AI-900: Microsoft Azure AI Fundamentals

2m 1. Machine Learning and Artificial Intelligence 1m 2. Prediction and Forecasting workloads 1m 3. Anomaly Detection Workloads 2m 4. Natural Language Processing Workloads 1m 5. Computer Vision Workloads 1m 6. Conversational AI Workloads 2m 7. Microsoft Guiding principles for response AI - Accountability 1m 8. Microsoft Guiding principles for response AI - Reliability and Safety 1m 9. Microsoft Guiding principles for response AI - Privacy and Security 1m 10. Microsoft Guiding principles for response AI - Transparency 1m 11. Microsoft Guiding principles for response AI - Inclusiveness 1m 12. Microsoft Guiding principles for response AI - Fairness

1m 1. Section Introduction 4m 2. Why even consider Machine Learning? 9m 3. The Machine Learning Model 9m 4. The Machine Learning Algorithms 3m 5. Different Machine Learning Algorithms 4m 6. Machine Learning Techniques 5m 7. Machine Learning Data - Features and Labels 6m 8. Lab - Azure Machine Learning - Creating a workspace 11m 9. Lab - Building a Classification Machine Learning Pipeline - Your Dataset 7m 10. Lab - Building a Classification Machine Learning Pipeline - Splitting data 9m 11. Optional - Lab - Creating an Azure Virtual Machine 6m 12. Lab - Building a Classification Machine Learning Pipeline - Compute Target 6m 13. Lab - Building a Classification Machine Learning Pipeline - Completion 8m 14. Lab - Building a Classification Machine Learning Pipeline - Results 2m 15. Recap on what's been done so far 7m 16. Lab - Building a Classification Machine Learning Pipeline - Deployment 4m 17. Lab - Installing the POSTMAN tool 6m 18. Lab - Building a Classification Machine Learning Pipeline - Testing 9m 19. Lab - Building a Regression Machine Learning Pipeline - Cleaning Data 3m 20. Lab - Building a Regression Machine Learning Pipeline - Complete Pipeline 3m 21. Lab - Building a Regression Machine Learning Pipeline - Results 3m 22. Feature Engineering 6m 23. Automated Machine Learning 2m 24. Deleting your resources

2m 1. Section Introduction 1m 2. Azure Cognitive Services 3m 3. Introduction to Azure Computer Vision solutions 5m 4. A look at the Computer Vision service 4m 5. Lab - Setting up Visual Studio 2019 12m 6. Lab - Computer Vision - Basic Object Detection - Visual Studio 2019 2m 7. Lab - Computer Vision - Restrictions example 3m 8. Lab - Computer Vision - Object Bounding Coordinates - Visual Studio 2019 2m 9. Lab - Computer Vision - Brand Image - Visual Studio 2019 5m 10. Lab - Computer Vision - Via the POSTMAN tool 2m 11. The benefits of the Cognitive services 2m 12. Another example on Computer Vision - Bounding Coordinates 5m 13. Lab - Computer Vision - Optical Character Recognition 2m 14. Face API 3m 15. Lab - Computer Vision - Analyzing a Face 3m 16. A quick look at the Face service 6m 17. Lab - Face API - Using Visual Studio 2019 5m 18. Lab - Face API - Using POSTMAN tool 7m 19. Lab - Face Verify API - Using POSTMAN tool 8m 20. Lab - Face Find Similar API - Using POSTMAN tool 9m 21. Lab - Custom Vision 2m 22. A quick look at the Form Recognizer service 8m 23. Lab - Form Recognizer

1m 1. Section Introduction 3m 2. Natural Language Processing 1m 3. A quick look at the Text Analytics 4m 4. Lab - Text Analytics API - Key phrases 1m 5. Lab - Text Analytics API - Language Detection 1m 6. Lab - Text Analytics Service - Sentiment Analysis 3m 7. Lab - Text Analytics Service - Entity Recognition 3m 8. Lab - Translator Service 1m 9. A quick look at the Speech Service 4m 10. Lab - Speech Service - Speech to text 1m 11. Lab - Speech Service - Text to speech 2m 12. Language Understanding Intelligence Service 8m 13. Lab - Working with LUIS - Using pre-built domains 4m 14. Lab - Working with LUIS - Adding our own intents 2m 15. Lab - Working with LUIS - Adding Entities 2m 16. Lab - Working with LUIS - Publishing your model 2m 17. QnA Maker service 9m 18. Lab - QnA Maker service 2m 19. Bot Framework 3m 20. Example of Bot Framework in Azure

5m 1. About the exam