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 Raspberry Pi - Master Advanced IoT Projects training are: Basic Linux proficiency, intermediate Python, GPIO basics, and simple electronics.. A preliminary interview validates your eligibility.

What are the objectives of the Training Raspberry Pi - Master Advanced IoT Projects training?

The objectives of the Training Raspberry Pi - Master Advanced IoT Projects training are: Configure Raspberry Pi for advanced projects. Program optimized Python GPIO scripts. Integrate sensors and actuators in real-time. Develop connected IoT applications. Optimize performance and power consumption. Deploy secure production solutions. Analyze and debug embedded systems. Upon completion, you will be able to put these skills into practice.

Is the training available in person?

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

Training Raspberry Pi - Master Advanced IoT Proj... | 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 Raspberry Pi - Master Advanced 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 Training Raspberry Pi - Master Advanced 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 Training Raspberry Pi - Master Advanced 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 access terms and deadlines

Training program

Module 1Advanced Raspberry Pi Configuration: Custom OS, GPIO, Secure Boot (Raspbian, System Tools)

Dive into installing optimized OS on Raspberry Pi, configure advanced GPIO with wiringPi, test custom boot scripts through practical exercises, assemble your first stable setup, and validate with a functional deliverable ready for IoT, while mastering common pitfalls for a flawless start.

Module 2Embedded Python Programming: GPIO Scripts, Multithreading (Python, RPi.GPIO)

Code advanced Python scripts to control GPIO with multithreading, implement interrupts and timers via interactive workshops, debug in real-time with dedicated IDEs, create a responsive blinking prototype, and optimize for low latency, gaining autonomy for your innovative Raspberry Pi projects.

Module 3Sensor/Actuator Integration: I2C, SPI, ADC (DHT22, Motors, Raspberry Pi)

Connect and program DHT22 sensors and motors via I2C/SPI on Raspberry Pi, perform continuous measurement exercises, fuse multi-sensor data into local dashboards, test robustness with simulated failure cases, and produce a complete IoT module ready to scale your embedded applications.

Module 4Connected IoT Projects: MQTT, Web Servers (Mosquitto, Flask, Raspberry Pi)

Develop Flask web servers and MQTT brokers on Raspberry Pi, connect to the cloud via network exercises, implement interactive remote dashboards, secure data flows with certificates, deploy an end-to-end IoT project like a connected weather station, and measure performance for immediate professional results.

Module 5Optimization and Deployment: Monitoring, Containers (Docker, Prometheus, Raspberry Pi)

Optimize Raspberry Pi power consumption with Docker and Prometheus monitoring, debug complex systems through advanced workshops, deploy securely in production, analyze metrics for fine-tuning, finalize a certified project portfolio, and leave with skills ready to boost your corporate IoT achievements.