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Training Model Distillation 2026 - Optimize AI Models in Production

Ref: GXE392
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 model distillation techniques to reduce the size of AI models
  • Develop professional skills in distillation with TensorFlow and PyTorch
  • Design optimized MLOps pipelines for distilled models in enterprise
  • Implement certifying knowledge distillation strategies in production
  • Optimize AI model performance for fast and cost-effective inference
  • Deploy lightweight models via industrial MLOps practices
  • Acquire certifying skills in Model Distillation 2026 training

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 1Fundamentals of Model Distillation: Theory and Knowledge Distillation (TensorFlow, PyTorch)

Discover the advanced principles of Model Distillation 2026, exploring teacher-student knowledge distillation with TensorFlow and PyTorch. Apply practical exercises on real datasets like CIFAR-10, configure custom distillers, analyze loss and fidelity metrics, produce your first models reduced by 70% in size, while integrating real business cases for immediate optimization.

Module 2Advanced Model Distillation Techniques: Feature and Logits Distillation (PyTorch Focus)

Dive into feature and logits distillation methods for Model Distillation 2026. Use PyTorch to implement multi-stage distillers, conduct hands-on workshops on Vision Transformers models, measure inference latency impact, optimize hyperparameters via grid search, generate teacher vs. student comparative reports, and apply to mobile and edge computing scenarios for concrete performance gains in enterprise.

Module 3Hybrid Model Distillation Optimization: Integrated Pruning and Quantization (TensorFlow, MLOps)

Integrate structured pruning and post-training quantization into your Model Distillation 2026 with TensorFlow. Combine these techniques in automated MLOps pipelines, practice on BERT and ResNet models through collaborative exercises, evaluate compression up to 90% without accuracy loss, deploy prototypes on Kubernetes, analyze reduced GPU costs, and deliver production-ready scripts.

Module 4MLOps for Model Distillation: CI/CD and Monitoring (TensorFlow Serving, PyTorch)

Deploy 2026 distilled models in full MLOps pipelines. Configure CI/CD pipelines with GitHub Actions and MLflow, integrate TensorFlow Serving and TorchServe for scalable inference, simulate deployments on AWS SageMaker, monitor drift via Prometheus, test robustness in real conditions, produce interactive dashboards to track enterprise KPIs, ensuring smooth production rollout.

Module 5Advanced Cases and Model Distillation Project: LLMs and 2026 Production (Full MLOps)

Apply Model Distillation 2026 to Large Language Models in a capstone project. Distill GPT-like models with PyTorch and TensorFlow, integrate MLOps for A/B testing and scaling, evaluate on industrial benchmarks like GLUE, optimize for edge devices, present deliverables in an enterprise pitch, receive expert feedback, and leave with a certifying portfolio to boost your career in optimized AI.

Evaluation method

  • Technical quizzes and advanced MCQs on distillation
  • Practical projects with real distilled models
  • MLOps case studies and final project defense

Learning method

  • Hands-on intensive project-based learning
  • Collaborative exercises in small groups
  • Real business cases and datasets
  • Post-training support and unlimited resources

Methods, materials and delivery

The Training Model Distillation 2026 - Optimize AI Models in Production 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 2026 - Optimize AI Models in Production 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 2026 - Optimize AI Models in Production 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
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« 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
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« 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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