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.
1 seat held for the next session
30:00Held for another
Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Master LoRA fine-tuning techniques to adapt AI models in professional IoT contexts
- Develop skills in optimizing large models for certified edge computing
- Design efficient fine-tuning pipelines reducing costs and time in business settings
- Implement LoRA 2026 on real IoT datasets using Hugging Face and PyTorch tools
- Deploy LoRA fine-tuned solutions on connected sensors for industrial applications
- Optimize AI performance in IoT via LoRA, ensuring scalability and GDPR compliance
Our social commitment
A school kit donated to a child for every training
To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.
- Backpack, notebooks and essential supplies
- Distributed through our partner charities
- Included, at no extra cost to you
The Learni story
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
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.
Program
Module 1LoRA Fine-Tuning Fundamentals: Principles, Setup, and Initial Tests (PyTorch, Hugging Face, IoT Datasets)
Discover the basics of LoRA fine-tuning 2026 through a practical immersion in Python and PyTorch. Set up your environment with Hugging Face Transformers to load pre-trained models adapted for IoT. Test on real sensor datasets such as industrial vibrations or LoRaWAN environmental data. Perform your first supervised fine-tunings with guided exercises. Analyze precision/recall metrics in real-time. Produce initial performance reports to validate professional skills.
Module 2Advanced LoRA Fine-Tuning 2026 Applications: Edge Deployment and IoT Optimization (LoRa, MQTT, Docker Containers)
Dive into deployments of LoRA fine-tuned models on IoT edge devices via Docker and Kubernetes. Integrate MQTT-LoRa protocols for real-time data streams. Optimize LoRA hyperparameters with tools like PEFT to reduce memory footprint by up to 90%. Simulate concrete Industry 4.0 cases on connected sensors. Deploy company-adapted CI/CD pipelines. Evaluate model robustness via stress tests. Generate deployable deliverables including secure APIs and monitoring dashboards for immediate ROI.
Evaluation method
- Daily interactive quizzes on LoRA concepts and implementations
- Final practical project: complete fine-tuning on personal IoT dataset
- Qualiopi certification issued after validated skills assessment
Learning method
- 70% hands-on: LoRA coding workshops on Jupyter and VS Code
- 30% theory: expert feedback on 2026 IoT advancements
- Real cases: anonymized enterprise LoRaWAN sensor datasets
- Continuous support: session replays, dedicated forum for 6 months post-training
Methods, materials and delivery
The Training LoRA Fine-Tuning 2026 - Optimizing Edge AI for IoT program is delivered onsite or remote (blended-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 2026 - Optimizing Edge AI for IoT 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 2026 - Optimizing Edge AI for IoT 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
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
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.
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.
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.
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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FAQ
Frequently asked questions
How much does the Training LoRA Fine-Tuning 2026 - Optimizing Edge AI for IoT training cost?+
The individual price is $2,310 (USD). The team / on-site group package is shown on the course page. A detailed quote is sent within one business day.
How long is the Training LoRA Fine-Tuning 2026 - Optimizing Edge AI for IoT training?+
The training lasts 2 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Solid foundations in Python, introductory machine learning, IoT protocols such as MQTT and LoRa
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
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