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 Advanced Raspberry Pi Training - Deploy Complex IoT Projects training are: Mastery of Linux, advanced Python programming, Raspberry Pi basics (GPIO, Raspbian, simple projects).. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Advanced Raspberry Pi Training - Deploy Complex IoT Projects training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Advanced Raspberry Pi Training - Deploy Complex… | 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 Advanced Raspberry Pi Training - Deploy Complex IoT Projects 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 Advanced Raspberry Pi Training - Deploy Complex IoT Projects 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 Advanced Raspberry Pi Training - Deploy Complex IoT Projects 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

Deploy a high-availability Raspberry Pi cluster with Docker Swarm

Integrate Raspberry Pi with cloud services like AWS IoT or Azure

Optimize performance for real-time applications and edge computing

Implement advanced security protocols (VPN, encryption, firewall)

Develop complex IoT projects with MQTT, Node-RED, and databases

Automate deployments via Ansible and CI/CD for Raspberry Pi

Analyze and debug embedded systems under high load

Training program

Module 1Advanced Architecture: Raspberry Pi Clustering (Docker, Kubernetes lite, High Availability)

Dive into configuring a multi-Raspberry Pi cluster, install Docker and Swarm to orchestrate containers, perform practical exercises on load balancing, test fault tolerance with concrete industrial IoT cases, produce a deliverable: functional cluster deployed and documented, gain autonomy to scale your embedded projects.

Module 2Cloud Integration and APIs: AWS IoT, Azure, RESTful Services

Connect your Raspberry Pi to AWS IoT Core and Azure IoT Hub, code Python scripts to send data via secure MQTT, integrate REST APIs with Node.js, simulate real sensor data flows in hands-on exercises, generate dynamic dashboards, leave with a cloud-ready prototype, transform your ideas into scalable and professional solutions.

Module 3IoT Edge Computing: MQTT, Node-RED, NoSQL Databases (InfluxDB)

Master Node-RED for visual IoT flows, configure MQTT broker on Raspberry Pi, integrate InfluxDB for time-series storage, develop exercises on edge processing of sensor data, analyze patterns with Grafana, create a deliverable: complete IoT system with automated alerts, boost your skills to dominate edge computing in production.

Module 4Security, Optimization, and Final Projects (Ansible, Monitoring)

Strengthen security with WireGuard VPN, advanced ufw, and encryption, optimize kernel for real-time via CPU/RAM tuning exercises, automate with Ansible playbooks, monitor via Prometheus, finalize a personal capstone project, validate skills through peer audit, leave as an expert ready to deploy in the enterprise.