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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Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.

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 ML models remain suboptimal, losing up to 30% accuracy on critical predictions such as customer churn or fraud detection, according to Kaggle studies.
This produces massive financial losses: the average bank forfeits 15% of annual revenue due to ineffective boosting.
In business, this stalls promotions and competitiveness, exposing you to agile competitors.
For data scientists and .NET developers, ignoring XGBoost blocks the transition to productive AI, risking career obsolescence.
Invest now to turn these risks into lasting strategic advantages.
Discover XGBoost through its quick installation with pip and conda, configure your first decision trees on Iris and Titanic datasets, perform basic training with early stopping to avoid overfitting, make predictions and visualize feature importances via matplotlib, produce your first performance reports with accuracy and ROC-AUC, apply practical exercises on real business cases to consolidate learning from the first day.
Dive into feature optimization with categorical encoding and scaling, build automated pipelines integrating XGBoost and preprocessing, test grid search and random search to hyperparameterize learning rate, max_depth, and subsample, analyze learning curves to detect underfitting, deploy k-fold cross-validation on large datasets, generate detailed reports with SHAP to interpret predictions, implement practical cases inspired by Kaggle challenges adapted to professional contexts.
Integrate XGBoost into .NET workflows via ML.NET and Python calls, develop REST APIs with Flask to serve models, containerize with Docker for scalable deployment, manage production performance monitoring with Prometheus, optimize inference latency on large volumes, test robustness against data drift, produce interactive dashboards with Plotly Dash, apply exercises on real business scenarios for smooth and secure production deployment.
Master GPU acceleration with native XGBoost to process millions of samples, combine XGBoost in ensembles with stacking and bagging to surpass benchmarks, correct biases with reweighting and focal loss techniques, analyze residual errors for rapid iterations, deploy hybrid .NET-Python models in microservices, evaluate business impact via simulated ROI, finalize with a capstone project on a custom dataset including source code deliverable and full report for skills certification.
The Training XGBoost - Optimizing High-Performance ML 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.
For the smooth delivery of the Training XGBoost - Optimizing High-Performance ML Models 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 XGBoost - Optimizing High-Performance ML Models 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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30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.