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Training Data Classification - Master Advanced Predictive Algorithms

Ref: FMR266
10 people max.
5500€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

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Learning objectives

  • Master advanced data classification algorithms for accurate predictions in business
  • Optimize models with Scikit-learn and R during this professional certifying training
  • Develop skills in handling imbalanced data for real data science projects
  • Implement ensemble and boosting techniques to boost predictive performance
  • Design end-to-end classification pipelines tailored to business needs
  • Rigorous model evaluation to ensure professional reliability in the enterprise

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

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.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Advanced Fundamentals of Data Classification: Evaluation Metrics, Cross-Validation (Scikit-learn)

Discover advanced metrics such as AUC-ROC, F1-score, and precision-recall to rigorously evaluate your data classification models. Apply k-fold cross-validation techniques with Scikit-learn on real datasets. Complete practical exercises on business cases to identify common pitfalls. Build your first comprehensive evaluation reports, integrating visualizations with Matplotlib for educational and professional analysis.

Module 2Supervised Data Classification Algorithms: SVM, Optimized KNN (Scikit-learn, Hyperparameters)

Dive into non-linear SVM and weighted KNN using Scikit-learn. Tune hyperparameters with GridSearchCV and RandomizedSearchCV on complex datasets. Test on real-world cases like banking fraud detection. Develop optimized scripts to scale to large volumes. Analyze the impact of RBF and polynomial kernels on performance. Produce enterprise-ready deliverables with quantified metrics and comparative visualizations.

Module 3Data Classification in R: Decision Trees, Random Forest (caret, randomForest packages)

Master decision trees and Random Forest in R using the caret and randomForest packages for robust data classification. Apply bagging and boosting techniques on real enterprise data. Perform automatic tuning exercises via trainControl. Compare results with Scikit-learn for a hybrid approach. Generate automated reports with ggplot2 charts. Integrate practical cases like customer segmentation for actionable deliverables.

Module 4Advanced Data Classification Management: Imbalanced Classes, SMOTE, XGBoost (Scikit-learn, R)

Handle imbalanced datasets in data classification with SMOTE, undersampling, and oversampling using Scikit-learn and R. Implement XGBoost and LightGBM for superior performance. Test on real scenarios like churn prediction. Optimize decision thresholds to maximize recall. Develop complete pipelines with imbalanced-learn. Produce sensitivity analyses and detailed business reports for immediate enterprise application.

Module 5Data Classification Deployment: MLflow Pipelines, SHAP Interpretability (Scikit-learn, R, Production)

Deploy your data classification models in production with MLflow and Docker. Integrate interpretability using SHAP and LIME in Scikit-learn and R. Simulate AWS or Azure cloud environments on critical business cases. Automate CI/CD pipelines for rapid implementation. Evaluate robustness against data drifts. Finalize with complete deliverables including Streamlit dashboards and executive reports for immediate professional adoption.

Evaluation method

  • Daily technical quizzes on metrics and algorithms
  • Final end-to-end classification project on real dataset
  • Peer-review evaluation and feedback from Qualiopi-certified trainer

Learning method

  • Hands-on practical exercises with Jupyter and RStudio
  • Concrete case studies from data-driven companies
  • Live Q&A sessions for personalized issue resolution
  • Unlimited access to replays and post-training resources

Methods, materials and delivery

The Training Data Classification - Master Advanced Predictive Algorithms program is delivered onsite or remote (blended-learning, e-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 - Master Advanced Predictive 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 - Master Advanced Predictive 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

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
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« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
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« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
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« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
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.

Step 1

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.
Step 2

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.
Step 3

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.
Step 4

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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