Course
Develop Natural Language Processing Solutions with Azure AI Services – Intensive Training («AI3X3»)
Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language.
Duration
1 day
Price
900.–
Course documents
Official Microsoft Courseware on Microsoft Learn
Course facts
Key Learnings
- Implementing multi-turn conversation and active learning
- Creating a question answering bot to interact with using natural language
- Provisioning Azure resources for Azure AI Language resource
- Defining intents, utterances, and entities
- Using patterns to differentiate similar utterances and pre-built entity components
- Training, testing, publishing, and reviewing an Azure AI Language model
- Understanding types of classification projects
- Building a custom text classification project
- Tagging data, training, and deploying a model
- Submitting classification tasks from your own app
- Provisioning a Translator resource
- Understanding language detection, translation, and transliteration
- Specifying translation options
- Defining custom translations
- Provisioning an Azure resource for the Azure AI Speech service
- Using the Azure AI Speech to text API to implement speech recognition
- Using the Text to speech API to implement speech synthesis
- Configuring audio format and voices
- Using Speech Synthesis Markup Language (SSML)
- Provisioning Azure resources for speech translation
- Generating text translation from speech
- Synthesizing spoken translations
Content
1 Analyze text with Azure AI Language
The Azure AI Language service enables you to create intelligent apps and services that extract semantic information from text.
2 Create question answering solutions with Azure AI Language
The question answering capability of the Azure AI Language service makes it easy to build applications in which users ask questions using natural language and receive appropriate answers.
3 Build a conversational language understanding model
The Azure AI Language conversational language understanding service (CLU) enables you to train a model that apps can use to extract meaning from natural language.
4 Create a custom text classification solution
The Azure AI Language service enables processing of natural language to use in your own app. Learn how to build a custom text classification project.
5 Custom named entity recognition
Build a custom entity recognition solution to extract entities from unstructured documents.
6 Translate text with Azure AI Translator service
The Translator service enables you to create intelligent apps and services that can translate text between languages.
7 Create speech-enabled apps with Azure AI services
The Azure AI Speech service enables you to build speech-enabled applications. This module focuses on using the speech-to-text and text to speech APIs, which enable you to create apps that are capable of speech recognition and speech synthesis.
8 Translate speech with Azure AI Speech service
Translation of speech builds on speech recognition by recognizing and transcribing spoken input in a specified language, and returning translations of the transcription in one or more other languages.
Target audience
The audience for this course includes AI engineers and developers.
Requirements
- Familiarity with Azure and the Azure portal
- Experience programming with C# or Python
- If you have no previous programming experience, we recommend you complete the Take your first steps with C# or Take your first steps with Python learning path before starting this workshop
Additional information
This workshop is integrated into the course AI-102: Designing and Implementing a Microsoft Azure AI Solution.
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Questions
We currently do not have any dates scheduled.
But we can arrange one for you. We will be happy to advise you individually on your course planning.
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