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 LoRaWAN Expert Training - Deploy Scalable IoT Networks training are: Mastery of LoRaWAN basics, experience with wireless networks, Linux, Python, and IoT protocols.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the LoRaWAN Expert Training - Deploy Scalable IoT Networks training is available in in-person. The format can be adapted to your needs (inter, intra, custom).

LoRaWAN Expert Training - Deploy Scalable IoT Ne... | 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 LoRaWAN Expert Training - Deploy Scalable IoT Networks 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 LoRaWAN Expert Training - Deploy Scalable IoT Networks 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 LoRaWAN Expert Training - Deploy Scalable IoT Networks 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 objectives

Design scalable LoRaWAN architectures for industrial IoT

Optimize network performance and energy consumption

Implement advanced protocols such as LoRaWAN 1.1 and Regional Parameters

Secure communications with AES-128 encryption and key management

Integrate LoRaWAN with MQTT, AWS IoT, and edge computing

Troubleshoot and monitor in real-time using tools like ChirpStack

Training program

Module 1LoRaWAN Architecture: Advanced Modeling (ChirpStack, Semtech, Simulations)

Dive into designing multi-gateway architectures, simulate topologies with NS-3, configure Network Server instances, perform exercises on LoRa radio propagation, produce a scalable network diagram ready for 10,000 nodes, test urban interference scenarios to master optimal gateway placement.

Module 2LoRaWAN Deployment: Installation and Configuration (Helium Hardware, TTN)

Install RAK and Dragino gateways, deploy a test network on The Things Network, integrate industrial sensors like Bosch, calibrate SF and ADR parameters through practical exercises, generate firmware configuration deliverables, simulate a deployment over 5 km² with RF coverage analysis.

Module 3LoRaWAN Optimization and Security: Advanced Protocols (LoRaWAN 1.1, Security)

Optimize QoS with Adaptive Data Rate, implement ABP/OTAA security and MIC, code Python scripts for key management, analyze replay attacks through real cases, produce a complete security audit, test inter-operator roaming for reliable hybrid networks.

Module 4LoRaWAN Integration and Troubleshooting: Real Projects (MQTT, Monitoring)

Integrate LoRaWAN with Kafka and Grafana for real-time dashboards, deploy an end-to-end project on AWS IoT Core, troubleshoot with Wireshark and LoRa Packet Forwarder, implement a smart city use case, deliver a performance report with 99.9% uptime metrics, prepare for expert certification.