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Training AWS Machine Learning Engineer Associate MLA-C01 - Obtain Your Certification in 3 Days, May 2026

Ref: HEB672
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 days
remote

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Learning objectives

  • Master key AWS services for Machine Learning such as SageMaker, Glue, and Lambda to implement scalable solutions.
  • Effectively prepare for the MLA-C01 certification exam with proven strategies and realistic mock exams.
  • Configure and deploy ML data pipelines on AWS for professional end-to-end workflows.
  • Implement optimized machine learning models through practical labs on the AWS console.
  • Validate your professional AWS ML engineering skills recognized by the global industry.
  • Optimize performance and security of ML applications on AWS for production-ready deployments.
  • Pass the AWS Machine Learning Engineer Associate certification in just 3 intensive days.

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 Studio, Data Services, and Initial Labs (Glue, S3, Athena)

Discover the basics of Machine Learning on AWS through an educational immersion in SageMaker to create your first notebooks and explore datasets with Glue and Athena. Perform practical labs on the AWS console to ingest, transform, and visualize real data, applying essential preprocessing techniques. Our experts guide each step to solidify your fundamental skills in a single dynamic day, with concrete cases inspired by industrial projects.

Module 2AWS ML Modeling and Deployment: Model Training, Hyperparameters, and Pipelines (SageMaker Pipelines, Endpoints)

Dive into model training and tuning with SageMaker: configure distributed jobs, optimize hyperparameters via Automatic Model Tuning, and deploy scalable endpoints. Hands-on labs on the AWS console simulate real scenarios like churn prediction or image classification, integrating Lambda for inference. Learn to orchestrate end-to-end pipelines with SageMaker Pipelines, boosting your expertise for production-ready ML applications in enterprise.

Module 3Intensive MLA-C01 Exam Preparation: Mock Exams, Full Review, and Success Strategies

Decisive day dedicated to certification: review all MLA-C01 exam domains via timed mock exams identical to the real AWS test, with detailed answers and tips. Strengthen weaknesses through targeted exercises on the AWS console, analyze common pitfalls, and master exam strategies (time management, scoring). End with a full simulation and a personalized plan to validate your certification in the next session, with >90% success rate among our alumni.

Evaluation method

  • Continuous evaluation through practical labs and exercises on the AWS console each day.
  • Mock exams and MLA-C01 exam simulations on day 3 to measure readiness.
  • Interactive quizzes and personalized feedback from AWS certified trainers.
  • Qualiopi training certificate and recommendations for the official exam.

Learning method

  • 70/20/10 method: 70% practical AWS labs, 20% real cases, 10% theory.
  • Unlimited access to the AWS console during training and 30 days post-training.
  • Session replay videos and e-learning resources for independent review.
  • Group limited to 10 participants for optimal individualized follow-up.

Methods, materials and delivery

The Training AWS Machine Learning Engineer Associate MLA-C01 - Obtain 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 Engineer Associate MLA-C01 - Obtain 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 Engineer Associate MLA-C01 - Obtain 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
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« 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
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« 😊👍 »

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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