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Training LightGBM 2026 - Master ultra-fast boosting in professional ML

Ref: LPF957
10 people max.
5250€ 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 LightGBM 2026 to develop high-performance professional ML models
  • Optimize LightGBM hyperparameters in certifying corporate contexts
  • Implement advanced feature engineering with LightGBM for accurate predictions
  • Deploy scalable LightGBM pipelines in production
  • Analyze and interpret LightGBM results for business decisions
  • Integrate LightGBM 2026 into collaborative data science workflows
  • Acquire certifying skills in fast boosting for professional reconversion

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 1LightGBM 2026 Fundamentals: installation and first models (Python, pip, datasets)

Rapid installation of LightGBM 2026 via pip or conda, professional environment setup with Jupyter and VS Code, exploration of real datasets like UCI or Kaggle, training your first classification and regression model, performance comparison with XGBoost on concrete cases, practical exercises to measure speed and accuracy, production of initial reports with key metrics like AUC and RMSE.

Module 2LightGBM 2026 Feature Engineering: advanced data preparation (pandas, categorical features)

Expert manipulation of large datasets with pandas and NumPy, automatic encoding of native categorical features in LightGBM 2026, creative engineering to boost accuracy like interactions and polynomials, implementation of scikit-learn pipelines integrated with LightGBM, tests on enterprise cases in finance and e-commerce, custom cross-validation, generation of optimized datasets ready for high-performance modeling.

Module 3LightGBM 2026 Hyperparameter Tuning: automated optimization (Optuna, grid search)

Systematic exploration of key parameters like num_leaves and learning_rate with grid search and random search, integration of Optuna for ultra-efficient Bayesian tuning in LightGBM 2026, early stopping management to avoid overfitting, optimization on GPU clusters for enterprise scaling, exercises on real-time datasets like IoT, comparison of time costs vs accuracy gains up to 20%, deliverable hyperopt configs reusable.

Module 4Advanced LightGBM 2026 Models: ensembles and interpretability (SHAP, custom objectives)

Construction of stacking ensembles and multi-objective boosting with LightGBM 2026, customization of loss objectives for specific business cases like ranking, model interpretation via integrated SHAP and LIME, feature importance analysis for actionable insights, practical exercises on churn and fraud predictions, debugging common production errors, production of interactive dashboards with Plotly for stakeholder reports.

Module 5LightGBM 2026 Deployment: production pipelines (Docker, MLflow, FastAPI)

Model containerization of LightGBM 2026 with Docker for AWS or Azure cloud deployment, experiment tracking via MLflow for professional versioning, creation of fast predictive APIs with FastAPI, load tests and real-time drift monitoring, CI/CD integration with GitHub Actions, end-to-end deployment exercises on a corporate end-to-end project, delivery of complete scripts and maintenance guide for immediate autonomy.

Evaluation method

  • Certifying MCQ to validate LightGBM 2026 skills at end of training
  • Continuous evaluation through practical exercises and hyperparameter tuning
  • Defense of end-to-end project for model deployment in production

Learning method

  • Courses led by an active expert data science trainer
  • Practical exercises on real enterprise cases with LightGBM 2026
  • Progressive end-to-end project over 5 days with code review
  • Complete course support PDF and Jupyter notebooks provided

Methods, materials and delivery

The Training LightGBM 2026 - Master ultra-fast boosting in professional ML 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 LightGBM 2026 - Master ultra-fast boosting in professional ML 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 LightGBM 2026 - Master ultra-fast boosting in professional ML 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

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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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