Built for US teams
Payment by wire transferEnhanced confidentialityPerfect for companies with 50 to 500 employeesScheduling to fit any time zone

1 seat held for the next session

30:00Held for another

Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.

← Back

Training Amazon SageMaker - Deploying ML at Enterprise Scale

Ref: NPX374
10 people max.
From $4,620 HT / per person
On-site on request · +$540 with certification exam
4 days
Remote

Share in 2 clicks

Trusted by — schools, companies and industrial groups
Aptar
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
Equans
EDF
Ubisoft
Microsoft
Aptar
ArcelorMittal
Every program built with a dedicated engineer
OpenAI
Anthropic
Mistral AI
NVIDIA
Google
Amazon Web Services
Microsoft Dynamics 365
Salesforce
ServiceNow
SAP
Oracle
Cisco
Fortinet
Palo Alto Networks
Aruba
VMware
Red Hat
Databricks
Snowflake
OVHcloud
Notion
AMD
Apple
OpenAI
Anthropic
Mistral AI
NVIDIA
Google
Amazon Web Services
Microsoft Dynamics 365
Salesforce
ServiceNow

Learning objectives

  • Master advanced Amazon SageMaker pipelines for rapid enterprise ML deployments
  • Develop professional skills in SageMaker Studio model optimization
  • Design scalable SageMaker architectures for certifying data projects
  • Implement low-code automation with SageMaker Canvas and Processing
  • Optimize SageMaker costs and performance for maximum enterprise profitability
  • Deploy secure SageMaker endpoints in real production
  • Integrate SageMaker with no-code workflows to accelerate innovation
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 this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Allan BUSI
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction

Program

Module 1Amazon SageMaker: Advanced Architectures and Studio (AWS tools, collaborative notebooks)

Discover expert configurations of Amazon SageMaker Studio for collaborative ML environments, configure optimized GPU instances, explore advanced Jupyter notebooks with hands-on exercises on real datasets, integrate TensorFlow and PyTorch libraries, produce your first scalable prototypes, and validate architectures through concrete enterprise cases for immediate skills enhancement.

Module 2Amazon SageMaker: Pipelines and Processing (low-code automation, distributed jobs)

Build end-to-end pipelines with SageMaker Pipelines, automate preprocessing via Processing Jobs on EMR clusters, test hyperparameters in hands-on exercises, integrate feature stores for data reuse, analyze CloudWatch logs for rapid debugging, deploy your first automated workflows, and apply to real business scenarios for enterprise certifying skills.

Module 3Amazon SageMaker: Model Optimization and Canvas (tuning, no-code ML)

Optimize models with SageMaker Autopilot and Hyperparameter Tuning, explore no-code Canvas interfaces for drag-and-drop ML, perform exercises on bias reduction and XAI explainability, benchmark GPU/TPU performance, integrate SageMaker Debugger for real-time monitoring, generate automated reports, and simulate edge deployments for advanced professional expertise.

Module 4Amazon SageMaker: Production Deployment and Monitoring (endpoints, MLOps)

Deploy secure SageMaker endpoints with A/B traffic splitting, configure serverless Lambda inference, implement Model Monitor for drift detection, integrate with CI/CD GitHub Actions in hands-on exercises, analyze costs via Cost Explorer, produce a final enterprise-ready project, and prepare for AWS certification to boost your low-code ML career.

Evaluation method

  • Daily technical quizzes on SageMaker pipelines
  • Capstone project: end-to-end model deployment
  • Peer code review evaluation and certifying attestation

Learning method

  • 70% hands-on exercises on real AWS environments
  • Fortune 500 enterprise case studies
  • Unlimited 3-month post-training support
  • 6-month post-course access to SageMaker labs

Methods, materials and delivery

The Training Amazon SageMaker - Deploying ML at Enterprise Scale 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 Amazon SageMaker - Deploying ML at Enterprise Scale 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 Amazon SageMaker - Deploying ML at Enterprise Scale 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 Amazon SageMaker - Deploying ML at Enterprise Scale training cost?+
The individual price is $4,620 (USD). The team / on-site group package is shown on the course page. A detailed quote is sent within one business day.
How long is the Training Amazon SageMaker - Deploying ML at Enterprise Scale 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?+
Machine learning experience with Python, basic AWS knowledge, mastery of supervised/unsupervised algorithms
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.
On-site & remote

This training across cities

Available on-site and remotely. Pick your city to see the local training center.

Your professional training, anywhere

Let's build
your next
program.

30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.

Reply within 24h · Vetted experts · USD invoicing · W-9 available