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.
Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud
Specialist course · Minimum level required
Trusted by — schools, companies and industrial groups
41,060 programs · 25 countries
Every program built with a dedicated engineer
Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft and Microsoft.
Amazon SageMaker training objectives
- Understand the architecture and main components of Amazon SageMaker
- Prepare, clean, and explore datasets on SageMaker
- Create, train, and optimize machine learning models using SageMaker notebooks
- Deploy, monitor, and scale ML models with SageMaker in production
- Automate the machine learning lifecycle with SageMaker Pipelines and integrate MLOps
Program
Amazon SageMaker curriculum: 3 modules over 3 days
Module 1 : Introduction and Getting Started with Amazon SageMaker
Presentation of the AWS environment, discovery of the SageMaker Studio interface, notebook management, introduction to S3 storage and IAM permissions. Importing and initial exploration of datasets in SageMaker.
Module 2 : Data Preprocessing, Model Training, and Tuning
Data preparation and cleaning techniques with SageMaker Processing. Use of built-in algorithms (XGBoost, Linear Learner, etc.), experiment management, hyperparameter tuning, implementation of interactive notebooks for training.
Module 3 : Deployment, Monitoring, and Advanced Architectures
Model deployment via managed endpoints (real-time inference, batch transform), lifecycle management with SageMaker Pipelines, monitoring, MLOps, security, costs, and best practices for industrialization on AWS.
How Amazon SageMaker skills are assessed
- Hands-on case study of training and deploying a complete model
- Final multiple-choice quiz on all Amazon SageMaker features
How the Amazon SageMaker course is taught
- Demonstrations in the SageMaker Studio environment
- Individual hands-on practice on a guided project
- Collaborative workshops and real-world use cases
- Enriched course materials with AWS resources
Amazon SageMaker training: access and practical arrangements
The Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud program is delivered onsite or remote (blended-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: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud 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: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud 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
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
The Learni story
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
Our method
How Learni guarantees the quality of your Amazon SageMaker training
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.
Our social commitment
A school kit donated to a child for every training booked
To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.
- Backpack, notebooks and essential supplies
- Distributed through our partner charities
- Included, at no extra cost to you
FAQ
Amazon SageMaker: frequently asked questions
What can participants do after Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud training?+
They can understand the architecture and main components of Amazon SageMaker, prepare, clean, and explore datasets on SageMaker and create, train, and optimize machine learning models using SageMaker notebooks. Those are the stated objectives of the Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud program at Advanced level, checked by the end-of-session assessment.
What does the Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud program cover, day by day?+
Day 1: Introduction and Getting Started with Amazon SageMaker. Day 2: Data Preprocessing, Model Training, and Tuning. Day 3: Deployment, Monitoring, and Advanced Architectures. The Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud program runs over 3 days, delivered on site.
How is Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud training assessed?+
Assessment relies on hands-on case study of training and deploying a complete model and final multiple-choice quiz on all Amazon SageMaker features. Learni issues a completion certificate together with the individual assessment report at the end of the Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud program, which an L&D team can file as evidence.
How much does Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud training cost per participant?+
Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud training costs $4,725 per participant. For an in-company team, the flat rate starts at $8,558 for the whole group, up to 8 people. The detailed quote, sent within one business day, adjusts the amount to the format and how far the syllabus is tailored to your team.
How long does Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud training take?+
3 days, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.
Who pays for Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud training?+
Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
What do participants need to know before Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud training?+
Prior knowledge in Python, machine learning, and basic AWS cloud concepts.
Is a certificate issued after Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud training?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.
Does Learni provide the equipment for Training: Master Amazon SageMaker: Develop and Deploy Machine Learning Models on the AWS Cloud training?+
No. A computer and a stable internet connection are required for each participant. Learni provides the learning platform, the trainer and all course materials.
Your professional training, anywhere
Let's build your Amazon SageMaker learning path.
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