Implement Natural Language
Processing Solutions
NLP covers the full range of language understanding and generation services in Azure. You'll learn Azure AI Language (sentiment, NER, key phrases, CLU, custom Q&A), Azure AI Translator (text and document translation), Azure AI Speech (speech-to-text, text-to-speech, speaker recognition), and custom language models for your own domains.
NLP is one of the largest exam domains. It spans three Azure service families: Azure AI Language (text analytics, CLU, custom Q&A), Azure AI Translator (translation), and Azure AI Speech (audio). Each has prebuilt and custom model options — the exam tests both the API usage and the decision of when to use which service.
Topics in this Part
Study in order — Topic 1 introduces the text analysis foundation; Topics 2 and 3 build on it.
Azure AI Language service — sentiment analysis, key phrase extraction, named entity recognition (NER), language detection, linked entities, and PII detection. Azure AI Translator — text translation, language detection, transliteration, and document translation. All with Python code, every line explained.
Azure AI Speech — speech-to-text (STT) for real-time and batch transcription, text-to-speech (TTS) with neural voices, speech translation (translate spoken words in real time), speaker recognition (verify identity by voice), and custom speech models for domain vocabulary. When to use Speech vs Whisper.
Custom NER, custom text classification, Conversational Language Understanding (CLU — LUIS replacement), custom question answering, and how to build conversational AI bots with Azure Bot Service and Bot Framework. Training, evaluation, and deployment of custom models. Decision guide: prebuilt vs custom.