Microsoft Certified Azure AI Fundamentals (AI-900)

سرفصل های دوره

1. Introducing Machine Learning Workloads

1. Introducing Machine Learning Workloads

2. AI vs Machine Learning

3. Language Processing

4. Object Detection

5. Data Mining

6. Anomaly Detection

7. Where Azure Fits In

2. The Machine Learning with Python Crash Course

1. Introducing the Machine Learning Crash Course

2. Install the Tools

3. Explore a Jupyter Notebook in VS Code

4. Get and Import Data

5. X and y

6. Train the Model

7. Score the Model

8. Save and Use the Model

3. Explore Azure ML Studio and AutoML

1. Introducing Azure Machine Learning Studio and AutoML

2. Deploy Azure Machine Learning Workspace

3. Explore Machine Learning Studio Features

4. Ingest Data

5. Create an AutoML Job

6. Review the Results of the AutoML Job

4. Create a Regression Model Pipeline

1. Introducing a Basic Regression Model Pipeline with Azure ML Designer

2. Understand the Designer Layout

3. Explore Pipeline Components

4. Build the Pipeline

5. Run and Review the Job

5. Understanding Computer Vision Services in Microsoft Azure

1. Intro to Microsoft Azure Computer Vision Services

2. Understanding Computer Vision Data Workflow

3. Value Proposition of Microsoft Azure Cognitive Services

4. Pricing Structure for Azure Computer Vision Services

5. Provision Azure Cognitive Services in Portal

6. Testing Azure Cognitive Services with Vision Studio

6. Understanding Common Computer Vision Scenarios

1. Understanding Image Segmentation and Facial Analysis

2. Using Object Detection for Commercial Security

3. Using Facial Recognition for Access Control Solutions

4. Improve Retail Decision Making with Computer Vision

5. Manage Workplace Safety with Computer Vision

6. Environmental Management with Computer Vision

7. Understand NLP and Azure Cognitive Services

1. Understand Concepts of Natural Language Processing

2. Language Detection

3. Sentiment Detection

4. Key Words and Phrase Detection

5. Entity Detection

6. Crash Course Develop a Logic App to leverage Cognitive Services

8. Consider Ethics of Machine Learning and AI

1. Introducing Responsible Usage of AI

2. Using AI in School and Work

3. The 6 Principles of Responsible AI

4. Fairness

5. Reliability and Safety

6. Privacy and Security

7. Inclusiveness

8. Transparency

9. Accountability

9. Create a Basic Classification Pipeline

1. Designer Refresher

2. Understanding Classification

3. Build the Pipeline

4. Run and Review the Pipeline

5. Introducing Basic Classification Pipelines in Azure ML Designer

10. Building Microsoft Azure Custom Vision Models

1. Intro to Microsoft Azure Cognitive Services Custom Vision

2. Competing Software Solutions for Computer Vision Tasks

3. Create Azure Custom Vision Project Resource

4. Gathering Data for Object Detection in Custom Vision

5. Initiate Training Process for Azure Custom Vision

6. Test Azure Custom Vision Model with Additional Data

7. Improve Accuracy of Azure Custom Vision Models

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تولید کننده: CBT Nuggets