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AI-900: Microsoft Azure AI Fundamentals Certification Video Training Course
The complete solution to prepare for for your exam with AI-900: Microsoft Azure AI Fundamentals certification video training course. The AI-900: Microsoft Azure AI Fundamentals certification video training course contains a complete set of videos that will provide you with thorough knowledge to understand the key concepts. Top notch prep including Microsoft Azure AI AI-900 exam dumps, study guide & practice test questions and answers.
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05:40:00 Hours
AI-900: Microsoft Azure AI Fundamentals Certification Video Training Course Exam Curriculum
1
Introduction and basics on Azure
5 Lectures
Time 00:29:00
2
Describe AI workloads and considerations
12 Lectures
Time 00:15:00
3
Describe fundamental principles of machine learning on Azure
24 Lectures
Time 02:13:00
4
Describe features of computer vision workloads on Azure
23 Lectures
Time 01:41:00
5
Describe features of Natural Language Processing and Conversational AI workloads
20 Lectures
Time 00:57:00
6
Exam Practice Section
1 Lectures
Time 00:05:00
Introduction and basics on Azure
-
5:00
1. Introduction to Azure
-
5:00
2. The Azure Free Account
-
4:00
3. Concepts in Azure
-
4:00
4. Quick view of the Azure portal
-
11:00
5. Lab - An example of creating a resource in Azure
Describe AI workloads and considerations
-
2:00
1. Machine Learning and Artificial Intelligence
-
1:00
2. Prediction and Forecasting workloads
-
1:00
3. Anomaly Detection Workloads
-
2:00
4. Natural Language Processing Workloads
-
1:00
5. Computer Vision Workloads
-
1:00
6. Conversational AI Workloads
-
2:00
7. Microsoft Guiding principles for response AI - Accountability
-
1:00
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
Describe fundamental principles of machine learning on Azure
-
1:00
1. Section Introduction
-
4:00
2. Why even consider Machine Learning?
-
9:00
3. The Machine Learning Model
-
9:00
4. The Machine Learning Algorithms
-
3:00
5. Different Machine Learning Algorithms
-
4:00
6. Machine Learning Techniques
-
5:00
7. Machine Learning Data - Features and Labels
-
6:00
8. Lab - Azure Machine Learning - Creating a workspace
-
11:00
9. Lab - Building a Classification Machine Learning Pipeline - Your Dataset
-
7:00
10. Lab - Building a Classification Machine Learning Pipeline - Splitting data
-
9:00
11. Optional - Lab - Creating an Azure Virtual Machine
-
6:00
12. Lab - Building a Classification Machine Learning Pipeline - Compute Target
-
6:00
13. Lab - Building a Classification Machine Learning Pipeline - Completion
-
8:00
14. Lab - Building a Classification Machine Learning Pipeline - Results
-
2:00
15. Recap on what's been done so far
-
7:00
16. Lab - Building a Classification Machine Learning Pipeline - Deployment
-
4:00
17. Lab - Installing the POSTMAN tool
-
6:00
18. Lab - Building a Classification Machine Learning Pipeline - Testing
-
9:00
19. Lab - Building a Regression Machine Learning Pipeline - Cleaning Data
-
3:00
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
-
6:00
23. Automated Machine Learning
-
2:00
24. Deleting your resources
Describe features of computer vision workloads on Azure
-
2:00
1. Section Introduction
-
1:00
2. Azure Cognitive Services
-
3:00
3. Introduction to Azure Computer Vision solutions
-
5:00
4. A look at the Computer Vision service
-
4:00
5. Lab - Setting up Visual Studio 2019
-
12:00
6. Lab - Computer Vision - Basic Object Detection - Visual Studio 2019
-
2:00
7. Lab - Computer Vision - Restrictions example
-
3:00
8. Lab - Computer Vision - Object Bounding Coordinates - Visual Studio 2019
-
2:00
9. Lab - Computer Vision - Brand Image - Visual Studio 2019
-
5:00
10. Lab - Computer Vision - Via the POSTMAN tool
-
2:00
11. The benefits of the Cognitive services
-
2:00
12. Another example on Computer Vision - Bounding Coordinates
-
5:00
13. Lab - Computer Vision - Optical Character Recognition
-
2:00
14. Face API
-
3:00
15. Lab - Computer Vision - Analyzing a Face
-
3:00
16. A quick look at the Face service
-
6:00
17. Lab - Face API - Using Visual Studio 2019
-
5:00
18. Lab - Face API - Using POSTMAN tool
-
7:00
19. Lab - Face Verify API - Using POSTMAN tool
-
8:00
20. Lab - Face Find Similar API - Using POSTMAN tool
-
9:00
21. Lab - Custom Vision
-
2:00
22. A quick look at the Form Recognizer service
-
8:00
23. Lab - Form Recognizer
Describe features of Natural Language Processing and Conversational AI workloads
-
1:00
1. Section Introduction
-
3:00
2. Natural Language Processing
-
1:00
3. A quick look at the Text Analytics
-
4:00
4. Lab - Text Analytics API - Key phrases
-
1:00
5. Lab - Text Analytics API - Language Detection
-
1:00
6. Lab - Text Analytics Service - Sentiment Analysis
-
3:00
7. Lab - Text Analytics Service - Entity Recognition
-
3:00
8. Lab - Translator Service
-
1:00
9. A quick look at the Speech Service
-
4:00
10. Lab - Speech Service - Speech to text
-
1:00
11. Lab - Speech Service - Text to speech
-
2:00
12. Language Understanding Intelligence Service
-
8:00
13. Lab - Working with LUIS - Using pre-built domains
-
4:00
14. Lab - Working with LUIS - Adding our own intents
-
2:00
15. Lab - Working with LUIS - Adding Entities
-
2:00
16. Lab - Working with LUIS - Publishing your model
-
2:00
17. QnA Maker service
-
9:00
18. Lab - QnA Maker service
-
2:00
19. Bot Framework
-
3:00
20. Example of Bot Framework in Azure
Exam Practice Section
-
5:00
1. About the exam
About AI-900: Microsoft Azure AI Fundamentals Certification Video Training Course
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AI-900 Premium Bundle
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- Premium File 256 Questions & Answers. Last update: Jun 09, 2025
- Training Course 85 Video Lectures
- Study Guide 391 Pages
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