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Course name Microsoft AI-900: Microsoft Azure AI Fundamentals

Corresponding Certification: Microsoft Certified: Azure AI Fundamentals

AI-900 Video Course

AI-900 Video Course is developed by Microsoft Professionals to help you pass the AI-900 exam.

You Will Learn:

Was 43.99 USD
Now 39.99 USD

Description

This course will improve your knowledge and skills required to pass Microsoft Azure AI Fundamentals exam.

Curriculum For This Course

  • 1. Introduction and basics on Azure 5 Videos 00:29:00
    • Introduction to Azure 5:00
    • The Azure Free Account 5:00
    • Concepts in Azure 4:00
    • Quick view of the Azure portal 4:00
    • Lab - An example of creating a resource in Azure 11:00
  • 2. Describe AI workloads and considerations 12 Videos 00:15:00
    • Machine Learning and Artificial Intelligence 2:00
    • Prediction and Forecasting workloads 1:00
    • Anomaly Detection Workloads 1:00
    • Natural Language Processing Workloads 2:00
    • Computer Vision Workloads 1:00
    • Conversational AI Workloads 1:00
    • Microsoft Guiding principles for response AI - Accountability 2:00
    • Microsoft Guiding principles for response AI - Reliability and Safety 1:00
    • Microsoft Guiding principles for response AI - Privacy and Security 1:00
    • Microsoft Guiding principles for response AI - Transparency 1:00
    • Microsoft Guiding principles for response AI - Inclusiveness 1:00
    • Microsoft Guiding principles for response AI - Fairness 1:00
  • 3. Describe fundamental principles of machine learning on Azure 24 Videos 02:13:00
    • Section Introduction 1:00
    • Why even consider Machine Learning? 4:00
    • The Machine Learning Model 9:00
    • The Machine Learning Algorithms 9:00
    • Different Machine Learning Algorithms 3:00
    • Machine Learning Techniques 4:00
    • Machine Learning Data - Features and Labels 5:00
    • Lab - Azure Machine Learning - Creating a workspace 6:00
    • Lab - Building a Classification Machine Learning Pipeline - Your Dataset 11:00
    • Lab - Building a Classification Machine Learning Pipeline - Splitting data 7:00
    • Optional - Lab - Creating an Azure Virtual Machine 9:00
    • Lab - Building a Classification Machine Learning Pipeline - Compute Target 6:00
    • Lab - Building a Classification Machine Learning Pipeline - Completion 6:00
    • Lab - Building a Classification Machine Learning Pipeline - Results 8:00
    • Recap on what's been done so far 2:00
    • Lab - Building a Classification Machine Learning Pipeline - Deployment 7:00
    • Lab - Installing the POSTMAN tool 4:00
    • Lab - Building a Classification Machine Learning Pipeline - Testing 6:00
    • Lab - Building a Regression Machine Learning Pipeline - Cleaning Data 9:00
    • Lab - Building a Regression Machine Learning Pipeline - Complete Pipeline 3:00
    • Lab - Building a Regression Machine Learning Pipeline - Results 3:00
    • Feature Engineering 3:00
    • Automated Machine Learning 6:00
    • Deleting your resources 2:00
  • 4. Describe features of computer vision workloads on Azure 23 Videos 01:41:00
    • Section Introduction 2:00
    • Azure Cognitive Services 1:00
    • Introduction to Azure Computer Vision solutions 3:00
    • A look at the Computer Vision service 5:00
    • Lab - Setting up Visual Studio 2019 4:00
    • Lab - Computer Vision - Basic Object Detection - Visual Studio 2019 12:00
    • Lab - Computer Vision - Restrictions example 2:00
    • Lab - Computer Vision - Object Bounding Coordinates - Visual Studio 2019 3:00
    • Lab - Computer Vision - Brand Image - Visual Studio 2019 2:00
    • Lab - Computer Vision - Via the POSTMAN tool 5:00
    • The benefits of the Cognitive services 2:00
    • Another example on Computer Vision - Bounding Coordinates 2:00
    • Lab - Computer Vision - Optical Character Recognition 5:00
    • Face API 2:00
    • Lab - Computer Vision - Analyzing a Face 3:00
    • A quick look at the Face service 3:00
    • Lab - Face API - Using Visual Studio 2019 6:00
    • Lab - Face API - Using POSTMAN tool 5:00
    • Lab - Face Verify API - Using POSTMAN tool 7:00
    • Lab - Face Find Similar API - Using POSTMAN tool 8:00
    • Lab - Custom Vision 9:00
    • A quick look at the Form Recognizer service 2:00
    • Lab - Form Recognizer 8:00
  • 5. Describe features of Natural Language Processing and Conversational AI workloads 20 Videos 00:57:00
    • Section Introduction 1:00
    • Natural Language Processing 3:00
    • A quick look at the Text Analytics 1:00
    • Lab - Text Analytics API - Key phrases 4:00
    • Lab - Text Analytics API - Language Detection 1:00
    • Lab - Text Analytics Service - Sentiment Analysis 1:00
    • Lab - Text Analytics Service - Entity Recognition 3:00
    • Lab - Translator Service 3:00
    • A quick look at the Speech Service 1:00
    • Lab - Speech Service - Speech to text 4:00
    • Lab - Speech Service - Text to speech 1:00
    • Language Understanding Intelligence Service 2:00
    • Lab - Working with LUIS - Using pre-built domains 8:00
    • Lab - Working with LUIS - Adding our own intents 4:00
    • Lab - Working with LUIS - Adding Entities 2:00
    • Lab - Working with LUIS - Publishing your model 2:00
    • QnA Maker service 2:00
    • Lab - QnA Maker service 9:00
    • Bot Framework 2:00
    • Example of Bot Framework in Azure 3:00
  • 6. Exam Practice Section 1 Videos 00:05:00
    • About the exam 5:00