Azure AI-3003 Training Course - Developing Natural Language Processing (NLP) Solutions
- Price
- Duration
- Number of hours
Our sessions are guaranteed from 1 registered participant (except in cases of force majeure).
Description of the Azure AI-3003 Training Course
This Azure AI training course – Developing Natural Language Processing (NLP) Solutions enables you to design applications capable of understanding and exploiting human language. You will learn to analyse texts, detect entities, classify content and automate the processing of textual data using Azure AI services. The programme also covers the development of conversational experiences and integration via API and SDK. Practical workshops will allow you to build a complete NLP solution tailored to business needs. Upon completion, you will be able to deploy intelligent applications based on natural language analysis.
Format
Remote (recorded sessions).
It is possible to customise the training content to meet the needs of your professional project.
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.
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 for the Azure AI-3003 Training Course
- 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
- 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 Azure AI-3003 Training Course
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
Identify business use cases suited to pre-built models. Analyse documents using the Read, Layout or General Document models. Process specialised documents (financial, tax, identity documents).
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.
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