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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.
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Training AWS Machine Learning Engineer Associate MLA-C01 - Earn Your Certification in 3 Days April 2026
Learning objectives
- Master essential AWS services for machine learning such as SageMaker, Glue, and Athena.
- Effectively prepare for the MLA-C01 certification exam with proven strategies.
- Implement complete ML data pipelines on the AWS console via practical labs.
- Validate your professional skills in modeling and deploying ML models on AWS.
- Optimize ML workflows for real business cases with native AWS tools.
- Pass the MLA-C01 exam by acquiring the market-demanded certifying skills.
- Deploy scalable and secure ML solutions in AWS production environments.
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.
Program
Module 1AWS Machine Learning Fundamentals: SageMaker, Data Preparation (Glue, Athena, Console Labs)
Discover the basics of machine learning on AWS with a focus on SageMaker for model building. Explore Glue and Athena for data engineering through practical labs on the AWS console. Apply these tools to real cases like cleaning and transforming massive datasets, fostering immediate and actionable understanding for your professional projects. (52 words)
Module 2AWS ML Modeling and Training: Hyperparameters, Tuning, Deployment (SageMaker, Advanced Labs)
Dive into advanced modeling with SageMaker: distributed training, hyperparameter tuning, and feature engineering. Perform hands-on exercises on the console to deploy optimized models, integrating enterprise use cases like real-time prediction. These practical sessions strengthen your skills for scalable and high-performance AWS implementations. (68 words)
Module 3Intensive MLA-C01 Exam Preparation: Practice MCQs, Strategic Review, Simulations (Passing Score Strategies)
Day dedicated to MLA-C01 exam success: exhaustive review of covered domains, timed practice MCQs, and analysis of common errors. Master exam strategies (time management, AWS pitfalls) via realistic simulations. Conclude with final labs for consolidation and personalized coaching, maximizing your certification chances in the next session. (72 words)
Evaluation method
- Continuous assessments via interactive quizzes and daily practical labs.
- MLA-C01-compliant practice MCQs to measure progress.
- Final simulated exam with personalized feedback and >90% success rate.
- AWS projects portfolio to integrate into your certifying CV.
Learning method
- Active pedagogy 70% hands-on: real labs on shared AWS console.
- Real case studies from Fortune 500 companies using SageMaker.
- Blended method: targeted theory + individual coaching in small groups.
- Unlimited access to e-learning platform post-training for reviews.
Methods, materials and delivery
The Training AWS Machine Learning Engineer Associate MLA-C01 - Earn Your Certification in 3 Days April 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 - Earn Your Certification in 3 Days April 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 - Earn Your Certification in 3 Days April 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
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
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.
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.
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.
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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