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Training: Become an Amazon SageMaker Expert: Deploy and Manage AI Models in Production

Ref: PVM273
8 people max.
From $3,465 HT / per person
Pay in 3 installments · On-site on request · +$540 with certification exam
3 days
Remote

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Learning objectives

  • Understand the architecture and main components of Amazon SageMaker
  • Know how to create, train, and deploy machine learning models on SageMaker
  • Set up automated and reproducible ML pipelines (MLOps)
  • Secure, monitor, and optimize models in production via SageMaker
  • Manage costs, permissions, and automate via the Python SDK and AWS CLI

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.

Célian Lebacle
Célian Lebacle

Learni trainer · Web & mobile expert

73%productivity gap
×3cost of inaction

Program

Module 1Introduction to Amazon SageMaker and ML Environment Design

Presentation of AWS and the SageMaker suite, fundamental AI concepts on AWS, creation of notebook instances, environment management, IAM roles and security, first dataset explorations on SageMaker. Practical exercises: interface discovery, data imports, and manipulation via SageMaker Studio.

Module 2Training, Deployment, and Model Management on SageMaker

Complete ML workflow: dataset preparation, selection of native and custom algorithms, distributed training, hyperparameter tuning, endpoint creation and deployment. Pipeline integration for versioning and repeatability. Hands-on practice: training on real cases (tabular data, images, or text), job monitoring, error handling.

Module 3Automation, Monitoring, Optimization, and MLOps with SageMaker

Workflow industrialization: automated pipelines, CI/CD with SageMaker Pipelines, data flow security, drift monitoring, multi-model endpoints, cost management, logs and metrics, integration with other AWS services (S3, Lambda, CloudWatch). Final workshop: full model deployment, performance monitoring, and maintenance automation.

Evaluation method

  • Final case study on deploying an ML model into production with monitoring
  • Daily quizzes and validation of practical skills through supervised exercises

Learning method

  • Guided practical workshops
  • Hands-on sessions with real datasets
  • Interactive courses and technical demos
  • Detailed materials and reusable scripts

Methods, materials and delivery

The Training: Become an Amazon SageMaker Expert: Deploy and Manage AI Models 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: Become an Amazon SageMaker Expert: Deploy and Manage AI Models 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: Become an Amazon SageMaker Expert: Deploy and Manage AI Models 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: Become an Amazon SageMaker Expert: Deploy and Manage AI Models in Production training cost?+
The individual price is $3,465 (USD). A detailed quote is sent within one business day.
How long is the Training: Become an Amazon SageMaker Expert: Deploy and Manage AI Models in Production training?+
The training lasts 3 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?+
Good knowledge of machine learning and Python. Basic AWS knowledge recommended.
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.

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