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 the principles of model distillation for professional AI applications
- Develop compact student models from powerful teacher models in enterprise settings
- Implement knowledge distillation techniques with PyTorch and Hugging Face
- Optimize model performance and size for certified deployment
- Design distillation pipelines tailored to real business use cases
- Evaluate and measure the effectiveness of distilled models in production
- Deploy lightweight models on edge devices and constrained servers
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: Teacher-Student Principles and PyTorch Setup (Loss Functions, Datasets)
Dive into the theoretical basics of model distillation with a focus on the teacher-student paradigm, install the dedicated PyTorch environment and prepare your real enterprise datasets, code your first vanilla distillation pipeline by applying loss functions like KL divergence and MSE, carry out practical exercises on image classification models, produce a student model 5x lighter with performance validation, and benefit from personalized code review to anchor your professional skills from the very first day.
Module 2Advanced Model Distillation Techniques: Features, Logits, and Multi-Stage Distillation (Hugging Face, NLP)
Explore sophisticated methods like feature and logit distillation on NLP tasks with Hugging Face Transformers, integrate BERT teacher to DistilBERT student while handling attention mechanisms and hidden states, apply exercises on enterprise text datasets such as sentiment analysis or NER, optimize hyperparameters via grid search and early stopping, test robustness on noisy data, generate precise fidelity and compression metrics, and build a progressive ongoing project that demonstrates a 70% reduction in latency while preserving 95% accuracy.
Module 3Model Distillation Deployment: Hybrid Optimization, Quantization, and Production Measurement (ONNX, TensorRT)
Move to action with deploying distilled models via ONNX and TensorRT for edge computing, combine distillation with pruning and quantization for extreme gains, integrate into enterprise CI/CD pipelines, measure latency, throughput, and memory footprint on real hardware, perform comparative benchmarks teacher vs student on IoT and mobile cases, produce deployable deliverables like optimized Docker images, and finalize with a certifying project defense that directly valorizes your skills in scalable production AI.
Evaluation method
- Technical multiple-choice quiz on distillation and optimization at the end of the course
- Practical evaluation through development of distillation pipelines
- Defense of the ongoing project with performance metrics
Learning method
- Instruction by an expert ML trainer with active professional experience
- Hands-on exercises on enterprise cases and open-source datasets
- Ongoing project for complete distillation across 3 days
- Detailed course materials and Jupyter notebooks provided
Methods, materials and delivery
The Training Model Distillation - Optimize AI for 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 - Optimize AI for 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 - Optimize AI for 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
★★★★★
« 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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