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Azure AI-3003 Training Course – Developing Natural Language Processing (NLP) Solutions

Azure AI-3003 Training Course – Developing Natural Language Processing (NLP) Solutions
Guaranteed sessions from 1 enrollee  •  No postponement risk except force majeure  •  60% hands-on
Key information
Duration1 day(s) / 6 h
Price550 € excl. VAT
FormatDistance learning, On-site at your premises
LevelIntermediate
CertifyingNo
TailoredCustomizable programme

Upcoming sessions

25 Janv. 2027
22 Fév. 2027
22 Mars 2027
12 Avr. 2027
3 Mai 2027

Would you like to schedule this training on a specific date? Contact us by email or via the contact form.

Description of the training: Azure AI-3003 Training Course – Developing Natural Language Processing (NLP) Solutions
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Would you like to schedule this training course on a specific date ? Contact us by email or by filling out the contact form.

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Good to know
GOOD TO KNOW

This training course includes many exercises (60% practice) for better learning. Sessions are guaranteed from 1 registered participant (except in cases of force majeure). A preliminary interview takes place between the participant and/or a company representative to properly account for the participant’s profile (level, needs, professional context, challenges…).
Assessment: during the training, the trainer evaluates the pedagogical progress of participants through MCQs, role-play scenarios and practical exercises. Participants receive a certificate of skills validation at the end of the training.

This training course is part of our Artificial Intelligence Training Courses. Explore our other AI training courses to fully leverage machine learning, LLMs and generative AI.

Objectives of the training: Azure AI-3003 Training Course – Developing Natural Language Processing (NLP) Solutions
Objectives of the Azure AI-3003 Training Course

Upon completion of the training, the participant will be able to:

  • Understand the fundamentals of natural language processing (NLP) and its use cases in modern applications.
  • Design and deploy solutions based on Azure AI Language to analyse and exploit textual data.
  • Implement features such as sentiment analysis, entity detection and text classification.
  • Create conversational models capable of interacting with users through intelligent interfaces.
  • Integrate NLP services into cloud applications via REST API and SDK.
  • Apply best practices in responsible AI, security and data governance.
Prerequisites of the training: Azure AI-3003 Training Course – Developing Natural Language Processing (NLP) Solutions
Prerequisites
  • Programming experience (Python or C# recommended).
  • Understanding of fundamental cloud concepts and the Azure portal.
  • General knowledge of artificial intelligence or machine learning (a plus).
  • Because each participant is unique, a personalised interview with our expert allows us to design a training course perfectly aligned with their objectives, level and professional challenges.
Target audience of the training: Azure AI-3003 Training Course – Developing Natural Language Processing (NLP) Solutions
Target Audience
  • Developers, AI engineers and data engineers wishing to integrate NLP capabilities into their applications.
  • Cloud architects and technical consultants working on artificial intelligence solutions.
  • IT professionals involved in automating the processing of textual or conversational data.
Detailed programme of the training: Azure AI-3003 Training Course – Developing Natural Language Processing (NLP) Solutions

Download the programme (PDF)

Introduction to NLP with Azure AI
  • Overview of NLP capabilities in Azure AI Services.
  • NLP use cases in enterprise applications.
  • Key concepts: tokenisation, lemmatisation, semantic analysis.
  • Setting up the Azure environment for NLP.
Text Analysis with Azure AI Language
Custom Text Classification
  • Creating classification projects.
  • Training and evaluating custom models.
  • Deploying classification solutions.
  • Optimising model performance.
Advanced Information Extraction
  • Extracting custom entities.
  • Structuring unstructured data.
  • Advanced labelling and annotation techniques.
  • Integrating results into business workflows.
Developing Conversational Applications
  • Introduction to Azure conversational solutions.
  • Designing question-and-answer systems (QnA Maker / CLU).
  • Implementing multi-turn dialogue management.
  • Integrating chatbots into applications.
Integration via API and SDK
  • Using Azure AI REST APIs.
  • Development with SDK.
  • Managing authentication and quotas.
  • Monitoring and logging API calls.
Responsible AI and Governance
  • Transparency and bias in NLP models.
  • Data protection and compliance.
  • Implementing content moderation principles.
  • Audit and governance of AI solutions.
Practical Workshops
  • Implementing a complete NLP solution.
  • Automated analysis of textual documents.
  • Development of a conversational use case.
  • Review and Q&A session.
Course highlights
  • Focuses on natural language processing with Azure AI
  • Covers text analysis and language services
  • Builds on hands-on workshops
  • Prepares you for the Microsoft AI-3003 path
FAQ
What is Azure AI Language (AI-3003)?

Azure AI Language (formerly Text Analytics) is Microsoft Azure’s AI service dedicated to natural language processing (NLP): named entity recognition, sentiment analysis, language detection, automatic summarization, text classification, question answering, and custom models via Language Studio. The MFE-IT AI-3003 track trains you to integrate these capabilities into your applications in 1 day (6 hours).

What is the difference between Azure AI Language and Azure OpenAI?

Azure AI Language provides ready-to-use specialized models (NER, sentiment, summarization) with predictable cost and low latency, ideal for well-scoped NLP tasks in production. Azure OpenAI gives access to generic LLMs (GPT-4o, GPT-4.1, o3, GPT-5) for general understanding and generation tasks. The two are often combined: AI Language for structured processing, Azure OpenAI for open-ended tasks. MFE-IT trains on both.

Can custom NLP models be trained with Azure AI Language?

Yes. Language Studio offers several custom projects: Custom NER to extract business entities, Custom Text Classification (single- or multi-class), Custom Question Answering, and Conversational Language Understanding (CLU) which replaces LUIS. Training is done through web-based annotation with no code. The MFE-IT training covers the full methodology of a custom NER/classification project.

How long is the Azure AI-3003 training?

The MFE-IT training lasts 1 day (6 hours), in a 100% custom format with a maximum of 3 participants per session. It covers: prebuilt services (sentiment, entities, PII, language, summarization), Custom NER and Custom Classification via Language Studio, Conversational Language Understanding, Question Answering, orchestration, and container deployment. 30 days of post-training support.