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Training Azure OpenAI Service 2026 - Deploying Generative AI in the Enterprise

Ref: NQU846
10 people max.
5500€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 days
remote

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Learning objectives

  • Master the configuration of Azure OpenAI Service 2026 for rapid professional deployments
  • Develop generative AI applications with advanced GPT models and custom assistants
  • Implement optimized prompt engineering to boost enterprise performance
  • Design secure and scalable pipelines tailored to certifying organizational needs
  • Optimize costs and governance of AI resources in a hybrid cloud context
  • Evaluate and deploy Azure OpenAI solutions to enhance competitiveness in professional training

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Fundamentals of Azure OpenAI Service 2026: Initial Configuration and Model Access (Azure Portal, CLI)

Discover the basics of Azure OpenAI Service 2026 through practical exercises on the Azure portal and CLI, configure your first deployments of GPT-4o models and assistants, explore real quotas and pricing, perform simple API call tests in Python with secure authentication, produce your first basic prompts and analyze generated responses, obtain a deliverable: functional test environment ready for the enterprise.

Module 2Prompt Engineering for Azure OpenAI Service 2026: Advanced Techniques and Optimization (chain-of-thought, few-shot)

Dive into prompt engineering with Azure OpenAI Service 2026, practice chain-of-thought and few-shot methods on concrete business cases, integrate tools like Semantic Kernel to structure interactions, test real-time iterations on professional datasets, measure impact via quality metrics, generate automated reports, end with a deliverable: library of optimized reusable prompts for production.

Module 3Application Integration with Azure OpenAI Service 2026: Full-Stack App Development (LangChain, Streamlit)

Build complete applications with Azure OpenAI Service 2026 using LangChain and Streamlit, integrate vector embeddings for semantic search, deploy intelligent chatbots connected to Azure Cosmos DB databases, simulate RAG flows for contextual responses, debug live with advanced logs, validate via unit tests, produce a deliverable: scalable deployed AI app prototype for the enterprise.

Module 4Security and Governance for Azure OpenAI Service 2026: GDPR Compliance and Content Filtering (Azure AI Content Safety)

Strengthen security of Azure OpenAI Service 2026 with Azure AI Content Safety and filtering policies, configure fine-grained access controls via Azure RBAC, implement monitoring with Azure Monitor and Sentinel to detect anomalies, audit logs for GDPR compliance in enterprise, test prompt injection attack scenarios, generate automated governance reports, obtain a deliverable: certifying secure framework for professional deployments.

Module 5Advanced Deployment of Azure OpenAI Service 2026: Scaling and Cost Optimization (Azure Kubernetes, fine-tuning)

Master scaling of Azure OpenAI Service 2026 on Azure Kubernetes Service with auto-scaling, optimize costs via reservations and fine-tuning of custom models, integrate CI/CD workflows with Azure DevOps, deploy to production with high availability, analyze performance via Power BI dashboards, simulate real enterprise loads, finalize with a deliverable: optimized, deployed, and documented AI solution for immediate adoption in certifying training.

Evaluation method

  • Daily interactive quizzes on key concepts of Azure OpenAI Service 2026
  • Final practical project: development of a complete AI app deployed in the cloud
  • Trainer evaluation on technical skills and certifying business cases

Learning method

  • 70% hands-on practice with exercises on Azure OpenAI Service 2026
  • Real-world use cases from Qualiopi-certified French companies
  • Individual remote mentoring for solving real problems
  • Post-training resources: videos, source code, and dedicated community

Methods, materials and delivery

The Training Azure OpenAI Service 2026 - Deploying Generative AI in the Enterprise program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training Azure OpenAI Service 2026 - Deploying Generative AI in the Enterprise program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training Azure OpenAI Service 2026 - Deploying Generative AI in the Enterprise program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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