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AI-900 Course Azure AI Fundamentals with Virtual Simulations

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Get prepared for the AI-900 exam with instructor led labs and hands on simulations available 24/7


1. Introduction
  • 1. Welcome to the course!
  • 2. Creating a free Azure Account
  • 3. Order of concepts covered in the course
  • 4.1 Introduction to AI.pdf
  • 4. Introduction to artificial intelligence terminology
  • 5. DONT SKIP! Using Assignments in the course

  • 2. Identify features of common AI workloads
  • 1. Understanding features of anomaly detection workloads
  • 2. Example of univariate anomaly detection
  • 3. Example of multivariate anomaly detection
  • 4. What is computer vision workloads
  • 5.1 natural-language-processing.zip
  • 5. Conceptual usage of natural language processing workloads
  • 6.1 knowledge mining.zip
  • 6. Visualizing knowledge mining principals
  • 7. SIMULATION Create an anomaly detector AI resource.html

  • 3. Identify guiding principles for responsible AI
  • 1.1 responsible ai.zip
  • 1. Introduction to responsible AI
  • 2.1 Fairness and Inclusiveness.pdf
  • 2. Fairness and Inclusiveness in an AI solution
  • 3.1 Reliability and Safety.pdf
  • 3. Reliability and safety in an AI solution
  • 4.1 Privacy and Security.pdf
  • 4. Privacy and security in an AI solution
  • 5.1 Transparency.pdf
  • 5. Transparency in an AI solution
  • 6.1 Accountability.pdf
  • 6. Accountability in an AI solution

  • 4. Identify common machine learning types
  • 1. Create an Azure Machine Learning workspace for machine learning scenarios
  • 2.1 regression machine learning.zip
  • 2. What is regression machine learning
  • 3. Building a pipeline with regression machine learning for cleaning a dataset
  • 4. Implement a regression machine learning scenario
  • 5. Evaluating the results of regression machine learning scenarios
  • 6.1 classification machine learning.zip
  • 6. What is classification machine learning
  • 7. Implement a classification machine learning scenario in Azure
  • 8.1 confusion matrix.zip
  • 8. Understanding labels on a confusion matrix
  • 9.1 clustering machine learning.zip
  • 9. Clustering machine learning example
  • 10. SIMULATION Create an Azure Machine Learning workspace.html
  • 11. SIMULATION Use ML Studio to create a pipeline automobile sample.html

  • 5. Describe core machine learning concepts
  • 1. Understanding features and labels in a dataset for machine learning
  • 2. How training and validation datasets are used in machine learning
  • 3. SIMULATION Open the Census pipeline in ML Studio.html

  • 6. Describe capabilities of visual tools in Azure Machine Learning Studio
  • 1. Using Automated machine learning
  • 2. Understanding Azure Machine Learning Designer
  • 3. Cleaning up our existing Azure resources
  • 4. SIMULATION Setup an Auto ML project for a PopularMovie.csv file..html

  • 7. Identify common types of computer vision solutions
  • 1.1 Azure Computer Vision Solutions.pdf
  • 1. What are the Azure computer vision solutions
  • 2. Creating an Azure computer vision resource
  • 3. Image classification and object detection solutions in vision studio
  • 4. Optical character recognition solutions in vision studio
  • 5. Facial detection and facial analysis solutions in vision studio
  • 6. Spatial analysis solutions in vision studio

  • 8. Identify Azure tools and services for computer vision tasks
  • 1. Using the POSTMAN tool for interacting with Azure AI Services
  • 2. Implementing the capabilities of the Computer Vision service
  • 3. Implementing the capabilities of the Custom Vision service
  • 4. Implementing the capabilities of the Face service
  • 5. Implementing the capabilities of the Form Recognizer service
  • 6. SIMULATION Create a Computer Vision Resource using the F Tier.html

  • 9. Identify features of common NLP Workload Scenarios
  • 1. What are the Azure AI Language features
  • 2. Creating a language service resource in Azure
  • 3. Trying out key phrase extraction
  • 4. Trying out key entity recognition
  • 5. Trying out key sentiment analysis
  • 6. Trying out key language modeling
  • 7. Trying out key speech recognition and synthesis
  • 8. Trying out key translation

  • 10. Identify Azure tools and services for NLP workloads
  • 1.1 language example.zip
  • 1. Exploring the capabilities of the Language service
  • 2. Exploring the capabilities of the Speech service
  • 3. Exploring the capabilities of the Translator service
  • 4.1 Questions and Answers Example.txt
  • 4. Configuring Azure AI language to support questions and answers support
  • 5. SIMULATION Create a language resource and open the language studio.html

  • 11. Identify considerations for conversational AI solutions on Azure
  • 1.1 Azure AI Bot Features.pdf
  • 1. Understanding the features and uses for bots
  • 2. Capabilities of Power Virtual Agents and the Azure Bot service
  • 3. Remove existing resource
  • 4. SIMULATION Create an Azure Bot using the free tier. Check channel health.html

  • 12. FINAL - Where do I go from here
  • 1. BONUS Lecture
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    تاریخ انتشار: ۱۲ آذر ۱۴۰۲
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