Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training DRP 2026 - Securing Enterprise Data Resilience training are: Basics in Data Science, knowledge of Python or R, experience in data management and ETL pipelines in a corporate environment. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training DRP 2026 - Securing Enterprise Data Resilience training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training DRP 2026 - Securing Enterprise Data… | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Training DRP 2026 - Securing Enterprise Data Resilience training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Training DRP 2026 - Securing Enterprise Data Resilience training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training DRP 2026 - Securing Enterprise Data Resilience training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training objectives

Master the design of Disaster Recovery Plans (DRP) tailored to professional Data Science environments

Develop certifiable skills in data pipeline and ML model resilience

Design disaster recovery strategies for data-driven companies

Implement backup and restore tools with Scikit-learn and R in a DRP context

Optimize business continuity through simulations of critical data scenarios

Evaluate and certify the robustness of Data Science infrastructures through practical training

Training program

Module 1DRP Fundamentals: Principles and 2026 Standards (Data Risks, RTO/RPO)

Discover the evolutions of the Disaster Recovery Plan (DRP) 2026 adapted to Data Science, analyze risks specific to data pipelines and ML models, calculate RTO and RPO through practical exercises on real datasets, identify vulnerabilities with open-source tools, draft an initial diagnostic of your data infrastructure, prepare deliverables compliant with ISO 22301 standards for companies.

Module 2Data Risk Analysis: Modeling and Prioritization (Scikit-learn, Stats)

Model data threats with Scikit-learn and R statistics, prioritize critical assets like SQL databases and Hadoop clusters, simulate cyberattacks and hardware failures on real company cases, integrate probabilistic metrics to quantify financial impacts, develop an interactive risk register, produce visual reports with Matplotlib to guide DRP decisions in professional training.

Module 3DRP Backup Strategies: Cloud and On-Premise Tools (AWS, Azure, R Scripts)

Implement automated backups for Data Science environments via AWS Backup and Azure Site Recovery, test Scikit-learn model restores with custom R scripts, configure multi-region replications on large datasets, evaluate performance via practical benchmarks, integrate monitoring with Prometheus, generate executable DRP test plans, ensure GDPR compliance for sensitive data in companies.

Module 4DRP Recovery Plans: Orchestration and Automation (Terraform, Ansible)

Orchestrate data infrastructure recovery with Terraform and Ansible in DRP 2026 context, automate ML pipeline deployments post-disaster, simulate failover on data-intensive Kubernetes clusters, validate recovery scripts with real-time exercises, optimize costs via elastic scaling, document complete operational procedures, prepare production-ready playbooks in certifying training.

Module 5DRP Testing and Optimization: Advanced Simulations (Full-Scale Exercises)

Execute full-scale data disaster simulations with chaos engineering, measure DRP effectiveness via 2026 KPIs, optimize with feedback loops and predictive AI using Scikit-learn, analyze real RTO/RPO gaps, certify your plan via simulated audit, develop a post-recovery monitoring dashboard in R, conclude with a deliverable project integrating all acquired skills to boost your Data Science career.