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Training AWS Machine Learning Specialty MLS-C01 - Get Your Certification in 3 Days May 2026

Ref: PVY441
10 people max.
3300 € HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
3 journées
distanciel

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Learning objectives

  • Master essential AWS services for machine learning such as SageMaker, Rekognition, and Comprehend to acquire professional certifying skills.
  • Effectively prepare for the MLS-C01 exam by covering all areas evaluated by AWS.
  • Configure scalable ML data and training pipelines on the AWS platform.
  • Implement and deploy production machine learning solutions with high availability.
  • Optimize performance, security, and costs of ML workloads on AWS.
  • Validate your skills to pass the AWS Machine Learning Specialty MLS-C01 certification.
  • Develop advanced strategies for data exploration and predictive modeling.

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

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.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1AWS Machine Learning Fundamentals: SageMaker, data engineering, and exploration (Glue, Athena, practical labs)

Discover the basics of AWS machine learning with SageMaker to create interactive Jupyter notebooks. Dive into data engineering with Glue for ETL and Athena for serverless queries on S3. Perform practical labs on AWS console: ingestion of real data, cleaning, and feature engineering exploration. Apply supervised/unsupervised algorithms on concrete datasets, optimizing preprocessing for performant models. This day lays solid foundations for your professional ML projects (58 words).

Module 2Advanced Modeling and ML Deployment: Hyperparameter tuning, inference, and scaling (SageMaker endpoints, ECS, advanced labs)

Advance to implementing advanced models with SageMaker: automatic hyperparameter tuning, distributed training on GPU/TPU. Deploy serverless endpoints for real-time or batch inference. Integrate Rekognition for vision and Comprehend for NLP on real enterprise cases. Hands-on labs: horizontal scaling with ECS/Fargate, monitoring via CloudWatch and X-Ray. Manage security with IAM roles and KMS encryption, while optimizing costs via Spot Instances. Prepare production-ready solutions (72 words).

Module 3Intensive Preparation for MLS-C01 Exam: Practice QCMs, full review, and success strategies (simulations, final labs)

Dedicate this day to targeted preparation for the AWS MLS-C01 exam: exhaustive review of the 5 domains (data engineering, modeling, exploratory, ML implementation, ML ops). Complete 4 timed practice QCM sessions identical to the real exam, with detailed corrections and tips. Analyze common pitfalls, time management strategies, and scoring. Finalize with synthesis labs on complex scenarios (ML pipeline troubleshooting). Receive your personalized post-training plan to pass the certification in just a few weeks (81 words).

Evaluation method

  • Continuous assessments through practical labs on AWS console with real-time feedback.
  • Complete MLS-C01 exam simulations (scored and analyzed practice QCMs).
  • Final project: design and deployment of a complete ML pipeline evaluated by experts.
  • Daily interactive quizzes to validate mastery of key concepts.

Learning method

  • Active pedagogy: 70% practical, 30% theory with AWS Specialty certified trainers.
  • Unlimited access to a dedicated AWS console during and after the training (30 days).
  • Replay videos of sessions and digital materials (slides, MLS-C01 cheat sheets).
  • Accelerated 3-day method for quick and effective certification.

Methods, materials and delivery

The Training AWS Machine Learning Specialty MLS-C01 - Get Your Certification in 3 Days May 2026 program is delivered onsite or remote (blended-learning, e-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 AWS Machine Learning Specialty MLS-C01 - Get Your Certification in 3 Days May 2026 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 AWS Machine Learning Specialty MLS-C01 - Get Your Certification in 3 Days May 2026 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

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
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« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
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.

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