • Search an index
  • Persist extracted information in a knowledge store
  • Module assessment

Enroll in this course

$2,380.00$2,995.00

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