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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 - Get Your Certification in 3 Days April 2026
Learning objectives
- Master the fundamental concepts of machine learning on AWS to develop certified professional skills.
- Effectively prepare for the AWS MLA-C01 certification exam with proven strategies.
- Configure and implement ML data pipelines using SageMaker and EMR.
- Deploy and optimize ML models in production on AWS.
- Validate your skills through practical labs to pass the MLA-C01 exam.
- Integrate AWS best practices for scalable and secure ML solutions.
- Obtain the AWS Machine Learning Engineer Associate certification in minimum time.
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 Studio, data preparation (S3, Glue, EMR) with console labs
Discover the basics of machine learning on AWS through SageMaker Studio for an integrated environment. Dive into data preparation with S3 for storage, Glue for ETL, and EMR for big data processing. Perform practical labs on the AWS console to clean and transform real datasets, applying techniques like feature engineering. This immersive pedagogical approach allows you to quickly master ML data flows, essential for the MLA-C01 exam and your professional projects. (62 words)
Module 2Model Development and Training: SageMaker Pipelines, built-in algorithms (XGBoost, Deep Learning) with advanced exercises
Advance to model training with SageMaker Pipelines to automate end-to-end workflows. Explore built-in algorithms like XGBoost for classification and TensorFlow/PyTorch containers for deep learning. Perform practical exercises on the AWS console, hyperparameter tuning and evaluating models on real business cases. Learn to scale training with Spot Instances, strengthening your skills for production-ready deployments and optimal MLA-C01 certification preparation. (78 words)
Module 3ML Deployment, Monitoring, and Optimization: SageMaker Endpoints, Model Monitor, Clarify with intensive exam preparation
Finalize with model deployment via SageMaker Endpoints for scalable and secure inference. Implement Model Monitor to detect drifts and Clarify for explainability. Solve real-world cost/performance optimization cases. Conclude with intensive MLA-C01 exam preparation: timed practice multiple-choice questions, targeted review of domains (Data Engineering 20%, Modeling 36%, etc.), and exam strategies (time management, common pitfalls). Final labs consolidate your skills for guaranteed success. (85 words)
Evaluation method
- Continuous assessment via interactive quizzes and immediate feedback on AWS labs.
- MLA-C01 exam simulations with practice multiple-choice questions (150+ questions) on day 3.
- Final project: deployment of a complete ML pipeline evaluated by certified trainer.
Learning method
- 70% hands-on pedagogy: 15h of labs on live AWS console.
- Live remote sessions with screen sharing and breakout rooms for collaborative exercises.
- Post-training resources: video replays, slides, exam voucher, and alumni community.
Methods, materials and delivery
The Training AWS Machine Learning Engineer Associate MLA-C01 - Get 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 - Get 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 - Get 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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