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 XGBoost - Optimize Predictive Models in Business
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Master XGBoost to develop ultra-high-performance professional predictive models
- Optimize XGBoost hyperparameters in certified enterprise contexts
- Implement advanced feature engineering with XGBoost for precision gains
- Deploy XGBoost in production with monitoring and scalability
- Design end-to-end pipelines integrating XGBoost for business competitiveness
- Analyze XGBoost model interpretability using SHAP and LIME
- Develop certified XGBoost skills for data-driven projects
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 models lose 25% in average precision, driving 40% false positives in fraud detection and millions of euros wasted annually.
Data teams without XGBoost expertise spend 35% more time on manual tuning, delaying critical business insights by weeks.
In 2024, 68% of senior data roles require XGBoost, excluding non-certified profiles and blocking promotions.
Every unoptimized project widens the competitive gap, with 52% of companies reporting market losses due to obsolete ML.
Act to convert these risks into lasting competitive advantages.
Program
Module 1XGBoost Fundamentals: Advanced Architecture and Optimized Installation (Python, GPU, Dask)
Dive into the internal architecture of XGBoost for massive datasets, install the environment with GPU acceleration via CUDA, configure Dask for distributed processing, build your first models on concrete business cases like churn prediction, perform practical customized cross-validation exercises, produce initial performance reports, and optimize early iterations for immediate accuracy.
Module 2Tuning XGBoost: Hyperparameters and Automated Optimization (Optuna, Ray Tune)
Master exhaustive hyperparameter tuning for XGBoost with Optuna to explore massive spaces, integrate Ray Tune for distributed tuning on clusters, test on real Kaggle benchmarks adapted for enterprise use, analyze impacts via advanced metrics like AUC-ROC and log-loss, develop reusable automated scripts, generate comparative visualizations, and deploy your first tuned model with proven 15-20% precision gains.
Module 3Feature Engineering with XGBoost: Advanced Techniques and Pipelines (SHAP, Embeddings)
Design expert feature engineering for XGBoost by extracting embeddings from textual and temporal data, integrate SHAP for fine-grained feature interpretability, build automated pipelines with ColumnTransformer and custom transformers, apply to business projects like banking fraud detection, perform A/B testing on features, produce interactive dashboards via Plotly, and validate competitiveness gains through concrete enterprise cases.
Module 4Deploying XGBoost: Production, Monitoring, and Scalability (Docker, MLflow)
Deploy XGBoost in production via Docker and Kubernetes for high availability, integrate MLflow for experiment tracking and model versioning, configure drift monitoring with Evidently AI, simulate massive real-time loads, develop scalable FastAPI inference APIs, test robustness on critical enterprise scenarios, finalize with a deliverable ongoing project, security audit, and maintenance plan for immediate ROI.
Evaluation method
- Expert quiz on XGBoost algorithms and optimization
- Practical assessment via tuning and deployment of the ongoing project
- Oral defense of the end-to-end pipeline before the certified trainer
Learning method
- Courses delivered by an active expert data science trainer
- Practical exercises on real enterprise datasets and Kaggle
- Progressive ongoing XGBoost project over 4 days
- Complete course materials with source codes and resources
Methods, materials and delivery
The Training XGBoost - Optimize Predictive Models in Business 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 - Optimize Predictive Models in Business 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 - Optimize Predictive Models in Business 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 - Optimize Predictive Models in Business training cost?+
The price is $4,620 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training XGBoost - Optimize Predictive Models in Business training?+
The training lasts 4 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?+
Mastery of Python, scikit-learn, gradient boosting algorithms, and large datasets
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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