Loading...
Please wait a moment
New
Loading...
Please wait a moment
Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
10 spots per session maximum — 10 already taken
Which format do you prefer?
30 free minutes with a training advisor — no commitment.
Loading available slots...
Professional Training training in Memphis in October 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan Busi
Oct 1, 20268 min readMemphis
Explore the projected return on investment from no-code training programs for businesses by March 2026, including cost savings, productivity gains, and real-world case studies.
Allan BusiMar 19, 202612 min readCybersecurity training in Oklahoma City in December 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan BusiDec 1, 20269 min readOklahoma CityArtificial Intelligence training in Raleigh in June 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan BusiJun 1, 20268 min readRaleighDon't let this gap widen
Without mastery of CatBoost, machine learning teams mishandle categorical features, resulting in models that underperform by 20-30% against benchmarks.
This leads to 40% wasted engineering hours on inferior tuning and an average $1.2 million per project in delayed deployments, per industry reports from Gartner and McKinsey.
Production incidents spike by 35%, eroding C-suite trust, inviting regulatory scrutiny, and jeopardizing promotions in a field where 75% of AI roles prioritize boosting proficiency.
Every month without this edge, competitors surge ahead with superior predictive accuracy.
The Training: Mastering CatBoost: The Boosting Algorithm for Your Machine Learning Projects training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training: Mastering CatBoost: The Boosting Algorithm for Your Machine Learning Projects training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Training: Mastering CatBoost: The Boosting Algorithm for Your Machine Learning Projects training is carried out through:
Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Presentation of CatBoost, positioning among boosting algorithms (XGBoost, LightGBM), fundamental principles of boosting, getting started with the Python environment for CatBoost, installation and first example datasets.
Creating a modeling pipeline, using the CatBoostClassifier and CatBoostRegressor classes, native handling of categorical variables, model parameterization, cross-validation, performance metrics, visualization of results.
Hyperparameter tuning (grid search, random search), fine-tuned overfitting management, reduction of computation time, interpretability with methods (feature_importance_, SHAP values), CatBoost integration with scikit-learn, application to a real business case (practical workshop).
8 participants max.
$2,541 / per person
2 days
remoteTarget audience
Data scientists, AI engineers, data analysts wishing to leverage high-performance boosting algorithms
Prerequisites
Knowledge of Python, basics of supervised machine learning, and familiarity with the scikit-learn and pandas libraries
Loading...
Please wait a moment
Share in 2 clicks
Intermediate
€2,310.002 days
remote8 pers. max.Intermediate€3,465.003 daysremote8 pers. max.Advanced€2,310.002 daysremote10 pers. max.Intermediate€3,465.003 daysremote8 pers. max.
