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Curriculum for AI-900 Certification Video Course
Name of Video | Time |
---|---|
![]() 1. Introduction to Azure |
5:00 |
![]() 2. The Azure Free Account |
5:00 |
![]() 3. Concepts in Azure |
4:00 |
![]() 4. Quick view of the Azure portal |
4:00 |
![]() 5. Lab - An example of creating a resource in Azure |
11:00 |
Name of Video | Time |
---|---|
![]() 1. Machine Learning and Artificial Intelligence |
2:00 |
![]() 2. Prediction and Forecasting workloads |
1:00 |
![]() 3. Anomaly Detection Workloads |
1:00 |
![]() 4. Natural Language Processing Workloads |
2:00 |
![]() 5. Computer Vision Workloads |
1:00 |
![]() 6. Conversational AI Workloads |
1:00 |
![]() 7. Microsoft Guiding principles for response AI - Accountability |
2:00 |
![]() 8. Microsoft Guiding principles for response AI - Reliability and Safety |
1:00 |
![]() 9. Microsoft Guiding principles for response AI - Privacy and Security |
1:00 |
![]() 10. Microsoft Guiding principles for response AI - Transparency |
1:00 |
![]() 11. Microsoft Guiding principles for response AI - Inclusiveness |
1:00 |
![]() 12. Microsoft Guiding principles for response AI - Fairness |
1:00 |
Name of Video | Time |
---|---|
![]() 1. Section Introduction |
1:00 |
![]() 2. Why even consider Machine Learning? |
4:00 |
![]() 3. The Machine Learning Model |
9:00 |
![]() 4. The Machine Learning Algorithms |
9:00 |
![]() 5. Different Machine Learning Algorithms |
3:00 |
![]() 6. Machine Learning Techniques |
4:00 |
![]() 7. Machine Learning Data - Features and Labels |
5:00 |
![]() 8. Lab - Azure Machine Learning - Creating a workspace |
6:00 |
![]() 9. Lab - Building a Classification Machine Learning Pipeline - Your Dataset |
11:00 |
![]() 10. Lab - Building a Classification Machine Learning Pipeline - Splitting data |
7:00 |
![]() 11. Optional - Lab - Creating an Azure Virtual Machine |
9:00 |
![]() 12. Lab - Building a Classification Machine Learning Pipeline - Compute Target |
6:00 |
![]() 13. Lab - Building a Classification Machine Learning Pipeline - Completion |
6:00 |
![]() 14. Lab - Building a Classification Machine Learning Pipeline - Results |
8:00 |
![]() 15. Recap on what's been done so far |
2:00 |
![]() 16. Lab - Building a Classification Machine Learning Pipeline - Deployment |
7:00 |
![]() 17. Lab - Installing the POSTMAN tool |
4:00 |
![]() 18. Lab - Building a Classification Machine Learning Pipeline - Testing |
6:00 |
![]() 19. Lab - Building a Regression Machine Learning Pipeline - Cleaning Data |
9:00 |
![]() 20. Lab - Building a Regression Machine Learning Pipeline - Complete Pipeline |
3:00 |
![]() 21. Lab - Building a Regression Machine Learning Pipeline - Results |
3:00 |
![]() 22. Feature Engineering |
3:00 |
![]() 23. Automated Machine Learning |
6:00 |
![]() 24. Deleting your resources |
2:00 |
Name of Video | Time |
---|---|
![]() 1. Section Introduction |
2:00 |
![]() 2. Azure Cognitive Services |
1:00 |
![]() 3. Introduction to Azure Computer Vision solutions |
3:00 |
![]() 4. A look at the Computer Vision service |
5:00 |
![]() 5. Lab - Setting up Visual Studio 2019 |
4:00 |
![]() 6. Lab - Computer Vision - Basic Object Detection - Visual Studio 2019 |
12:00 |
![]() 7. Lab - Computer Vision - Restrictions example |
2:00 |
![]() 8. Lab - Computer Vision - Object Bounding Coordinates - Visual Studio 2019 |
3:00 |
![]() 9. Lab - Computer Vision - Brand Image - Visual Studio 2019 |
2:00 |
![]() 10. Lab - Computer Vision - Via the POSTMAN tool |
5:00 |
![]() 11. The benefits of the Cognitive services |
2:00 |
![]() 12. Another example on Computer Vision - Bounding Coordinates |
2:00 |
![]() 13. Lab - Computer Vision - Optical Character Recognition |
5:00 |
![]() 14. Face API |
2:00 |
![]() 15. Lab - Computer Vision - Analyzing a Face |
3:00 |
![]() 16. A quick look at the Face service |
3:00 |
![]() 17. Lab - Face API - Using Visual Studio 2019 |
6:00 |
![]() 18. Lab - Face API - Using POSTMAN tool |
5:00 |
![]() 19. Lab - Face Verify API - Using POSTMAN tool |
7:00 |
![]() 20. Lab - Face Find Similar API - Using POSTMAN tool |
8:00 |
![]() 21. Lab - Custom Vision |
9:00 |
![]() 22. A quick look at the Form Recognizer service |
2:00 |
![]() 23. Lab - Form Recognizer |
8:00 |
Name of Video | Time |
---|---|
![]() 1. Section Introduction |
1:00 |
![]() 2. Natural Language Processing |
3:00 |
![]() 3. A quick look at the Text Analytics |
1:00 |
![]() 4. Lab - Text Analytics API - Key phrases |
4:00 |
![]() 5. Lab - Text Analytics API - Language Detection |
1:00 |
![]() 6. Lab - Text Analytics Service - Sentiment Analysis |
1:00 |
![]() 7. Lab - Text Analytics Service - Entity Recognition |
3:00 |
![]() 8. Lab - Translator Service |
3:00 |
![]() 9. A quick look at the Speech Service |
1:00 |
![]() 10. Lab - Speech Service - Speech to text |
4:00 |
![]() 11. Lab - Speech Service - Text to speech |
1:00 |
![]() 12. Language Understanding Intelligence Service |
2:00 |
![]() 13. Lab - Working with LUIS - Using pre-built domains |
8:00 |
![]() 14. Lab - Working with LUIS - Adding our own intents |
4:00 |
![]() 15. Lab - Working with LUIS - Adding Entities |
2:00 |
![]() 16. Lab - Working with LUIS - Publishing your model |
2:00 |
![]() 17. QnA Maker service |
2:00 |
![]() 18. Lab - QnA Maker service |
9:00 |
![]() 19. Bot Framework |
2:00 |
![]() 20. Example of Bot Framework in Azure |
3:00 |
Name of Video | Time |
---|---|
![]() 1. About the exam |
5:00 |
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Microsoft AI-900 Training Course
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