AI-102T00 Designing and Implementing an Azure AI Solution

$2,495.00 USD

4 Days


Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. The course will use C# or Python as the programming language.

Who Should Attend?

Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure.

  • Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
  • Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
  • Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
  • Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
  • Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
  • Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

Learning Credits: Learning Credits can be purchased well in advance of your training date to avoid having to commit to specific courses or dates. Learning Credits allow you to secure your training budget for an entire year while eliminating the administrative headache of paying for individual classes. They can also be redeemed for a full year from the date of purchase. If you have previously purchased a Learning Credit agreement with New Horizons, you may use a portion of your agreement to pay for this class.

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Corporate Tech Pass: Our Corporate Tech Pass includes unlimited attendance for a single person, in the following Virtual Instructor Led course types: Microsoft Office, Microsoft Technical, CompTIA, Project Management, SharePoint, ITIL, Certified Ethical Hacker, Certified Hacking Forensics Investigator, Java, Professional Development Courses and more. The full list of eligible course titles can be found at

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Course Prerequisites

Before attending this course, students must have:
  • Knowledge of Microsoft Azure and ability to navigate the Azure portal
  • Knowledge of either C# or Python
  • Familiarity with JSON and REST programming semantics
    Recommended course prerequisites
  • AI-900T00: Microsoft Azure AI Fundamentals course
  • Agenda

    1 - Prepare to develop AI solutions on Azure

    • Define artificial intelligence
    • Understand AI-related terms
    • Understand considerations for AI Engineers
    • Understand considerations for responsible AI
    • Understand capabilities of Azure Machine Learning
    • Understand capabilities of Azure AI Services
    • Understand capabilities of the Azure OpenAI Service
    • Understand capabilities of Azure Cognitive Search

    2 - Create and consume Azure AI services

    • Provision an Azure AI services resource
    • Identify endpoints and keys
    • Use a REST API
    • Use an SDK

    3 - Secure Azure AI services

    • Consider authentication
    • Implement network security

    4 - Monitor Azure AI services

    • Monitor cost
    • Create alerts
    • View metrics
    • Manage diagnostic logging

    5 - Deploy Azure AI services in containers

    • Understand containers
    • Use Azure AI services containers

    6 - Analyze images

    • Provision an Azure AI Vision resource
    • Analyze an image
    • Generate a smart-cropped thumbnail and remove background

    7 - Classify images

    • Provision Azure resources for Azure AI Custom Vision
    • Understand image classification
    • Train an image classifier

    8 - Detect, analyze, and recognize faces

    • Identify options for face detection analysis and identification
    • Understand considerations for face analysis
    • Detect faces with the Azure AI Vision service
    • Understand capabilities of the face service
    • Compare and match detected faces
    • Implement facial recognition

    9 - Read Text in images and documents with the Azure AI Vision Service

    • Explore Azure AI Vision options for reading text
    • Use the Read API

    10 - Analyze video

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

    11 - Analyze text with Azure AI Language

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

    12 - Build a question answering solution

    • 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

    13 - 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

    14 - Create a custom text classification solution

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

    15 - Custom named entity recognition

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

    16 - Translate text with Azure AI Translator service

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

    17 - 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

    18 - Translate speech with the Azure AI Speech service

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

    19 - Create an Azure AI Search solution

    • Manage capacity
    • Understand search components
    • Understand the indexing process
    • Search an index
    • Apply filtering and sorting
    • Enhance the index

    20 - Create a custom skill for Azure AI Search

    • Create a custom skill
    • Add a custom skill to a skillset

    21 - Create a knowledge store with Azure AI Search

    • Define projections
    • Define a knowledge store

    22 - Plan an Azure AI Document Intelligence solution

    • Understand AI Document Intelligence
    • Plan Azure AI Document Intelligence resources
    • Choose a model type

    23 - Use prebuilt Form Recognizer models

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

    24 - 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

    25 - Get started with Azure OpenAI Service

    • Access Azure OpenAI Service
    • Use Azure OpenAI Studio
    • Explore types of generative AI models
    • Deploy generative AI models
    • Use prompts to get completions from models
    • Test models in Azure OpenAI Studio's playgrounds

    26 - Build natural language solutions with Azure OpenAI Service

    • Integrate Azure OpenAI into your app
    • Use Azure OpenAI REST API
    • Use Azure OpenAI SDK

    27 - Apply prompt engineering with Azure OpenAI Service

    • Understand prompt engineering
    • Write more effective prompts
    • Provide context to improve accuracy

    28 - Generate code with Azure OpenAI Service

    • Construct code from natural language
    • Complete code and assist the development process
    • Fix bugs and improve your code

    29 - Generate images with Azure OpenAI Service

    • What is DALL-E?
    • Explore DALL-E in Azure OpenAI Studio
    • Use the Azure OpenAI REST API to consume DALL-E models

    30 - Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service

    • Understand Retrieval Augmented Generation (RAG) with Azure OpenAI Service
    • Add your own data source
    • Chat with your model using your own data

    31 - Fundamentals of Responsible Generative AI

    • Plan a responsible generative AI solution
    • Identify potential harms
    • Measure potential harms
    • Mitigate potential harms
    • Operate a responsible generative AI solution

    Upcoming Class Dates and Times

    May 28, 29, 30, 31
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