• AI-102: Designing and Implementing an Azure AI Solution [AI-102T01-A] training including Exam Voucher

  • Group Training

    Learn to translate the vision from solution architects to build complete end-to-end solutions as an Azure AI engineer!

    Training code
    CGAAI102CE
    Spoken Language
    English
    Language Materials
    English
    Dayparts
    8
    Price
    €2.000,00
    excl. VAT No extra costs.

    Book AI-102: Designing and Implementing an Azure AI Solution [AI-102T01-A] training including Exam Voucher now

    In group training, we use several learning methods to help you obtain the knowledge, give you helpful insights and get you inspired. Check the Spoken language and Language materials on the left for language info.

    • 7-11-2022
      Utrecht
      €2.000,00
      €2.000,00
    • 8-5-2023
      Online Virtual
      €2.000,00
      €2.000,00
     

    What is AI-102: Designing and Implementing a Microsoft Azure AI Solution including exam voucher

    Gain subject matter expertise using cognitive services, machine learning, and knowledge mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, and conversational AI.
    The training is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.
    This course uses MOC (Microsoft Official Courseware) and will be given by an experienced MCT (Microsoft Certified Trainer).
    See the below modules for more information:
    Module 1: Introduction to AI on Azure
    Artificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you'll learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You'll also learn about some considerations for designing and implementing AI solutions responsibly.
    Lessons

    • Introduction to Artificial Intelligence
    • Artificial Intelligence in Azure

    Module 2: Developing AI Apps with Cognitive Services
    Cognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you'll learn how to provision, secure, monitor, and deploy cognitive services..
    Lessons

    • Getting Started with Cognitive Services
    • Using Cognitive Services for Enterprise Applications

    Module 3: Getting Started with Natural Language Processing
    Natural Language processing (NLP) is a branch of artificial intelligence that deals with extracting insights from written or spoken language. In this module, you'll learn how to use cognitive services to analyze and translate text.
    Lessons

    • Analyzing text
    • Translating text

    Module 4: Building Speech-Enabled Applications
    Many modern apps and services accept spoken input and can respond by synthesizing text. In this module, you'll continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.
    Lessons

    • Introducing Language Understanding
    • Create a new LUIS Service
    • Build LUIS
    • Speech recognition and synthesis
    • Speech translation

    Module 5: Creating Language Understanding Solutions
    To build an application that can intelligently understand and respond to natural language input, you must define and train a model for language understanding. In this module, you'll learn how to use the Language Understanding service to create an app that can identify user intent from natural language input.
    Lessons

    • Creating a Language Understanding App
    • Publishing and Using a Language Understanding App
    • Using Language Understanding with Speech

    Module 6: Building a QnA Solution
    One of the most common kinds of interaction between users and AI software agents is for users to submit questions in natural language, and for the AI agent to respond intelligently with an appropriate answer. In this module, you'll explore how the QnA Maker service enables the development of this kind of solution.
    Lessons
    Creating a QnA Knowledge Base

    • Publishing and Using a QnA Knowledge Base

    Module 7: Conversational AI and the Azure Bot Service
    Bots are the basis for an increasingly common kind of AI application in which users engage in conversations with AI agents, often as they would with a human agent. In this module, you'll explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a platform for creating and delivering conversational experiences.
    Lessons

    • Bot Basics
    • Implementing a Conversational Bot

    Module 8: Getting Started with Computer Vision
    Computer vision is an area of artificial intelligence in which software applications interpret visual input from images or video. In this module, you'll start your exploration of computer vision by learning how to use cognitive services to analyze images and video.
    Lessons

    • Analyzing Images
    • Analyzing Videos

    Module 9: Developing Custom Vision Solutions
    While there are many scenarios where pre-defined general computer vision capabilities can be useful, sometimes you need to train a custom model with your own visual data. In this module, you'll explore the Custom Vision service, and how to use it to create custom image classification and object detection models.
    Lessons

    • Image Classification
    • Object Detection

    Module 10: Detecting, Analyzing, and Recognizing Faces
    Facial detection, analysis, and recognition are common computer vision scenarios. In this module, you'll explore the user of cognitive services to identify human faces.
    Lessons

