Training Azure Machine Learning - Deploying Expert AI Models

Very demanding course · Expertise required

$7,875

  • 5 days
  • Onsite
  • 10 people max.
Ref: MDF336
10 people max.
$7,875
In-company rate: from $14,175 for the whole teamExpertise rate: $1,575 per day, reflecting the difficulty level
On-site and certification exam on quote
5 days
Onsite

Don't let this gap widen

Why this program matters

  • Companies that ignore Azure Machine Learning lose competitiveness against rivals adopting AI at scale.

  • Studies show that 67% of ML projects fail without robust MLOps tools, leading to costly delays and wasted budgets.

  • Professionals without these skills see their careers stall as demand surges.

  • Acting now avoids these risks and secures your position in the AI market.

Allan BUSI, Learni trainer · AI expert
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction
Flag of the United StatesBuilt for US teams
Payment by wire transferEnhanced confidentialityPerfect for companies with 50 to 500 employeesScheduling to fit any time zone

Trusted by — schools, companies and industrial groups

41,059 programs · 25 countries

  • Aptar
  • ArcelorMittal
  • Equans
  • EDF
  • Ubisoft
  • Microsoft

Every program built with a dedicated engineer

  • OpenAI
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  • Mistral AI
  • NVIDIA
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  • Microsoft Dynamics 365
  • Salesforce
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  • SAP
  • Oracle
  • Cisco
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  • Palo Alto Networks
  • Aruba
  • VMware
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  • Databricks
  • Snowflake
  • OVHcloud
  • Notion
  • AMD
  • Apple

Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft and Microsoft.

Azure Machine Learning training objectives

  • Master advanced professional training pipelines in Azure Machine Learning for enterprise use.
  • Develop certified skills in optimizing large-scale Deep Learning models.
  • Design integrated Prompt Engineering solutions within Azure workflows for enterprise needs.
  • Implement secure and scalable deployment strategies tailored to professional requirements.
  • Optimize costs and performance of AI models in a certified enterprise context.
  • Configure complete MLOps environments for professional AI projects.

Program

Azure Machine Learning curriculum: 5 modules over 5 days

Module 1 : Theme: Advanced Azure Machine Learning for data preparation (Azure Data Factory, notebooks, pipelines)

Participants explore expert Azure Machine Learning features to ingest and transform large datasets using Azure Data Factory and interactive notebooks. They perform practical exercises on automated cleaning, feature engineering and data versioning. Real enterprise cases illustrate the creation of reusable pipelines, resulting in an optimized dataset deliverable for training.

Module 2 : Theme: Azure Machine Learning for Deep Learning and distributed training (AML compute, TensorFlow)

This day covers training complex Deep Learning models with Azure Machine Learning, leveraging AML Compute clusters for distributed computing. Learners implement TensorFlow and PyTorch scripts, optimize hyperparameters via HyperDrive and analyze metrics. A practical exercise on a real dataset produces a trained model with complete logs and performance metrics.

Module 3 : Theme: Azure Machine Learning and Prompt Engineering for generative models (Azure OpenAI, fine-tuning)

Experts learn to integrate Prompt Engineering into Azure Machine Learning to refine generative models via Azure OpenAI. They design advanced prompts, perform fine-tuning and evaluate results on business use cases. Practical workshops deliver a customized model with documentation of prompt techniques used.

Module 4 : Theme: Azure Machine Learning for MLOps deployment and monitoring (Azure ML endpoints, Application Insights)

This session details model deployment via Azure ML endpoints, including CI/CD pipelines and real-time monitoring with Application Insights. Participants manage versions, automate tests and analyze data drift. A concrete project delivers a deployed endpoint with an operational monitoring dashboard.

Module 5 : Theme: Azure Machine Learning for AI optimization and governance (Azure Policy, Responsible AI)

The final day focuses on cost optimization, governance and ethics with Azure Machine Learning, applying Azure Policy and Responsible AI tools. Learners audit existing models, implement compliance controls and optimize resources. They finalize a complete deliverable including an audit report and strategic recommendations for the enterprise.

How Azure Machine Learning skills are assessed

  • Final MCQ on advanced Azure Machine Learning concepts
  • Evaluated practical project with full model deployment
  • Oral presentation of deliverables before the trainer

How the Azure Machine Learning course is taught

  • Access to a dedicated Azure environment during the training
  • Digital versions of materials and notebooks provided
  • Practical exercises based on real enterprise cases
  • Personalized feedback on developed projects

Azure Machine Learning training: access and practical arrangements

The Training Azure Machine Learning - Deploying Expert AI Models 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 - Deploying Expert AI Models 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 - Deploying Expert AI Models 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.

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.

Our method

How Learni guarantees the quality of your Azure Machine Learning training

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.

A child walking to school with a backpack
Our social commitment

A school kit donated to a child for every training booked

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
Enroll and offer a kit
FAQ

Azure Machine Learning: frequently asked questions

Which tools are used in Azure Machine Learning training?+
Hands-on work runs on azure Data Factory, notebooks, pipelines, AML compute, tensorFlow and azure OpenAI. Those tools come from the Azure Machine Learning program itself, delivered on site over 5 days, so participants practise on the stack they will use at work.
What can participants do after Azure Machine Learning training?+
They can master advanced professional training pipelines in Azure Machine Learning for enterprise use, develop certified skills in optimizing large-scale Deep Learning models and design integrated Prompt Engineering solutions within Azure workflows for enterprise needs. Those are the stated objectives of the Azure Machine Learning program at Expert level, checked by the end-of-session assessment.
What does the Azure Machine Learning program cover, day by day?+
Day 1: Theme: Advanced Azure Machine Learning for data preparation (Azure Data Factory, notebooks, pipelines). Day 2: Theme: Azure Machine Learning for Deep Learning and distributed training (AML compute, TensorFlow). Day 3: Theme: Azure Machine Learning and Prompt Engineering for generative models (Azure OpenAI, fine-tuning). Day 4: Theme: Azure Machine Learning for MLOps deployment and monitoring (Azure ML endpoints, Application Insights). Day 5: Theme: Azure Machine Learning for AI optimization and governance (Azure Policy, Responsible AI). The Azure Machine Learning program runs over 5 days, delivered on site.
How is Azure Machine Learning training assessed?+
Assessment relies on final MCQ on advanced Azure Machine Learning concepts, evaluated practical project with full model deployment and oral presentation of deliverables before the trainer. Learni issues a completion certificate together with the individual assessment report at the end of the Azure Machine Learning program, which an L&D team can file as evidence.
How much does Azure Machine Learning training cost per participant?+
Azure Machine Learning training costs $7,875 per participant. For an in-company team, the flat rate starts at $14,175 for the whole group, up to 8 people. The detailed quote, sent within one business day, adjusts the amount to the format and how far the syllabus is tailored to your team.
How long does Azure Machine Learning training take?+
5 days, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.
Who pays for Azure Machine Learning training?+
Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
What do participants need to know before Azure Machine Learning training?+
Mastery of Python, experience in machine learning with scikit-learn or TensorFlow, Azure knowledge and model deployment.
Is a certificate issued after Azure Machine Learning training?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.
Does Learni provide the equipment for Azure Machine Learning training?+
No. A computer and a stable internet connection are required for each participant. Learni provides the learning platform, the trainer and all course materials.
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