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.
Training LoRA Fine-Tuning - Customizing AI LLMs in 2026
Trusted by — schools, companies and industrial groups
25,719 programs · 25 countries
Every program built with a dedicated engineer
Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft and Microsoft.
Learning objectives
- Master LoRA principles for fine-tuning professional models
- Develop skills in efficient adaptation of LLMs in enterprise settings
- Implement LoRA with PEFT and Hugging Face for certified projects
- Design LoRA fine-tunings on real and optimized datasets
- Deploy customized LoRA models in certified production environments
- Optimize GPU resources via LoRA for professional gains
Program
Module 1Fundamentals: Understanding LoRA Fine-Tuning (PEFT, Hugging Face, PyTorch)
Discovery of key LoRA concepts to adapt LLMs without full retraining, installation of the environment with PEFT and transformers libraries, first exercises on a BERT-like model to customize simple NLP tasks, analysis of low-rank matrices and their impact on GPU resources, creation of a first functional LoRA script with validation on an enterprise dataset, immediate trainer feedback to consolidate the basics.
Module 2Practice: Applying LoRA Fine-Tuning to LLMs (datasets, hyperparameters, evaluation)
Practical fine-tuning of an LLM like Llama on a custom text dataset for an enterprise chatbot, configuration of LoRA hyperparameters (rank, alpha), use of Hugging Face Trainer to accelerate training, evaluation tests with perplexity and BLEU metrics, collaborative exercises on real customer automation cases, generation of performance reports and iterative adjustments to maximize professional accuracy.
Module 3Deployment: Optimize and Deploy LoRA Fine-Tuning (ONNX, AI Servers, Monitoring)
Export of optimized LoRA models to ONNX for rapid deployment, integration with FastAPI or Docker for enterprise APIs, monitoring of production performance via Weights & Biases, exercises on scaling LoRA for large data volumes in 2026, creation of tailored CI/CD pipelines, finalization of a complete red thread project with certified documentation and maintenance plan for immediate implementation.
Evaluation method
- Quiz to validate learning outcomes at the end of the training
- Continuous assessment through practical LoRA exercises
- Presentation of the red thread fine-tuning project
Learning method
- Courses led by an active AI expert trainer
- Practical exercises on real enterprise LoRA use cases
- Progressive red thread project for LLM fine-tuning
- Complete course materials provided to each participant
Methods, materials and delivery
The Training LoRA Fine-Tuning - Customizing AI LLMs in 2026 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 - Customizing AI LLMs in 2026 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 - Customizing AI LLMs in 2026 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.
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.
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.
Our social commitment
A school kit donated to a child for every training booked
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
FAQ
Frequently asked questions
Which tools are used in LoRA Fine-Tuning training?+
Hands-on work runs on PEFT, hugging Face, pyTorch, datasets, hyperparameters and evaluation. Those tools come from the LoRA Fine-Tuning program itself, delivered on site over 3 days, so participants practise on the stack they will use at work.
What can participants do after LoRA Fine-Tuning training?+
They can master LoRA principles for fine-tuning professional models, develop skills in efficient adaptation of LLMs in enterprise settings and implement LoRA with PEFT and Hugging Face for certified projects. Those are the stated objectives of the LoRA Fine-Tuning program at Beginner level, checked by the end-of-session assessment.
What does the LoRA Fine-Tuning program cover, day by day?+
Day 1: Fundamentals: Understanding LoRA Fine-Tuning (PEFT, Hugging Face, PyTorch). Day 2: Practice: Applying LoRA Fine-Tuning to LLMs (datasets, hyperparameters, evaluation). Day 3: Deployment: Optimize and Deploy LoRA Fine-Tuning (ONNX, AI Servers, Monitoring). The LoRA Fine-Tuning program runs over 3 days, delivered on site.
How is LoRA Fine-Tuning training assessed?+
Assessment relies on quiz to validate learning outcomes at the end of the training, continuous assessment through practical LoRA exercises and presentation of the red thread fine-tuning project. Learni issues a completion certificate together with the individual assessment report at the end of the LoRA Fine-Tuning program, which an L&D team can file as evidence.
How much does LoRA Fine-Tuning training cost per participant?+
LoRA Fine-Tuning training is priced on quote. The amount depends on headcount, format and how far the syllabus is tailored to your team. A detailed quote is sent within one business day, and team pricing covers the whole group from the second participant.
How long does LoRA Fine-Tuning training take?+
3 days, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.
Who pays for LoRA Fine-Tuning training?+
Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
What do participants need to know before LoRA Fine-Tuning training?+
Python basics, numpy/pandas, and deep learning fundamentals.
Is a certificate issued after LoRA Fine-Tuning training?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.
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