Rise of the Machines

Overview

Explore machine learning and predictive analytics with Azure ML in this primer, led by Microsoft's Director of Architecture Josh Holmes.

Syllabus

• Course Introduction and Objectives
Overview of Machine Learning and Predictive Analytics
Course Goals and Outcomes
• Introduction to Machine Learning
Basics of Machine Learning
Key Concepts in Predictive Analytics
Types of Machine Learning Models
• Overview of Azure Machine Learning
Introduction to Azure Machine Learning Studio
Setting up Azure ML Environment
Navigating Azure ML Workspace
• Data Preparation and Exploration
Importing and Cleaning Data
Data Transformation Techniques
Visualizing Data with Azure ML
• Building Machine Learning Models
Selecting Algorithms
Training and Validating Models
Evaluating Model Performance
• Advanced Azure ML Features
Automated Machine Learning
Using Pre-built Models in Azure
Hyperparameter Tuning
• Deploying and Managing Models
Deploying Models as Web Services
Monitoring Deployed Models
Managing Model Lifecycle in Azure ML
• Case Studies and Real-world Applications
Industry-specific Use Cases
Success Stories Utilizing Azure ML
• Ethical Considerations in AI
Understanding Bias in AI Models
Ensuring Privacy and Security with Azure ML
• Hands-on Lab Sessions
End-to-End Project using Azure ML
Collaboration and Group Work in Azure
• Course Summary and Next Steps
Recap of Key Learnings
Resources for Further Study in AI and Azure

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Subjects

Conference Talks