
Create a new subscription and an Azure AI Language resource in a MAS Language resource group with a storage account; enable sentiment analysis, key phrase extraction, and custom text classification.
Integrate pii detection into existing python code by replacing recognize_entities with recognize_pii_entities and optionally print the redacted_text for the response; filter entities by confidence_score under 0.9.
Explore entity linking and disambiguation in Azure AI Language by analyzing how context differentiates meanings like Mars (planet vs chocolate bar), and interpreting linked entities and confidence scores.
Explore sentiment analysis and opinion mining in Azure AI Language, classifying as positive, neutral, or negative across over 90 languages, with targets, mixed sentiment, assessments, and $1 per 1,000 records.
Microsoft Azure allows you to extract information from your text. Among other things, you can classify and summarize text, and ask it questions.
In this 3 hour course we’ll cover the skills that you need for the APL-3003 Microsoft Applied Skills credential for building a natural language processing solution with Azure AI Language.
Note: this Applied Skill credential was retired on 30 June 2026. However, the information in this course is still useful to learn how to use Azure AI Language.
It will also help with the Microsoft exam AI-102 "Designing and Implementing a Microsoft Azure AI Solution".
Please note: This course is not affiliated with, endorsed by, or sponsored by Microsoft.
First, we’ll sign up for a free Azure subscription. Then, we’ll create a Language resource, and use it to analyze text. We’ll use the pre-built models to detect the language, extract key phrases, recognise entities and sentiment, and more.
After that, we’ll analyze the text using Python and C#. We connect to the Language resource and analyse text, extracting the information for use in our own programmes.
Finally, we’ll create our own custom models for text classification and named entity recognition extraction. We’ll upload documents into an Azure Storage Account container, train the model based on labels, and test it using the portal, Python and C#.
There are several practice activities and quizzes throughout the course, so you can be sure that you are learning.
By the end of the course, you'll be able to analyse your own text in the portal and using Python and C#, and perhaps even take the official Microsoft assessment. That would look great on your CV or resume.