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 Model Distillation - Optimize AI for Production 2026
Trusted by — schools, companies and industrial groups
41,258 programs · 25 countries
Every program built with a dedicated engineer
Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft, Microsoft and Atos.
Model Distillation training 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
Program
Model Distillation curriculum: 5 modules over 5 days
Module 1 : Model 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 2 : Advanced 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 3 : Distillation 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 4 : Automated 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 5 : Model 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.
How Model Distillation skills are assessed
- 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
How the Model Distillation course is taught
- 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
Model Distillation training: access and practical arrangements
The Training Model Distillation - Optimize AI for Production 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 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
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
How Learni guarantees the quality of your Model Distillation training
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
Model Distillation: frequently asked questions
Which tools are used in Model Distillation training?+
Hands-on work runs on pyTorch, tensorFlow, hugging Face, ONNX, distilBERT and tinyBERT. Those tools come from the Model Distillation program itself, delivered on site over 5 days, so participants practise on the stack they will use at work.
What can participants do after Model Distillation training?+
They can master model distillation techniques for professional applications, develop compact, high-performing models for certified business use and implement knowledge distillation with PyTorch and TensorFlow. Those are the stated objectives of the Model Distillation program at Intermediate level, checked by the end-of-session assessment.
What does the Model Distillation program cover, day by day?+
Day 1: Model Distillation Fundamentals: Principles and Teacher-Student Architectures (PyTorch, TensorFlow). Day 2: Advanced Model Distillation: Logit-Based and Feature-Based Techniques (Hugging Face, ONNX). Day 3: Distillation of Large Language Models: Compact LLMs for 2026 (DistilBERT, TinyBERT). Day 4: Automated Model Distillation Pipelines: MLOps Tools and Hyperparameters (AutoDistill, Ray Tune). Day 5: Model Distillation Deployment and Evaluation: Edge, Cloud, and Monitoring (Docker, Kubernetes, MLflow). The Model Distillation program runs over 5 days, delivered on site.
How is Model Distillation training assessed?+
Assessment relies on multiple-choice quiz to validate learning outcomes at the end of the training, continuous assessment through practical exercises on distillation and presentation of the capstone compact model project to the trainer. Learni issues a completion certificate together with the individual assessment report at the end of the Model Distillation program, which an L&D team can file as evidence.
How much does Model Distillation training cost per participant?+
Model Distillation training costs $5,775 per participant. For an in-company team, the flat rate starts at $10,395 for the whole group, up to 8 people. The detailed quote, sent within one business day, adjusts the amount to the format and how far the syllabus is tailored to your team.
How long does Model Distillation training take?+
5 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 Model Distillation 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 Model Distillation training?+
Mastery of Python, TensorFlow or PyTorch, fundamentals of deep neural networks.
Is a certificate issued after Model Distillation 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.
Does Learni provide the equipment for Model Distillation training?+
No. A computer and a stable internet connection are required for each participant. Learni provides the learning platform, the trainer and all course materials.
Your professional training, anywhere
Let's build your Model Distillation learning path.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.
Reply within 24h · Vetted experts · USD invoicing · W-9 available
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