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.
Learning objectives
- Master model distillation techniques for professional applications
- Develop compact, high-performing models for certified business use
- Implement knowledge distillation with PyTorch and TensorFlow
- Optimize large language models for 2026 deployment
- Design automated and scalable distillation pipelines
- Evaluate post-distillation performance in production contexts
- Deploy distilled models on edge devices for business gains
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.
Program
Module 1Model Distillation Fundamentals: Principles and Teacher-Student Architectures (PyTorch, TensorFlow)
Dive into the basics of model distillation with an expert trainer, install PyTorch and TensorFlow environments to create your first teacher-student pair, explore distillation losses like KL-divergence and MSE, perform practical exercises on CIFAR-10 and MNIST datasets, produce your first 5x lighter compact model while retaining 95% of performance, and analyze metrics to validate immediate production gains.
Module 2Advanced Model Distillation: Logit-Based and Feature-Based Techniques (Hugging Face, ONNX)
Advance to the next level by implementing logit-based distillation on BERT transformers via Hugging Face, compare feature-based methods with intermediate activations to boost accuracy, work on real business cases like text classification, generate models exported to ONNX for interoperability, test in real-time on GPU/CPU, and document a performance report showing latency reductions up to 70%, ready for your 2026 AI projects.
Module 3Distillation of Large Language Models: Compact LLMs for 2026 (DistilBERT, TinyBERT)
Tackle distillation of massive LLMs like GPT or Llama by creating ultra-efficient DistilBERT versions, use methods like layer-wise distillation and progressive shrinking, apply to real business NLP tasks such as text generation or Q&A, measure impact on memory and inference time with TensorBoard, produce a mobile-deployable model, and optimize for edge computing, transforming your AI workflows into scalable and cost-effective solutions.
Module 4Automated Model Distillation Pipelines: MLOps Tools and Hyperparameters (AutoDistill, Ray Tune)
Automate your processes with MLOps pipelines dedicated to model distillation using AutoDistill and Ray Tune for hyperparameter search, integrate CI/CD with GitHub Actions for team reproducibility, experiment on custom datasets like your business data, generate teacher vs. student benchmarks, fine-tune temperature and alpha for optimal accuracy, and deploy a complete workflow ready for 2026 production, accelerating your iterations by 50%.
Module 5Model Distillation Deployment and Evaluation: Edge, Cloud, and Monitoring (Docker, Kubernetes, MLflow)
Finalize with deployment of distilled models in Docker and Kubernetes containers for cloud scalability, monitor performance via MLflow and Prometheus in real conditions, evaluate robustness against adversarial attacks and data drift, apply to a business capstone project like computer vision, produce a live metrics dashboard, and prepare a secure production rollout plan, ensuring 60% cloud cost savings and GDPR compliance for 2026.
Evaluation method
- Multiple-choice quiz to validate learning outcomes at the end of the training
- Continuous assessment through practical exercises on distillation
- Presentation of the capstone compact model project to the trainer
Learning method
- Courses led by an active AI expert trainer
- Practical exercises on real business ML cases
- Progressive capstone distillation project throughout the training
- Complete course materials and source codes provided to each participant
Methods, materials and delivery
The Training Model Distillation - Optimize AI for Production 2026 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 Model Distillation - Optimize AI for Production 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 Model Distillation - Optimize AI for Production 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
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
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
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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