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 Data Classification - Classify Data for Reliable Predictions
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Master the fundamentals of data classification in certified professional training
- Develop skills to prepare datasets in a business environment
- Implement classification algorithms with Scikit-learn and R
- Evaluate models to optimize accurate predictions
- Design data classification projects applied to business
- Acquire recognized data science skills certification
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 data classification, 70% of companies lose predictive insights opportunities, leading to decision errors costing up to 15% of annual revenue according to Gartner.
Misclassified models generate massive false positives, such as 25% of customer churn poorly detected, impacting retention and revenue.
Careers stagnate without classification skills, novice data analysts risk obsolescence in the face of the AI boom.
Invest in professional training to avoid competitiveness losses, secure your data-driven future right now.
Program
Module 1Data Classification Fundamentals: Key Concepts, Problem Types (Python Tools, Scikit-learn)
Discover the basics of data classification through interactive presentations and introductory exercises on Python and Scikit-learn, analyze supervised vs unsupervised problems, handle simple datasets like Iris, identify relevant features, create first visualizations with Matplotlib, produce initial reports on binary classification, consolidate essential concepts for rapid progression in a small group.
Module 2Data Preparation for Data Classification: Cleaning, Feature Engineering (pandas, R dplyr)
Dive into dataset cleaning with pandas and R, handle missing values, encode categorical variables, scale features using StandardScaler, apply oversampling techniques for imbalanced datasets, test on real e-commerce cases, generate automated pipelines, validate data quality with basic metrics, obtain datasets ready for efficient business modeling.
Module 3Basic Data Classification Algorithms: KNN, Naive Bayes, Decision Trees (Scikit-learn, R)
Implement KNN for nearest neighbors, train probabilistic Naive Bayes, build decision trees with Scikit-learn and R packages, compare performances on real healthcare datasets, adjust hyperparameters manually, visualize trees with Graphviz, predict classes on test data, analyze common errors, produce first reliable business-applicable predictions.
Module 4Advanced Data Classification Algorithms: SVM, Random Forest (Optimization, Cross-Validation)
Master SVM for maximum margins, deploy robust Random Forest ensembles with Scikit-learn and R randomForest, practice k-fold cross-validation, tune hyperparameter grids with GridSearchCV, evaluate ROC-AUC on customer churn, diagnose overfitting via learning curves, optimize models for superior accuracy, export deployable predictors to production.
Module 5Projects and Deployment in Data Classification: Business Cases, Basic MLOps (Streamlit, R Shiny)
Carry out end-to-end bank fraud classification projects, integrate complete Scikit-learn and R pipelines, deploy interactive dashboards with Streamlit and Shiny, test model robustness on real data, present deliverables to stakeholders, discuss ethics and bias, plan cloud scalability, obtain validated skills certification, leave with a concrete portfolio for data science employability.
Evaluation method
- Daily quizzes on theoretical concepts
- Graded practical case studies
- Final data classification project evaluated by experts
Learning method
- Learning through concrete business projects
- Supervised hands-on sessions in small groups of max 10
- Certified real-world data science cases
- Post-training resources support for 6 months
Methods, materials and delivery
The Training Data Classification - Classify Data for Reliable Predictions 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 - Classify Data for Reliable Predictions 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 - Classify Data for Reliable Predictions 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 - Classify Data for Reliable Predictions training cost?+
The price is $5,775 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training Data Classification - Classify Data for Reliable Predictions training?+
The training lasts 5 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?+
Basics in Python or R programming, descriptive statistics fundamentals, regular Excel use
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
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