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.
Describe your need, get a tailored program and a pre-filled quote in 3 min. A 100% free call with an advisor.
1 seat held for the next session
Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.

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.
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
Without Azure Machine Learning mastery, data teams waste 50% of their time on non-scalable manual trainings, with cloud costs inflated up to 30k€ annually per poorly optimized project.
Unmonitored models generate 25% errors in production, causing 15% losses in predictive revenue.
In 2024, 68% of companies fail their AI initiatives due to lack of cloud ML expertise, risking obsolescence against competitors 3x faster.
Each quarter without Azure skills widens an unrecoverable competitive gap.
Dive into Azure Machine Learning by creating your first secure workspace via the Azure portal and ML Studio interface, install the Python SDK to automate setups, explore compute instances and GPU clusters for fast training, complete practical exercises on resource management, and produce a ready-to-use environment for professional projects with full documentation.
Import and clean large datasets from Blob Storage or Data Lake via Azure ML pipelines, use built-in tools for EDA exploration with Pandas and MLflow tracking, apply automated transformations on real enterprise data, test dataset versioning for traceability, and generate interactive visual reports along with an optimized datastore for ML training.
Launch distributed training jobs on Azure ML with scikit-learn, TensorFlow, and PyTorch, enable AutoML to identify the best models in hours instead of days, configure hyperparameter tuning via Bayesian sweeps on GPU clusters, evaluate performance with ROC-AUC metrics and cross-validation, and produce a leading model with MLflow logs for immediate production integration.
Design CI/CD pipelines with Azure ML Designer and Python SDK for ingestion-enrichment-training-deployment, integrate Git for versioning code and models, test serverless orchestrations with Azure Functions, simulate fault-tolerant scenarios on large data volumes, and deliver a reproducible pipeline with automatic scheduling for continuous enterprise deployments.
Deploy models to real-time ACI/AKS endpoints with secure scoring via Azure AD tokens, configure auto-scaling for traffic spikes, implement monitoring with Application Insights and drift detection, test inference on concrete business cases like churn prediction, generate dashboards and alerts for proactive supervision, and finalize with a deployed and certified red thread project.
The Training Azure Machine Learning - Deploying Scalable ML Pipelines 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.
For the smooth delivery of the Training Azure Machine Learning - Deploying Scalable ML Pipelines program, the following equipment is required:
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.
Assessment of skills acquired during the Training Azure Machine Learning - Deploying Scalable ML Pipelines program is performed through:
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.
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.
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.
Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.
30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.
No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.
Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.
A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.
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Automation & workflowsIndustry-certifiedAvailable on-site and remotely. Pick your city to see the local training center.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.