Loading...
Please wait a moment
New
Loading...
Please wait a moment
Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
Which format do you prefer?
30 free minutes with a training advisor — no commitment.
Loading available slots...
No-Code / Low-Code training in Leeds in November 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan Busi
Nov 1, 20268 min readLeeds
Artificial Intelligence training in Glasgow in June 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan BusiJun 1, 20268 min readGlasgowArtificial Intelligence training in Mesa in September 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan BusiSep 1, 20268 min readMesaArtificial Intelligence training in San Francisco in October 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan BusiOct 1, 20268 min readSan FranciscoThe Training: Mastering XGBoost for High-Performance Machine Learning Models training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training: Mastering XGBoost for High-Performance Machine Learning Models training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Training: Mastering XGBoost for High-Performance Machine Learning Models training is carried out through:
Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Presentation of XGBoost and its place among boosting algorithms. Reminders on decision trees, bagging, and boosting. Introduction to gradient boosting and model composition. Getting started with XGBoost in Python. Loading, preparing, and exploratory analysis of datasets. First binary classification model with XGBoost. Analysis of results and initial performance indicators.
In-depth understanding of XGBoost parameters (booster, learning rate, max_depth, subsample, colsample_bytree, gamma, lambda, alpha, etc.). Introduction to manual and automatic hyperparameter tuning (Grid Search, Random Search, Hyperopt, Optuna). Overfitting management with cross-validation. Use of early stopping. Importance of feature selection and handling missing data in XGBoost.
Deploying an XGBoost model in a Scikit-learn pipeline. Saving and loading trained models (pickle, joblib). Model interpretability with SHAP and Feature Importance. Communicating and presenting results to a business audience. Concrete case studies: analysis of a real-world regression dataset and a multi-class classification dataset. Best practices for industrialization and production monitoring.
8 participants max.
$3,630 / per person
3 days
distancielTarget audience
Data scientists, engineers, data analysts, AI professionals, and developers wishing to deepen their use of XGBoost for machine learning projects.
Prerequisites
Knowledge of supervised machine learning fundamentals, proficiency in Python, and classic data science tools (Pandas, NumPy, Scikit-learn).
Loading...
Please wait a moment
Share in 2 clicks
Discover a step-by-step roadmap to become a skilled AI engineer by March 2026. From prerequisites to advanced projects, tools, and job strategies, this guide covers everything for aspiring professionals.
Allan BusiMar 7, 202612 min readSoftware Development training in Louisville in January 2025 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan BusiJan 1, 20259 min readLouisvilleAvancée
€2,100.002 journées
distanciel10 pers. max.Novice€5,250.005 journéesdistanciel10 pers. max.Expert€2,100.002 journéesdistanciel10 pers. max.Intermédiaire€3,150.003 journéesdistanciel10 pers. max.