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Training Azure Machine Learning 2026 - Deploying Scalable AIs in the Enterprise

Ref: SPU780
10 people max.
From $4,620 HT / per person
On-site on request · +$540 with certification exam
4 days
Remote

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ArcelorMittal
Equans
EDF
Ubisoft
Microsoft
Aptar
ArcelorMittal
Equans
EDF
Ubisoft
Microsoft
Aptar
ArcelorMittal
Equans
EDF
Ubisoft
Microsoft
Aptar
ArcelorMittal
Equans
EDF
Ubisoft
Microsoft
Aptar
ArcelorMittal
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Learning objectives

  • Master the new automated pipelines in Azure Machine Learning 2026 to accelerate AI developments in the enterprise.
  • Develop certifiable skills in hyperparameter optimization and distributed scaling on Azure.
  • Design advanced MLOps solutions integrating Azure ML Studio and Kubernetes for professional production.
  • Implement multimodal models with 2026 features, boosting AI team efficiency.
  • Optimize costs and performance of large-scale AI workloads in a Qualiopi-certified context.
  • Deploy autonomous AI agents via Azure ML, enhancing professional competitiveness.
A child walking to school with a backpack
Our social commitment

A school kit donated to a child for every training

To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.

  • Backpack, notebooks and essential supplies
  • Distributed through our partner charities
  • Included, at no extra cost to you

The Learni story

Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.

Don't let this gap widen

Why this program matters

  • Without mastery of Azure Machine Learning 2026, 75% of data teams struggle to scale their AI models, resulting in project timelines multiplied by 3 according to Gartner 2025.

  • Companies lose up to 20% market share to competitors adopting advanced MLOps, with cloud costs exploding without hyperparameter optimization.

  • Career risk: rapid obsolescence of expert skills, blocking promotions to senior AI architect roles.

  • Invest now to secure AI leadership and exponential ROI.

Allan BUSI
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction

Program

Module 1Azure Machine Learning 2026 Architectures: Advanced Pipelines and Hybrid Workspaces (Azure ML Studio, CLI v2)

Discover the 2026 evolutions of Azure Machine Learning with configuration of hybrid multi-cloud workspaces, creation of automated pipelines via designer and Python SDK, hands-on exercises on massive datasets to train distributed models, real-time log analysis for advanced debugging, deliverables include a production-ready functional pipeline, enhancing your professional skills in scalable AI.

Module 2Hyperparameter Optimization in Azure Machine Learning 2026: Distributed Tuning and AutoML Pro (Ray Tune, Optuna Integrated)

Dive into 2026 optimization algorithms with distributed Bayesian tuning on Azure GPU clusters, comparison of AutoML Pro vs. manual sweeps via Jupyter notebooks, real-world cases on vision and NLP with custom metrics, hands-on exercises to reduce training time by 70%, automated report generation, obtain optimal hyperparameters applicable in certifiable enterprise settings.

Module 3Advanced MLOps in Azure Machine Learning 2026: Serverless Deployment and Monitoring (ACI, AKS, Responsible AI Dashboard)

Master 2026 deployments with serverless endpoints on Azure Container Instances, Kubernetes integration for auto-scaling, monitoring setup via Azure ML Metrics and drift detection, hands-on workshops on automated rollbacks and A/B model testing, enterprise use cases with data governance, deliverables include a complete deployed MLOps pipeline, boosting your expertise in reliable AI.

Module 4AI Agents and Innovative Features in Azure Machine Learning 2026: Multimodal and Edge Inference (Phi-3, Custom Agents)

Explore 2026 autonomous agents with Phi-3 fine-tuning and tool chaining via LangChain on Azure, edge deployment on IoT Edge, exercises on vision-language multimodal models, cost optimization with spot instances, real industrial case simulations, finalize with a deliverable capstone project, certifying your advanced skills to transform your AI practice in the enterprise.

Evaluation method

  • Daily interactive technical quizzes on Azure ML 2026 with immediate feedback.
  • Final MLOps project deployed live, graded by Qualiopi experts.
  • Recognized certifying attestation validating expert skills in professional AI.

Learning method

  • 80% hands-on method: real-time coding workshops on dedicated Azure playgrounds.
  • Fortune 500 enterprise case studies migrated to Azure ML 2026.
  • Unlimited post-training resources access: labs, templates, alumni community.
  • 1-to-1 mentorship support during and after the certifying training.

Methods, materials and delivery

The Training Azure Machine Learning 2026 - Deploying Scalable AIs in the Enterprise program is delivered onsite or remote (blended-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 Machine Learning 2026 - Deploying Scalable AIs 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 Machine Learning 2026 - Deploying Scalable AIs 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

Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.

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.

FAQ

Frequently asked questions

How much does the Training Azure Machine Learning 2026 - Deploying Scalable AIs in the Enterprise training cost?+
The price is $4,620 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training Azure Machine Learning 2026 - Deploying Scalable AIs in the Enterprise training?+
The training lasts 4 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Expertise in Python and ML frameworks (TensorFlow, PyTorch), mastery of Azure (compute and storage services), experience in ML pipelines and production deployment.
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
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