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Training Azure Machine Learning 2026 - Deploying Scalable AIs in Production

Ref: WTU897
10 people max.
From $5,775 HT / per person
On-site on request · +$540 with certification exam
5 days
Remote

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

  • Master Azure Machine Learning 2026 for professional certifying AI pipelines.
  • Develop optimized deep learning models in an expert environment.
  • Design automated workflows for the enterprise with advanced MLOps.
  • Deploy scalable and secure AI solutions in production.
  • Optimize ML performance with the latest Azure 2026 features.
  • Implement prompt engineering for intelligent AI agents.
  • Acquire certifying skills in professional AI training.
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, 70% of ML projects fail in production according to Gartner, causing 6-month delays and 40% inflated costs.

  • Companies lose 25% competitiveness against AI-native competitors, with data scientists underutilized on manual tasks.

  • Career risk: salary stagnation and displacement by automated AI.

  • Invest now to secure your expertise and boost your professional value.

Allan BUSI
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction

Program

Module 1Azure Machine Learning 2026 Architecture: Expert Modeling and Advanced Workspaces (CLI, SDK, UI)

Discover the new features of Azure Machine Learning 2026 through practical labs on CLI v2 and Python SDK, configure secure hybrid workspaces, implement custom conda environments for TensorFlow 3.0, analyze massive datasets with advanced AutoML, and produce a deliverable architecture report for your company, while integrating real-world cost optimization cases.

Module 2Azure Machine Learning 2026 Pipelines: Expert MLOps and Automation (YAML, Reusable Components)

Build end-to-end pipelines with Designer and YAML, integrate custom components for deep learning, automate distributed training on GPU A100, test reproducibility via DVC, monitor with Azure Monitor, deploy a complete pipeline on a real Kaggle dataset, and generate performance metrics for professional validation.

Module 3Azure Machine Learning 2026 Deployment: Scaling and Serving (ONNX, AKS, Managed Endpoints)

Master expert deployment with ACI and AKS, convert models to ONNX for fast inference, configure managed endpoints with A/B traffic splitting, implement RBAC and VNET security, scale via Kubernetes autoscaling, test latency under real loads, and deliver a production-ready deployed model for enterprise.

Module 4Optimization and Monitoring in Azure Machine Learning 2026: Performance Tuning and Explainability (SHAP, Drift Detection)

Optimize models with distributed hyperparameter tuning and quantization, integrate SHAP for regulatory explainability, detect data drift in real-time via Azure ML, monitor with Application Insights and custom metrics, apply automated remediations, analyze a real failure case, and produce a Grafana dashboard for enterprise monitoring.

Module 5Advanced Azure Machine Learning 2026: AI Agents, Prompt Engineering, and Integrations (LangChain, RAG)

Develop AI agents with expert prompt engineering via Semantic Kernel, implement RAG on Azure Search and OpenAI, integrate multimodal deep learning, secure with Azure Key Vault, test in multi-agent scenarios, deploy a complete RAG solution for enterprise Q&A, and finalize with a deliverable certifying project.

Evaluation method

  • Daily technical quizzes on Azure ML 2026
  • Final project: MLOps pipeline deployed in simulated production
  • Qualiopi certificate with validated expert skills

Learning method

  • 70% hands-on on real Azure labs
  • Fortune 500 company case studies
  • Individual mentoring by Microsoft certified experts
  • Post-training resources: GitHub templates and videos

Methods, materials and delivery

The Training Azure Machine Learning 2026 - Deploying Scalable AIs in Production 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 Production 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 Production 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 Production training cost?+
The price is $5,775 (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 Production training?+
The training lasts 5 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?+
Advanced mastery of Azure, expert Python, ML frameworks like TensorFlow and PyTorch, CI/CD pipelines, and cloud 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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