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.
1 seat held for the next session
30:00Held for another
Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.
Training AI Act — Risk Management and Data Governance
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Implement the iterative risk management system required by Art. 9
- Identify risks to health, safety, and fundamental rights, including intended uses and foreseeable misuses
- Define mitigation measures and determine the acceptability of residual risk, supported by test evidence
- Document the data governance required by Art. 10, from collection to labeling
- Measure and correct biases, and frame the processing of sensitive data solely for this purpose
Our social commitment
A school kit donated to a child for every training
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
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.
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 1The Article 9 Risk Management System
An iterative process planned across the entire lifecycle, not a one-off deliverable: identification and analysis of known and reasonably foreseeable risks, estimation of risks related to intended use and reasonably foreseeable misuse, evaluation of emerging risks revealed by post-market monitoring, adoption of appropriate measures. Hierarchy of measures: eliminate or reduce by design, mitigate and control what remains, inform and train the deployer. Special attention to vulnerable persons and effects on minors. How to integrate this system with existing product or quality risk management, and what AI risk management frameworks contribute methodologically without replacing the regulation.
Module 2Risk Workshop on a Real System
Framing: purpose, affected populations, influenced decisions, deployment context. Construction of risk scenarios, from most probable to most severe, including misuse and silent failure. Rating, acceptability criteria, reasoned thresholds rather than intuitive scores. Determination of mitigation measures and their evidence: what is tested, how, with which evaluation set and success criterion. Drafting of residual risk and its justification, which must hold up to an auditor. Cross-review between subgroups: each team challenges another's analysis, an exercise that reveals blind spots better than internal review.
Module 3Data Governance: Article 10 Point by Point
Required practices for training, validation, and test datasets: design choices, data origin and original purpose of collection, preparation operations (annotation, labeling, cleaning, updating, enrichment, aggregation), assumptions made about what the data are supposed to represent, assessment of availability, quantity, and suitability, examination of possible biases with regard to health, safety, and fundamental rights, detection and correction measures, identification of gaps that prevent compliance. Expected relevance, representativeness, and accuracy, and geographic, contextual, or behavioral specificity of the usage framework. Practical work: draft the governance sheet for an existing dataset.
Module 4Measuring Biases, Tracing, and Articulating with GDPR
Build a measurement protocol: dedicated evaluation sets, selected subpopulations and how to define them without inventing them, fairness metrics and what each truly indicates, thresholds and trade-offs between incompatible metrics. Corrective measures: rebalancing, reweighting, constraints during training, post-processing, and the cost of each. Exceptional processing of special categories of data solely for bias detection and correction: strict conditions, minimization, security, deletion, traceability of the decision. Articulation with GDPR: legal basis, minimization, retention periods, data protection impact assessment and what it shares with the AI Act file. Case study: deliver the complete data file of a system and its quantified remediation plan.
Evaluation method
- Self-assessment at the start, followed by a validation quiz at the end of each day
- Continuous assessment of deliverables produced during the session, reviewed by the instructor
- Final presentation: group presentation of the compliance deliverable built during the training
Learning method
- Work on participants' real AI use cases or on anonymized training files
- Guided reading of the regulation articles and annexes, with the consolidated text in view
- Reusable models provided: register, document templates, analysis and control grids
Methods, materials and delivery
The Training AI Act — Risk Management and Data Governance 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 AI Act — Risk Management and Data Governance 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 AI Act — Risk Management and Data Governance 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.
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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FAQ
Frequently asked questions
How much does the Training AI Act — Risk Management and Data Governance training cost?+
The price is $4,620 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training AI Act — Risk Management and Data Governance training?+
The training lasts 4 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Knowledge of the model lifecycle and requirements applicable to high-risk systems. Experience in risk management or data quality is a plus.
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
On-site & remote
This training across cities
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