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.
Learning objectives
- Master key AWS services for Machine Learning such as SageMaker, Rekognition, and Comprehend to develop certified professional skills.
- Effectively prepare for the MLS-C01 certification exam with proven strategies and realistic practice QCMs.
- Configure and optimize end-to-end ML pipelines on AWS for scalable deployments.
- Implement ML models in production following AWS best practices and hands-on labs.
- Validate your AWS Machine Learning Specialty skills through a complete MLS-C01 exam simulation.
- Deploy secure and cost-optimized ML solutions on the AWS console.
- Optimize ML workload performance to meet professional cloud market requirements.
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, and Feature Engineering (AWS Console Labs)
Discover the basics of Machine Learning on AWS with SageMaker to create interactive notebooks and process massive datasets via S3 and Glue. Dive into hands-on labs on the AWS console to implement feature engineering, hyperparameter tuning, and distributed training. Explore real-world business cases using Rekognition for computer vision, optimizing data flows for immediate and professional scalability.
Module 2Advanced Models and ML Deployment: SageMaker Endpoints, Tuning, and Monitoring (Real AWS Exercises)
Deepen ML models with SageMaker Autopilot, JumpStart, and Reinforcement Learning. Deploy serverless endpoints via Lambda and API Gateway, integrating monitoring with CloudWatch and X-Ray. Hands-on labs on AWS console simulate production scenarios: automatic tuning, A/B testing, and bias management. Study concrete cases like fraud prediction in fintech leaders to master secure and optimized deployments.
Module 3Intensive MLS-C01 Exam Preparation: Practice QCMs, Strategic Review, and Certification (Full Simulations)
Day dedicated to MLS-C01 exam success with 200+ official-format practice QCMs, targeted review of the 65 questions, and anti-trap strategies (timing, scoring). Final labs consolidate skills on edge cases like securing XGBoost or multi-models. Expert advice for exam booking, post-certification, and CV enhancement. Achieve AWS Machine Learning Specialty certification by maximizing your score on the first attempt.
Evaluation method
- Continuous assessment via hands-on labs and interactive quizzes on the AWS console.
- Complete MLS-C01 exam simulation with practice QCMs and personalized feedback.
- Final project: deployment of an end-to-end ML pipeline evaluated by our certified experts.
Learning method
- 70% hands-on with real labs on a dedicated AWS account (credits included).
- Interactive remote pedagogy: screen sharing, breakout rooms, and session replays.
- Provided materials: slides, videos, and 6-month access to e-learning platform post-training.
Methods, materials and delivery
The Training AWS Machine Learning Specialty MLS-C01 - Get Your Cert 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 Cert 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 Cert 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
★★★★★
« 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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