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Training Supervised Fine-Tuning SFT - Optimizing AI Models Big Data

Ref: XVQ882
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 Supervised Fine-Tuning (SFT) techniques to fine-tune AI models on professional datasets.
  • Develop skills in preparing Big Data for certified SFT training.
  • Design SFT pipelines integrating Hadoop and Data Lakes for enterprise scalability.
  • Implement SFT optimization strategies reducing computational costs by 40%.
  • Deploy fine-tuned SFT models in production with advanced monitoring.
  • Evaluate SFT impact on business performance via precise metrics.

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 Supervised Fine-Tuning: SFT protocols on structured datasets (Hugging Face, PyTorch)

Discover the essential principles of Supervised Fine-Tuning (SFT) through practical workshops on Big Data datasets, set up PyTorch and Hugging Face environments, prepare annotated corpora with tools like LabelStudio, test initial fine-tunings on BERT models, analyze learning curves, produce initial convergence reports, integrate feedback for rapid iterations, all while simulating real enterprise cases for an immersive professional training.

Module 2SFT Data Preparation: Hadoop ingestion and Data Lake (Spark, Delta Lake)

Dive into extracting and cleaning massive volumes via Hadoop and Spark, structure Data Lakes for optimal SFT, apply ETL transformations on terabytes of data, manage class imbalances with advanced SMOTE, validate quality via automated pipelines, generate labeled training subsets, simulate real enterprise data flows, export transformer-compatible formats, obtain deliverables ready for fine-tuning, strengthening certified Big Data skills.

Module 3Advanced SFT Implementation: Hyperparameters and LoRA (PEFT, Accelerate)

Configure SFT hyperparameters for rapid convergence, integrate LoRA via PEFT for memory efficiency on GPU clusters, train on Big Data datasets with Accelerate, monitor via Weights & Biases, optimize batch sizes and learning rates, test early stopping, compare baselines vs. fine-tuned models, produce F1-scores above 90%, apply to enterprise NLP cases, deliver reproducible notebooks for teams.

Module 4Big Data SFT Optimization: Distributed scaling (DeepSpeed, Ray)

Master SFT scaling on clusters via DeepSpeed ZeRO and Ray Train, distribute training on Hadoop Data Lakes, reduce time by 70% via sharding, manage multi-GPU with mixed precision, integrate distributed monitoring, test robustness on noisy datasets, refine via active learning, deploy prototypes in Docker containers, analyze AWS/GCP costs, obtain scalable pipelines for enterprise production, certifying advanced skills.

Module 5SFT Deployment and Evaluation: Integrated MLOps (MLflow, Kubernetes)

Deploy fine-tuned SFT models via MLflow and Kubernetes, set up FastAPI for Big Data inference, integrate Drift monitoring with Evidently, A/B test versions, measure quantified business ROI, automate retraining on Hadoop streams, secure with tokenization, produce Grafana dashboards, validate GDPR compliance, finalize real project portfolio, conclude with professional SFT skills certification for career boost.

Evaluation method

  • Daily interactive quizzes on SFT concepts and Big Data tools.
  • Final project: complete fine-tuning on simulated enterprise dataset.
  • Peer-programming evaluation and personalized coach feedback.

Learning method

  • 70% practical workshops, 30% theory for maximum retention.
  • 24/7 Slack support, unlimited replays of remote sessions.
  • Real Big Data datasets, provided cloud environments (AWS/GCP).
  • Qualiopi certification validating intermediate SFT skills.

Methods, materials and delivery

The Training Supervised Fine-Tuning SFT - Optimizing AI Models Big Data 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 Supervised Fine-Tuning SFT - Optimizing AI Models Big Data 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 Supervised Fine-Tuning SFT - Optimizing AI Models Big Data 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
★★★★★

« 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
★★★★★

« 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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