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 mastering Amazon SageMaker, data teams waste 50% of their time on manual ML infrastructure, with hidden costs exploding to 40% of the data budget.
70% of ML projects fail in production due to lack of scalable pipelines, resulting in 25% missed revenue from faulty predictions.
In 2026, 85% of ML job postings require SageMaker, excluding non-certified candidates and blocking promotions.
Every quarter without MLOps skills widens the competitive gap, exposing the company to critical data incidents and massive customer losses.
Dive into SageMaker Studio to configure secure and collaborative domains, install the boto3 SDK to interact with S3 and ECR, create custom notebooks with GPU/CPU kernels, import and prepare real enterprise datasets via Processing Jobs, perform practical exercises on an image classification case, produce interactive visualizations with SageMaker Experiments, and generate a deliverable preprocessing report for your ongoing project.
Design end-to-end pipelines with SageMaker Pipelines to automate preprocessing, training, and evaluation, deploy distributed jobs on multi-node clusters with XGBoost and Deep Learning algorithms, test automatic hyperparameter tuning on large datasets, integrate custom metrics via Clarify for bias detection, apply to a business predictive scenario such as churn prediction, iterate quickly with code review, and export an optimized model ready for production.
Deploy models to serverless or asynchronous endpoints with auto-scaling, configure CloudWatch and Model Monitor for real-time drift detection, implement A/B tests and canary deployments on real traffic, integrate with Lambda and API Gateway for enterprise apps, optimize costs with spot instances and compilation, finalize with a complete production deployment exercise for your ongoing project, produce an operational dashboard, and develop a sustainable MLOps plan.
The Training Amazon SageMaker - Deploying Scalable ML 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.
For the smooth delivery of the Training Amazon SageMaker - Deploying Scalable ML in Production 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 Amazon SageMaker - Deploying Scalable ML in Production 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.