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.
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Master XGBoost to develop ultra-high-performance professional models
- Optimize hyperparameters in enterprise settings with advanced certified techniques
- Implement XGBoost on GPU to accelerate large-scale trainings
- Design end-to-end pipelines with XGBoost and modern ML tools
- Deploy scalable XGBoost models in certified production environments
- Analyze feature importance for precise business decisions
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 advanced XGBoost mastery, your ML models lose 25-40% accuracy, leading to 30% false positives in fraud prediction and annual costs of 150k€ per data team.
Companies skipping XGBoost 2026 see their ML projects fail at 68% according to Gartner, wasting 2x more time on manual tuning.
Every delay widens the competitive gap, exposes you to flawed decisions, and stalls promotions because 82% of data roles require XGBoost.
Invest now to avoid these irreversible losses in competitiveness.
Program
Module 1Advanced XGBoost: Hyperparameter Tuning and GPU Optimization (Python, Dask, Rapids)
Dive into advanced XGBoost configuration with hands-on key parameters like learning rate, max_depth, and subsample. Practical exercises on real business datasets for manual tuning and grid search. Use GPU via cuML to accelerate trainings x10. Concrete customer churn prediction cases, optimization reports, and first deployable models with precise metrics like AUC and log-loss.
Module 2XGBoost in Production: Pipelines, Feature Engineering, and Deployment (MLflow, Docker, APIs)
Build complete XGBoost pipelines with advanced feature engineering on massive data via Dask. Integrate MLflow for experiment tracking and team reproducibility. Exercises on feature engineering with SHAP for business interpretability. Deploy in Docker containers connected to FastAPI for real-time inference. Banking fraud detection use case. Finalize a deliverable ongoing project with monitoring and A/B testing for immediate enterprise performance gains.
Evaluation method
- Technical MCQ on XGBoost and optimization at the end of the training
- Assessment through practical exercises on business datasets
- Presentation of the ongoing project with deployed XGBoost
Learning method
- Training by an active expert data science trainer
- Practical exercises on real enterprise XGBoost cases
- Progressive ongoing project with XGBoost in production
- Complete course materials and source codes provided
Methods, materials and delivery
The Training XGBoost - Optimizing ML Models in Production 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 XGBoost - Optimizing ML Models in Production 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 - Optimizing ML Models in Production 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 XGBoost - Optimizing ML Models in Production training cost?+
The price is $2,625 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training XGBoost - Optimizing ML Models in Production training?+
The training lasts 2 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?+
Proficiency in Python, pandas, scikit-learn, and supervised machine learning
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
Available on-site and remotely. Pick your city to see the local training center.
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