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.
Describe your need, get a tailored program and a pre-filled quote in 3 min. A 100% free call with an advisor.
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To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
Don't let this gap widen
Without mastering XGBoost, your predictive models underperform severely, with average accuracy 25% below that of experts.
Companies therefore lose an average of 150 000 € per project through bad decisions and missed opportunities, with 70% of advanced modeling failures tied to improper tuning.
Your career stagnates: relegated to basic tasks, you let competing data scientists capture promotions and budgets.
Every quarter without advanced skills widens the gap, threatening your team's competitiveness against the surge in data.
Presentation of XGBoost and its history. Principle of gradient boosting, differences with Random Forest, introduction to the Python library. Types of problems addressed. Preparation and cleaning of datasets, handling missing variables, transformation and encoding. Manipulation of XGBoost DMatrix. First trials of simple classification and regression models. Practical examples step by step.
Detailed presentation of main XGBoost hyperparameters (max_depth, learning_rate, n_estimators, subsample, colsample_bytree, etc.) and their effects. Setting up automatic cross-validation and Grid Search for optimization. Identifying and managing overfitting. Using appropriate evaluation metrics (AUC, accuracy, log-loss, RMSE). Practical exercises with advanced tuning and result interpretation.
Explainability of XGBoost models (feature importance, SHAP, visualization). Preventing and analyzing overfitting, handling imbalanced data, advanced preprocessing techniques for XGBoost. Sectoral examples (finance, health, industry). Export, saving, and deploying an XGBoost model in production. Best practices for scaling (big data). Practical cases and mini-projects throughout the day.
The Training: Mastering XGBoost: Advanced Modeling for Data Science program is delivered onsite or remote (blended-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.
For the smooth delivery of the Training: Mastering XGBoost: Advanced Modeling for Data Science program, the following equipment is required:
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.
Assessment of skills acquired during the Training: Mastering XGBoost: Advanced Modeling for Data Science program is performed through:
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.
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
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.
Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.
30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.
No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.
Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.
A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.
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PythonIndustry-certified
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Generative AI & LLMsIndustry-certified
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Machine learningIndustry-certifiedAvailable on-site and remotely. Pick your city to see the local training center.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.