Analyze Text Using Azure AI Language SDK in Python
Learn to extract key phrases, recognize entities, and detect PII in text using Azure AI Language SDK in Python for document analysis and privacy compliance.

Lab overview
Azure AI Language is a cloud-based service that provides advanced natural language processing capabilities to extract meaningful insights from unstructured text. The service enables organizations and individuals to automatically analyze documents, identify key topics, recognize important entities like people and companies, and detect personally identifiable information to ensure privacy compliance and data protection.
In this lab, you will build Python applications that leverage the Azure AI Language SDK to perform comprehensive text analysis on client documents. You'll learn how to extract key phrases and named entities from business communications, implement PII detection and redaction for privacy compliance.
Objectives
Upon completion of this intermediate level lab, you will be able to:
- Extract key phrases and topics from legal and business documents using the Azure AI Language SDK
- Recognize named entities including people, organizations, dates, and locations in text content
- Detect personally identifiable information (PII) in client communications and sensitive documents
- Implement custom redaction techniques to protect sensitive information while maintaining document readability
- Integrate Azure AI Language text analytics capabilities into Python applications for document processing
- Apply privacy compliance best practices when handling sensitive client information
Who is this lab for?
This lab is designed for:
- Python developers looking to integrate AI-powered text analytics into their applications
- Legal professionals and paralegals who need to process and analyze large volumes of client documents
- Data privacy officers responsible for implementing PII detection and redaction workflows
- Business analysts who want to extract insights from unstructured text data
- Software engineers building document management and compliance systems
- AI/ML practitioners interested in natural language processing and text analytics solutions
Verified against your live environment
An automated validation engine inspects your actual resources and configurations as you work. Completion means the task was performed — not multiple choice, real-world proficiency.
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Related reading
Environment
Every lab includes
- Real environment, pre-credentialed
- Automated checks on every step
- Isolated sandbox, auto cleanup
- AI-recommended next steps
Lab curriculum
- 01
Extracting Key Phrases and Entities from Documents
1 automated check
- 02
Redacting Sensitive Information with PII Detection
1 automated check
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