Develop natural language solutions in Azure
AI-3003(1 day)
Develop natural language solutions in Azure
6.000 DKK
(excl. VAT)
Course calendar
Description
Language understanding and processing are core components of modern AI solutions. This course gives you the skills to develop and deploy intelligent applications that can analyze text, answer complex questions, understand conversations, and translate or generate speech.
You learn to use Azure AI Language to analyze sentiment, identify key phrases, and extract named entities from text. You work with question answering, custom text classification, and conversational language understanding (CLU), and gain experience building and training your own models. We also dive into speech-enabled solutions with Azure AI Speech, where you learn to integrate speech recognition, speech synthesis, and translation, and to develop speech-enabled chatbots with generative AI.
Topics include:
- Text analysis with Azure AI Language
- Developing question answering solutions with knowledge bases
- Building and training CLU and NER models
- Custom text classification and entity recognition
- Translation and speech recognition with Azure AI Speech
- Developing speech-enabled AI applications
This course is for developers, AI engineers, and data scientists who want to build robust, scalable NLP and speech applications in Azure.
This course is part of AI-103: Develop AI apps and agents on Azure, which gives you a complete, in-depth overview of the entire AI platform in Azure.
We recommend AI-103 if you want a more structured program where you work with several technologies together and build a stronger foundation for building AI solutions on Azure.
Prerequisites
To get the most out of the course, we recommend experience or knowledge equivalent to:
Next steps
If you want to build on your skills, these may be relevant:
Module overview
- Detect text language
- Analyze sentiment (positive, negative, neutral)
- Extract key phrases
- Recognize named entities and link to sources
- Understand question-answering vs general language understanding
- Create, test, and publish a knowledge base
- Implement multi-turn conversational support
- Apply active learning for improved accuracy
- Provision Azure AI Language resources
- Define intents, utterances & entities
- Use patterns to distinguish similar inputs
- Integrate prebuilt entity recognition
- Train, test, publish, and review your CLU model
- Understand types of text classification projects
- Build a custom classification pipeline
- Tag training data and train the model
- Deploy the model and integrate into apps
- Learn custom NER methodologies
- Label entities in unstructured docs
- Train, evaluate, and deploy an NER model
- Use API to submit entity extraction tasks
- Provision a Translator resource
- Understand detection, translation, transliteration
- Specify translation options and quality settings
- Define and integrate custom translation glossaries
- Provision Azure AI Speech resources
- Implement speech-to-text
- Use text-to-speech for voice synthesis
- Configure audio formats, voice styles, SSML
- Provision speech translation resources
- Capture spoken language and translate in real-time
- Output translated speech via voice synthesis
- Build audio-enabled chat apps using generative AI
- Interpret tone, intent, and language from spoken input
- Integrate speech understanding with generative models
Free course advice
We care a lot about helping you find the course path that creates the most value for you and your workplace. Get in touch with our course advisors — they're ready to help you, free of charge and with no obligation.
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