    • Detecting Faces with the Computer Vision Service
    • Using the Face Service

    Module 11: Reading Text in Images and Documents
    Optical character recognition (OCR) is another common computer vision scenario, in which software extracts text from images or documents. In this module, you'll explore cognitive services that can be used to detect and read text in images, documents, and forms.
    Lessons

    • Reading text with the Computer Vision Service
    • Extracting Information from Forms with the Form Recognizer service

    Module 12: Creating a Knowledge Mining Solution
    Ultimately, many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly important way to build intelligent search solutions that use AI to extract insights from large repositories of digital data and enable users to find and analyze those insights.
    Lessons

    • Implementing an Intelligent Search Solution
    • Developing Custom Skills for an Enrichment Pipeline
    • Creating a Knowledge Store
     
     

    Who should attend AI-102: Designing and Implementing a Microsoft Azure AI Solution including exam voucher

    This training is aimed at Cloud Solution Architects, Azure artificial intelligence designers, and AI developers. You have experience working with data scientists, data engineers, IoT specialists, and software developers.
    Also, you will receive a voucher to make the exam. Enlist today!

    Prerequisites

    The participants should have,

    • Professional experience with cloud technologies, and experience with software development.
    • Implementing solutions in C# or Python.
    • Knowledge of Microsoft Azure and ability to navigate the Azure portal.
    • Familiarity with JSON and REST programming semantics.
    • If you are completely new to Azure AI services, please complete Microsoft Azure AI

    Objectives

    After completing this training, you will be able to:

    • Describe considerations for AI-enabled application development
    • Create, configure, deploy, and secure Azure Cognitive Services
    • Develop applications that analyze text
    • Develop speech-enabled applications
    • Create applications with natural language understanding capabilities
    • Create QnA applications
    • Create conversational solutions with bots
    • Use computer vision services to analyze images and videos
    • Create custom computer vision models
    • Develop applications that detect, analyze, and recognize faces
    • Develop applications that read and process text in images and documents
    • Create intelligent search solutions for knowledge mining

    Exam information

    • Exam duration (minutes): 150-210
    • % extra time for non-native speakers:
    • Number of exam questions: 40-60
    • Minimum correct questions: 0,7
    • Exam style: Multiple choice
    • Open book: No
     
    Incompany

    Learn to translate the vision from solution architects to build complete end-to-end solutions as an Azure AI engineer!

    Training code
    CGAAI102CE
    Spoken Language
    English
    Language Materials
    English
    Dayparts
    8
    Price
    €2.000,00
    excl. VAT No extra costs.

    With an Incompany training you have several advantages:

    - You choose the location
    - You experience the training with your colleagues, so it is always in line with your practice
    - The trainer can tailor explanations, examples and assignments to your organization
    - In consultation exercises can be adapted to organization-specific questions

    Request more information or a quote.

     

    What is AI-102: Designing and Implementing a Microsoft Azure AI Solution including exam voucher

    Gain subject matter expertise using cognitive services, machine learning, and knowledge mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, and conversational AI.
    The training is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.
    This course uses MOC (Microsoft Official Courseware) and will be given by an experienced MCT (Microsoft Certified Trainer).
    See the below modules for more information:
    Module 1: Introduction to AI on Azure
    Artificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you'll learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You'll also learn about some considerations for designing and implementing AI solutions responsibly.
    Lessons

    • Introduction to Artificial Intelligence
    • Artificial Intelligence in Azure

    Module 2: Developing AI Apps with Cognitive Services
    Cognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you'll learn how to provision, secure, monitor, and deploy cognitive services..
    Lessons

    • Getting Started with Cognitive Services
    • Using Cognitive Services for Enterprise Applications

    Module 3: Getting Started with Natural Language Processing
    Natural Language processing (NLP) is a branch of artificial intelligence that deals with extracting insights from written or spoken language. In this module, you'll learn how to use cognitive services to analyze and translate text.
    Lessons

    • Analyzing text
    • Translating text

    Module 4: Building Speech-Enabled Applications
    Many modern apps and services accept spoken input and can respond by synthesizing text. In this module, you'll continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.
    Lessons

    • Introducing Language Understanding
    • Create a new LUIS Service
    • Build LUIS
    • Speech recognition and synthesis
    • Speech translation

