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Training Amazon SageMaker 2026 - Automate ML Pipelines Low-Code

Ref: YIX183
10 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

  • Master the low-code tools of Amazon SageMaker 2026 to develop professional ML pipelines in a business environment.
  • Design and optimize automated workflows with SageMaker Studio and Canvas for certifiable skills.
  • Deploy scalable predictive endpoints integrating Zapier and Power Apps for increased productivity.
  • Implement advanced experiments with AutoML and JumpStart in a no-code training context.
  • Analyze and monitor models in production via SageMaker Clarify and Model Monitor.
  • Integrate Bubble for no-code interfaces connected to SageMaker in real projects.
  • Certify your low-code ML skills to boost your corporate career.

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 2026: low-code architecture and advanced Studio (pipelines, Canvas, JumpStart)

Discover the low-code new features of Amazon SageMaker 2026 through practical exercises on SageMaker Studio, set up collaborative notebooks with Processing Jobs, test Canvas for code-free ML on real datasets, implement JumpStart to import pre-trained models, create your first automated pipelines with enterprise use cases, and generate deliverables like exportable notebooks ready for production, all in 7 hours of intensive practice.

Module 2Amazon SageMaker 2026: deployment and no-code integrations (endpoints, Zapier, Power Apps)

Dive into advanced deployment with SageMaker serverless Endpoints, optimize real-time inference on GPU, integrate Zapier to automate ML data flows to no-code apps, connect Power Apps for interactive dashboards powered by your models, simulate enterprise scenarios with A/B testing, generate performance reports, and deploy a complete project integrating these tools, ensuring rapid and certifiable skill development in 7 hours.

Module 3Amazon SageMaker 2026: monitoring, optimization, and Bubble (Clarify, Model Monitor, no-code apps)

Master monitoring with SageMaker Model Monitor to detect production drifts, use Clarify for explainability and bias detection on complex models, optimize costs via Spot Instances and autoscaling, integrate Bubble to create no-code user interfaces powered by SageMaker, test a full-stack low-code business application use case, produce a project portfolio with quantified metrics, and validate your skills via a final challenge in 7 hours of professional simulation.

Evaluation method

  • Daily interactive quizzes on SageMaker 2026 features to validate theoretical knowledge.
  • Final low-code project: deployment of a complete ML pipeline with Zapier and Power Apps integrations.
  • Qualiopi certifying attestation delivered after practical evaluation and advanced quizzes.

Learning method

  • 70% practical: hands-on workshops on AWS console with real datasets and no-code tools.
  • 30% theory: feedback from experience and ML best practices in business.
  • Synchronous remote method: live sessions with screen sharing and breakout rooms.
  • Resources: video replays, SageMaker templates, extended AWS lab access for 30 days.

Methods, materials and delivery

The Training Amazon SageMaker 2026 - Automate ML Pipelines Low-Code 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 2026 - Automate ML Pipelines Low-Code 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 2026 - Automate ML Pipelines Low-Code 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 2026 - Automate ML Pipelines Low-Code training cost?+
The individual price is $3,465 (USD). A detailed quote is sent within one business day.
How long is the Training Amazon SageMaker 2026 - Automate ML Pipelines Low-Code 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?+
Mastery of Python for data science, advanced machine learning concepts, experience with AWS (EC2, S3), and basics in model deployment.
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.
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