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.
Trusted by — schools, companies and industrial groups
Learning objectives
- Master supervised classification algorithms with Scikit-learn for professional projects
- Develop skills in preparing and feature engineering complex enterprise datasets
- Implement advanced models like Random Forest and SVM to optimize accuracy
- Evaluate and tune classifier performance with ROC metrics and cross-validation
- Integrate R for in-depth statistical analyses in certifying data science
- Design end-to-end pipelines adapted to real-world cases in professional training
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 this upskilling, your team accumulates a technological gap that translates directly into productivity loss.
Organizations that don't train their talents on key topics see their competitiveness drop.
Every quarter without training is a gap widening with competitors who invest.
The cost of inaction quickly exceeds that of well-targeted training.
Program
Module 1Data Classification Fundamentals 2026: Data Preparation and Supervised Models (Scikit-learn, Feature Engineering)
Discover advanced preprocessing techniques for heterogeneous datasets, cleaning outliers and balancing classes with SMOTE, through practical workshops on Jupyter Notebook. Implement KNN and Logistic Regression on Iris and Titanic datasets, analyze initial biases, and generate initial accuracy reports. Explore feature selection with chi2 and RFE, apply to real e-commerce cases, produce visualizations with Matplotlib to identify key patterns, and validate first models in real-time.
Module 2Data Classification Optimization 2026: Tuning, Evaluation, and R Integration (Hyperparameters, ROC Curves)
Dive into hyperparameter tuning via GridSearchCV and RandomizedSearch on Random Forest and Gradient Boosting, optimize to minimize overfitting on real datasets like Wine Quality. Evaluate with ROC-AUC curves, precision-recall, and confusion matrices, compare cross-validation performances. Integrate R for Bayesian analyses and advanced GLM, migrate Scikit-learn scripts to tidyverse, deploy pipelines with MLflow for tracking. Conclude with a capstone project on fraud classification, delivering a deployable model and executive report.
Evaluation method
- Interactive quizzes at the end of each day on key concepts and implementations
- Individual practical project with a real dataset and peer review
- Qualiopi certificate issued after validation of exercises and final MCQ
Learning method
- 70% practical: live coding workshops on real datasets with Scikit-learn and R
- 30% theory: focus on algorithms and metrics via interactive slides
- Guided exercises in small groups for immediate feedback
- Access to replays for 30 days for self-review
Methods, materials and delivery
The Training Data Classification 2026 - Mastering Advanced Algorithms 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 Data Classification 2026 - Mastering Advanced Algorithms 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 Data Classification 2026 - Mastering Advanced Algorithms 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 Data Classification 2026 - Mastering Advanced Algorithms training cost?+
The individual price is $2,310, and the team / on-site price is $5,775 (USD). A detailed quote is sent within one business day.
How long is the Training Data Classification 2026 - Mastering Advanced Algorithms 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?+
Basic knowledge of Python or R, notions of descriptive statistics, and introductory 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.
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