Getting Started with Azure AI and ML

Welcome to the Azure AI and Machine Learning documentation portal. This section provides the foundational knowledge and steps to begin your journey with Microsoft's powerful cloud-based artificial intelligence and machine learning services.

What is Azure AI and ML?

Azure AI and Machine Learning offers a comprehensive suite of services that empower developers and data scientists to build, train, and deploy machine learning models at scale. It provides:

Pre-built AI models: Leverage ready-to-use cognitive services for vision, speech, language, and decision-making.
Machine Learning platforms: Utilize Azure Machine Learning for end-to-end MLOps, including data preparation, model training, deployment, and monitoring.
Responsible AI tools: Ensure your AI systems are fair, reliable, safe, private, secure, inclusive, transparent, and accountable.
Scalable infrastructure: Deploy models on a global scale with robust and flexible computing options.

Before You Begin: Prerequisites

To make the most of this guide, ensure you have the following:

An active Azure subscription. A free trial is available.
Basic understanding of cloud computing concepts.
Familiarity with Python or C# (depending on your chosen service).
(Optional) An Azure Machine Learning workspace for advanced ML scenarios.

Your First Steps in Azure AI and ML

Let's dive into practical steps to get you started:

Explore Cognitive Services

Discover pre-built AI capabilities that can be easily integrated into your applications. Try out services like Text Analytics, Computer Vision, or Speech-to-Text.

Get Started with Cognitive Services

Set Up Azure Machine Learning

Create an Azure Machine Learning workspace and learn how to manage your ML projects, datasets, experiments, and models.

Create Your ML Workspace

Build Your First Model

Follow guided tutorials to train and deploy a simple machine learning model using Azure Machine Learning Designer or Python SDK.

Train Your First Model

Key Learning Resources

We've curated a selection of essential resources to accelerate your learning:

Quickstarts: Get hands-on experience with specific Azure AI and ML services. View Quickstarts
Tutorials: Comprehensive guides covering various AI/ML tasks and scenarios. Browse Tutorials
Conceptual Overviews: Understand the core principles and architecture of Azure AI and ML. Read Concepts
SDK Documentation: For developers using Python or .NET. SDK Documentation

What's Next?

Once you've completed the initial setup and basic tutorials, you can explore more advanced topics such as:

Deploying models as web services and containerized applications.
Monitoring and managing deployed models in production.
Implementing Responsible AI practices in your solutions.
Leveraging specialized AI services like Azure OpenAI.

Continue your learning journey by exploring the Advanced Topics section.