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Training LoRA Fine-Tuning - Optimizing Large-Scale IoT Networks

Ref: GTY921
10 people max.
5500€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

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Learning objectives

  • Master advanced LoRA fine-tuning techniques for professional IoT applications
  • Develop skills in optimizing LoRa networks in enterprise settings
  • Configure MQTT-LoRa integrations for certified connectivity
  • Implement fine-tuned sensors with advanced power management
  • Deploy scalable and secure LoRA solutions in production
  • Optimize IoT performance through custom fine-tuning and real-world testing

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

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.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1LoRA Fine-Tuning Fundamentals: Advanced Protocols and Semtech Tools (Modulation Discovery)

Dive into the deep mechanisms of LoRA fine-tuning through practical workshops on Semtech SX126x kits, analyze modulations from SF7 to SF12, adjust Spreading Factor and Bandwidth parameters to maximize range, perform NS-3 simulations to validate gains, produce an initial optimized configuration report, integrate real IoT enterprise cases with pair exercises for rapid assimilation of professional concepts.

Module 2LoRA Fine-Tuning Network: Gateways and Servers (The Things Network Integration)

Configure multi-channel LoRa gateways with adaptive fine-tuning, deploy on The Things Network to test scalability, optimize Coding Rate and Sync Word using Wireshark tools, simulate 100 nodes to identify bottlenecks, integrate MQTT broker for real-time data streams, generate Grafana dashboards as deliverables, apply to industrial scenarios like smart cities, with real-time debugging and collaborative exercises to strengthen enterprise skills.

Module 3LoRA Fine-Tuning Sensors: Sensors and Power Consumption (Arduino/ESP32 Tools)

Fine-tune IoT sensors on ESP32-LoRa with duty cycle optimization, measure power consumption using multimeters and profilers, implement Adaptive Data Rate for 50% energy savings, test in controlled environments with humidity/vibration, develop custom firmware in MicroPython, produce functional MQTT-connected prototypes, analyze logs for iterative tuning, via connected agriculture use cases, practical workshops ensure professional mastery.

Module 4LoRA Fine-Tuning Security: Encryption and Authentication (LoRaWAN 1.1)

Strengthen LoRA security through AES-128 fine-tuning and key rotation, configure ABP/OTAA on ChirpStack, simulate replay attacks to validate robustness, integrate Device Integrity Protocol, test with 50 devices in a cluster, generate certificates and IAM policies, apply to critical IoT like connected healthcare, ethical pentest exercises, deliverables include comprehensive security audits, preparing for certified enterprise deployments.

Module 5LoRA Fine-Tuning Deployment: Scalability and Monitoring (Integrative Final Project)

Deploy a complete fine-tuned LoRA network in-person, integrate 20 real sensors with MQTT-LoRa hybrid, monitor via Prometheus/InfluxDB, optimize live for 99.9% QoS, test failover and roaming, produce a project dossier with quantified ROI, present to a panel simulating company management, consolidate learning through in-depth Q&A, obtain personalized feedback for certified IoT skills.

Evaluation method

  • Daily technical quizzes on LoRA fine-tuning
  • Final project on optimized network deployment
  • Practical evaluations in pairs with expert feedback

Learning method

  • 70% hands-on practice on real LoRa hardware and simulations
  • 30% advanced theory with IoT enterprise case studies
  • Collaborative exercises in small groups
  • Advanced simulations and real-time debugging

Methods, materials and delivery

The Training LoRA Fine-Tuning - Optimizing Large-Scale IoT Networks program is delivered onsite or remote (blended-learning, e-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 LoRA Fine-Tuning - Optimizing Large-Scale IoT Networks 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 LoRA Fine-Tuning - Optimizing Large-Scale IoT Networks 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

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
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« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
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« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
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« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
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.

Step 1

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.
Step 2

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.
Step 3

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.
Step 4

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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