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Training Model Distillation 2026 - Compact Your AI Models by 90%

Ref: RWP726
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 the fundamentals of Model Distillation 2026 in certified professional training.
  • Develop practical skills to efficiently compress AI models in a business context.
  • Design distillation pipelines tailored to professional needs.
  • Implement advanced techniques using TensorFlow and PyTorch for lightweight models.
  • Optimize MLOps deployment of distilled models for immediate scalability.
  • Acquire certified skills in model distillation to boost your career.

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 1Model Distillation 2026: Fundamentals and Theoretical Principles (TensorFlow, Key Concepts)

Discover the basics of Model Distillation 2026 through clear explanations of knowledge transfer principles, distillation types (logits, features), and performance benefits. Use TensorFlow to model a simple teacher-student setup, perform practical exercises on MNIST datasets, analyze compression metrics, and produce your first 70% size-reduced model, with personalized feedback from expert trainers.

Module 2Model Distillation 2026: Techniques with TensorFlow (Tools, Offline Distillation)

Dive into TensorFlow to implement offline distillation on complex CNN models, configuring optimal hyperparameters like temperature and alpha. Work on real image classification cases, measure minimal accuracy loss, integrate visualizations with TensorBoard, perform inference speed benchmarks, and generate a deliverable: a 5x faster deployable model ready for business production.

Module 3Model Distillation 2026: PyTorch Implementation (Online Distillation, Advanced Cases)

Switch to PyTorch to master online and progressive distillation, applying hybrid techniques on datasets like CIFAR-10. Code dynamic teacher-student architectures, optimize with custom loss functions, test robustness to noise, compare multi-GPU performance, and create a detailed report with improved F1-score metrics, ideal for mobile and edge computing applications in professional training.

Module 4Model Distillation 2026: MLOps Integration (CI/CD Pipelines, Deployment)

Integrate Model Distillation 2026 into complete MLOps workflows using Docker and Kubernetes, automate pipelines with MLflow for tracking and versioning. Deploy on AWS or GCP cloud, simulate production loads, manage iterative updates, resolve common pitfalls like student overfitting, and produce a scalable end-to-end pipeline, certified for immediate business use.

Module 5Model Distillation 2026: Practical Projects and Final Optimization (TensorFlow, PyTorch, MLOps)

Apply everything in a capstone project: distill an LLM like BERT into a lightweight version using TensorFlow and PyTorch, integrate MLOps for real-time monitoring. Solve real business challenges (mobile latency, GPU costs), optimize for 90% size reduction with preserved accuracy, present your solution in a pitch, receive a Qualiopi certified evaluation, and leave with a concrete portfolio to boost your professional skills.

Evaluation method

  • Interactive quizzes and daily MCQs to validate theoretical knowledge.
  • Hands-on practical projects with personalized expert feedback.
  • Final exam and Qualiopi certified attestation on model distillation.

Learning method

  • Alternating theory and intensive practice on real business cases.
  • Hands-on exercises with TensorFlow, PyTorch, and MLOps tools.
  • Individualized pedagogical support in small groups of max 10.
  • Post-training resources: source codes, videos, and alumni community.

Methods, materials and delivery

The Training Model Distillation 2026 - Compact Your AI Models by 90% 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 - Compact Your AI Models by 90% 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 - Compact Your AI Models by 90% 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
★★★★★

« 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
★★★★★

« 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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