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.
1 seat held for the next session
30:00Held for another
Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.
Training: Mastering XGBoost for High-Performance Machine Learning Models
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Understand the XGBoost algorithm and its mathematical foundations.
- Effectively configure and optimize an XGBoost model.
- Apply XGBoost to practical classification and regression cases.
- Master the management of overfitting and biases.
- Interpret XGBoost model results and explain them to a non-technical audience.
- Automate hyperparameter tuning with modern tools.
- Integrate XGBoost into a production machine learning pipeline.
Our social commitment
A school kit donated to a child for every training
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.
- Backpack, notebooks and essential supplies
- Distributed through our partner charities
- Included, at no extra cost to you
The Learni story
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
Why this program matters
Without mastering XGBoost, your machine learning models lose up to 35% in accuracy, generating erroneous predictions that bias strategic decisions.
Companies suffer average losses of 120 000 € per year due to suboptimal models, with 40% of data scientists' time wasted on ineffective tuning and endless debugging.
60% of ML project failures are linked to improper use of advanced algorithms like XGBoost, threatening your team's competitiveness and your professional advancement.
Each month without in-depth expertise amplifies these risks, letting the competition overtake you inexorably.
Program
Module 1Foundations of XGBoost and First Implementations
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.
Module 2Advanced Optimization and Tuning of XGBoost
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.
Module 3Production Deployment, Interpretability, and Case Studies
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.
Evaluation method
- Multiple-choice quizzes to validate technical skills at the end of each module.
- Implementation of an end-to-end mini-project evaluated by the trainer.
- Self-assessment questionnaires at the beginning and end of the training.
Learning method
- Detailed presentations and explanatory diagrams.
- Coding and practical workshops on Jupyter Notebooks.
- Real case studies and experience feedback.
- Complete pedagogical support, scripts, and datasets provided.
Methods, materials and delivery
The Training: Mastering XGBoost for High-Performance Machine Learning Models 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.
Equipment required
For the smooth delivery of the Training: Mastering XGBoost for High-Performance Machine Learning Models 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: Mastering XGBoost for High-Performance Machine Learning Models 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
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.
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.
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.
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.
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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FAQ
Frequently asked questions
How much does the Training: Mastering XGBoost for High-Performance Machine Learning Models training cost?+
The price is $3,675 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training: Mastering XGBoost for High-Performance Machine Learning Models training?+
The training lasts 3 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Knowledge of supervised machine learning fundamentals, proficiency in Python, and classic data science tools (Pandas, NumPy, Scikit-learn).
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
On-site & remote
This training across cities
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