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AI-900 (Azure AI Fundamentals) Training Course

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Master AI and Machine Learning to excel in the AI-900 Exam


1. Introduction
  • 1. Introduction.html
  • 2.1 Azure AI-900 udemy maruchintech 20240619.pdf
  • 2. Course Material.html

  • 2. Chapter 1 Microsoft Certification Exam and Preparation
  • 1. 1.What is Azure
  • 2. 2-1.Learning Principles
  • 3. 2-2.Overviews of Microsoft Certification Exam
  • 4. 3-1.Basics of Cloud Computing
  • 5. 3-2.Key Features of Cloud Computing
  • 6. 3-3.Categories of Cloud Computing
  • 7. 4-1.Management level and hierarchy
  • 8. 4-2.Region and Availability Zone
  • 9. 4-3.Azure Resource Manager
  • 10. 5.Creating an Azure Account
  • 11. [HOL] Notification

  • 3. 1.Fundamentals of Machine Learning
  • 1. Fundamentals of Machine Learning
  • 2. Flow of Machine Learning
  • 3. Azure Machine Learning
  • 4. [HOL] Azure Machine Learning - AutoML1
  • 5. [HOL] Azure Machine Learning - AutoML2
  • 6. Azure Machine Learning Notebooks
  • 7. [HOL] 1.Basic Operations
  • 8. [HOL] 2.Environment Setup
  • 9. [HOL] 3.Confirmation of data
  • 10. [HOL] 4.Data Transformation
  • 11. [HOL] 5.Handling Missing Data
  • 12. [HOL] 6.Aggregation
  • 13. [HOL] 7.Visualization
  • 14. (Ref) Libraries for Machine Learning
  • Files.zip

  • 4. 2.Clustering
  • 1. 1. What is Cluster Analysis
  • 2. 2. What is Ward Method
  • 3. 3. Ward Method Practice
  • 4. [HOL] Ward Method
  • 5. 4. Results of Ward Method
  • 6. 5. What is K-Means Method
  • 7. [HOL] K-Means Method
  • 8. 6. Results of K-Means Medhod
  • Files.zip

  • 5. 3.Logistic Regression
  • 1. 1. What is Logistic Regression
  • 2. 2. Hands-on for Logistic Regression
  • 3. [HOL] Logistic Regression 1
  • 4. 3. Results of HOL
  • 5. [HOL] Logistic Regression 2
  • 6. [HOL] Logistic Regression 3
  • 7. 4. Confusion Matrix
  • Files.zip

  • 6. 4.Support Vector Machines
  • 1. 1. What is Support Vector Machines
  • 2. 2. Hands-on for Support Vector Machines
  • 3. [HOL] Support Vector Machines
  • 4. 3. Results of HOL
  • Files.zip

  • 7. 5.Ensemble Learning
  • 1. 1. What is Ensemble Learning
  • 2. 2. Hands-on for Ensemble Learning
  • 3. [HOL] Ensemble Learning
  • 4. 3. Results for Ensemble Learning
  • Files.zip

  • 8. 6.Deep Learning
  • 1. 1. What is Deep Learning
  • 2. 2. Activation Function
  • 3. 3. Loss Function
  • 4. 4. Backpropagetion
  • 5. 5. HOL What is Convolutional Neural Network
  • 6. 6.HOL Libraries for Deep Learning
  • 7. 7. HOL Dataset
  • 8. 8. HOL Algorithmis for CNN
  • 9. 9. HOL Comilation
  • 10. 10. HOL Running the model
  • 11. [HOL] Deep Learning
  • Files.zip

  • 9. 7.Azures AI Services
  • 1. Azures AI Services

  • 10. (Ref) Azure Core Services
  • 1. 1. Azure Monitor
  • 2. 2-1. Azure Key Vault
  • 3. 2-2. Microsoft Entra ID No.1
  • 4. 2-2. Microsoft Entra ID No.2
  • 5. 3-1. Azure Policy
  • 6. 3-2. Roll-Based Accecc Policy
  • 7. 3-3. Lock & Tag
  • 8. 4. Azure Virtual Machine
  • 9. 5. Network
  • 10. 5-1. Virtual Network
  • 11. 5-2. Firewalls

  • 11. Chapter3 Practice Test
  • 1. Preparation for Practice Test
  • 2. Practice Test.html

  • 12. Chapter4 Summary
  • 1. Bonus Lecture
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