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Training Amazon SageMaker - Deploying Scalable ML Pipelines

Ref: EBW995
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 advanced Amazon SageMaker pipelines for professional, certifiable ML deployments
  • Develop skills in scalable hyperparameter tuning and feature engineering in enterprise settings
  • Design optimized serverless endpoints for critical production workloads
  • Implement automated MLOps workflows with SageMaker to accelerate iterations
  • Optimize ML model costs and performance through advanced monitoring and A/B testing
  • Integrate SageMaker into hybrid ecosystems for robust and secure AI solutions

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 Pipelines and Processing (Studio tools, distributed jobs, enterprise cases)

Discover SageMaker pipeline architectures for distributed processing of massive datasets, configure Processing Jobs with Spark and custom containers, perform practical exercises on real feature stores, integrate real-time S3 data, produce automated data quality reports, apply scalable transformations on concrete enterprise cases, validate deliverables via interactive SageMaker dashboards.

Module 2Amazon SageMaker: Expert Training, Tuning, and Deployment (autoML algorithms, multi-model endpoints)

Dive into automated hyperparameter tuning with Bayesian Optimization, train distributed models on GPU/TPU via SageMaker Training, deploy elastic endpoints with autoscaling, test live A/B experiments, optimize latency via Triton compilation, integrate custom ONNX models, generate production-ready artifacts, analyze metrics via CloudWatch in high-load scenarios.

Module 3Amazon SageMaker: MLOps and Production Monitoring (CI/CD workflows, Model Registry, alerting)

Implement end-to-end MLOps pipelines with SageMaker Projects and Pipelines, configure Model Registry for advanced governance, enable Clarify for bias detection and explainability, monitor model drift in real-time via Model Monitor, automate rollbacks and retrainings, integrate with Kubernetes EKS for hybridization, deploy secure solutions with VPC and fine-grained IAM, conclude with a deliverable and certifiable capstone project.

Evaluation method

  • Supervised final MLOps project with real endpoint deployment
  • Advanced technical quiz on SageMaker tuning and monitoring
  • Group analysis of enterprise case study with expert feedback

Learning method

  • Hands-on exercises for 70% of the time on a dedicated AWS environment
  • Real-world use cases from Fortune 500 companies with anonymized datasets
  • Individual mentoring by AWS/ML certified trainers with 15 years of experience
  • Scalable simulations in multi-regions for production workloads

Methods, materials and delivery

The Training Amazon SageMaker - 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.

Equipment required

For the smooth delivery of the Training Amazon SageMaker - Deploying Scalable ML Pipelines 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 Scalable ML Pipelines 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 Scalable ML Pipelines 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 - Deploying Scalable ML Pipelines 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?+
Advanced proficiency in Python, AWS (EC2, S3, Lambda), SageMaker Studio, ML frameworks (TensorFlow, PyTorch), basic CI/CD pipelines, and MLOps
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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