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Training XGBoost - Optimize Predictive Models in Business

Ref: DAK859
10 people max.
5600€ 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
4 journées
distanciel

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Learning objectives

  • Master XGBoost to develop ultra-high-performance professional predictive models
  • Optimize XGBoost hyperparameters in certified enterprise contexts
  • Implement advanced feature engineering with XGBoost for precision gains
  • Deploy XGBoost in production with monitoring and scalability
  • Design end-to-end pipelines integrating XGBoost for business competitiveness
  • Analyze XGBoost model interpretability using SHAP and LIME
  • Develop certified XGBoost skills for data-driven projects

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 1XGBoost Fundamentals: Advanced Architecture and Optimized Installation (Python, GPU, Dask)

Dive into the internal architecture of XGBoost for massive datasets, install the environment with GPU acceleration via CUDA, configure Dask for distributed processing, build your first models on concrete business cases like churn prediction, perform practical customized cross-validation exercises, produce initial performance reports, and optimize early iterations for immediate accuracy.

Module 2Tuning XGBoost: Hyperparameters and Automated Optimization (Optuna, Ray Tune)

Master exhaustive hyperparameter tuning for XGBoost with Optuna to explore massive spaces, integrate Ray Tune for distributed tuning on clusters, test on real Kaggle benchmarks adapted for enterprise use, analyze impacts via advanced metrics like AUC-ROC and log-loss, develop reusable automated scripts, generate comparative visualizations, and deploy your first tuned model with proven 15-20% precision gains.

Module 3Feature Engineering with XGBoost: Advanced Techniques and Pipelines (SHAP, Embeddings)

Design expert feature engineering for XGBoost by extracting embeddings from textual and temporal data, integrate SHAP for fine-grained feature interpretability, build automated pipelines with ColumnTransformer and custom transformers, apply to business projects like banking fraud detection, perform A/B testing on features, produce interactive dashboards via Plotly, and validate competitiveness gains through concrete enterprise cases.

Module 4Deploying XGBoost: Production, Monitoring, and Scalability (Docker, MLflow)

Deploy XGBoost in production via Docker and Kubernetes for high availability, integrate MLflow for experiment tracking and model versioning, configure drift monitoring with Evidently AI, simulate massive real-time loads, develop scalable FastAPI inference APIs, test robustness on critical enterprise scenarios, finalize with a deliverable ongoing project, security audit, and maintenance plan for immediate ROI.

Evaluation method

  • Expert quiz on XGBoost algorithms and optimization
  • Practical assessment via tuning and deployment of the ongoing project
  • Oral defense of the end-to-end pipeline before the certified trainer

Learning method

  • Courses delivered by an active expert data science trainer
  • Practical exercises on real enterprise datasets and Kaggle
  • Progressive ongoing XGBoost project over 4 days
  • Complete course materials with source codes and resources

Methods, materials and delivery

The Training XGBoost - Optimize Predictive Models in Business 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 XGBoost - Optimize Predictive Models in Business 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 XGBoost - Optimize Predictive Models in Business 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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