    Module 5: Creating Language Understanding Solutions
    To build an application that can intelligently understand and respond to natural language input, you must define and train a model for language understanding. In this module, you'll learn how to use the Language Understanding service to create an app that can identify user intent from natural language input.
    Lessons

    • Creating a Language Understanding App
    • Publishing and Using a Language Understanding App
    • Using Language Understanding with Speech

    Module 6: Building a QnA Solution
    One of the most common kinds of interaction between users and AI software agents is for users to submit questions in natural language, and for the AI agent to respond intelligently with an appropriate answer. In this module, you'll explore how the QnA Maker service enables the development of this kind of solution.
    Lessons
    Creating a QnA Knowledge Base

    • Publishing and Using a QnA Knowledge Base

    Module 7: Conversational AI and the Azure Bot Service
    Bots are the basis for an increasingly common kind of AI application in which users engage in conversations with AI agents, often as they would with a human agent. In this module, you'll explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a platform for creating and delivering conversational experiences.
    Lessons

    • Bot Basics
    • Implementing a Conversational Bot

    Module 8: Getting Started with Computer Vision
    Computer vision is an area of artificial intelligence in which software applications interpret visual input from images or video. In this module, you'll start your exploration of computer vision by learning how to use cognitive services to analyze images and video.
    Lessons

    • Analyzing Images
    • Analyzing Videos

    Module 9: Developing Custom Vision Solutions
    While there are many scenarios where pre-defined general computer vision capabilities can be useful, sometimes you need to train a custom model with your own visual data. In this module, you'll explore the Custom Vision service, and how to use it to create custom image classification and object detection models.
    Lessons

    • Image Classification
    • Object Detection

    Module 10: Detecting, Analyzing, and Recognizing Faces
    Facial detection, analysis, and recognition are common computer vision scenarios. In this module, you'll explore the user of cognitive services to identify human faces.
    Lessons

    • Detecting Faces with the Computer Vision Service
    • Using the Face Service

    Module 11: Reading Text in Images and Documents
    Optical character recognition (OCR) is another common computer vision scenario, in which software extracts text from images or documents. In this module, you'll explore cognitive services that can be used to detect and read text in images, documents, and forms.
    Lessons

    • Reading text with the Computer Vision Service
    • Extracting Information from Forms with the Form Recognizer service

    Module 12: Creating a Knowledge Mining Solution
    Ultimately, many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly important way to build intelligent search solutions that use AI to extract insights from large repositories of digital data and enable users to find and analyze those insights.
    Lessons

    • Implementing an Intelligent Search Solution
    • Developing Custom Skills for an Enrichment Pipeline
    • Creating a Knowledge Store
     
     

    Who should attend AI-102: Designing and Implementing a Microsoft Azure AI Solution including exam voucher

    This training is aimed at Cloud Solution Architects, Azure artificial intelligence designers, and AI developers. You have experience working with data scientists, data engineers, IoT specialists, and software developers.
    Also, you will receive a voucher to make the exam. Enlist today!

    Prerequisites

    The participants should have,

    • Professional experience with cloud technologies, and experience with software development.
    • Implementing solutions in C# or Python.
    • Knowledge of Microsoft Azure and ability to navigate the Azure portal.
    • Familiarity with JSON and REST programming semantics.
    • If you are completely new to Azure AI services, please complete Microsoft Azure AI

    Objectives

    After completing this training, you will be able to:

    • Describe considerations for AI-enabled application development
    • Create, configure, deploy, and secure Azure Cognitive Services
    • Develop applications that analyze text
    • Develop speech-enabled applications
    • Create applications with natural language understanding capabilities
    • Create QnA applications
    • Create conversational solutions with bots
    • Use computer vision services to analyze images and videos
    • Create custom computer vision models
    • Develop applications that detect, analyze, and recognize faces
    • Develop applications that read and process text in images and documents
    • Create intelligent search solutions for knowledge mining

    Exam information

    • Exam duration (minutes): 150-210
    • % extra time for non-native speakers:
    • Number of exam questions: 40-60
    • Minimum correct questions: 0,7
    • Exam style: Multiple choice
    • Open book: No
     
  • Related

    Fields of Expertise
    Microsoft