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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.
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Professional Training training in Dallas in July 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan Busi
Jul 1, 20268 min readDallas
Professional Training training in New York in September 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan BusiSep 1, 20268 min readNew YorkArtificial Intelligence training in Raleigh in June 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan BusiJun 1, 20268 min readRaleighNo-Code / Low-Code training in Leeds in November 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan BusiNov 1, 20268 min readLeedsDon't let this gap widen
Without expert mastery of scikit-learn, your models lose 25-40% accuracy in production, leading to estimated financial losses of 50k€/year for an average data team, erroneous business decisions on churn or fraud, manual tuning taking 3x the time, obsolescence against agile AI competitors, buggy pipelines causing 15% deployment downtimes, eroded competitiveness from suboptimal algorithms, team frustration from untuned hyperparameters.
The Training scikit-learn - Optimize Your Advanced ML Models 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 scikit-learn - Optimize Your Advanced ML Models 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 scikit-learn - Optimize Your Advanced ML Models 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.
Dive into building complex pipelines, integrate custom transformers for expert preprocessing, handle real datasets via interactive exercises, test robustness on concrete business cases like customer prediction, generate optimized deliverables ready to scale, boost your efficiency with seamless transformation chains.
Learn to tune precisely with GridSearchCV and RandomizedSearchCV on large datasets, explore parameter spaces through practical workshops, apply Bayesian Optimization to accelerate, validate on real benchmarks like Kaggle, produce detailed optimization reports, transform your suboptimal models into high-performing champions.
Master advanced ensembles with stacking and voting classifiers, integrate XGBoost into scikit-learn pipelines, deploy via joblib and Flask APIs on enterprise cases, simulate production with drift monitoring, create Dockerized scripts, deliver scalable and monitored models for immediate impact.
10 participants max.
$3,465 / per person
21 hours
in-personTarget audience
Data Scientists, Machine Learning Engineers, advanced data analysts seeking to upskill on scikit-learn.
Prerequisites
Advanced proficiency in Python, pandas, NumPy, basic ML algorithms, and intermediate scikit-learn usage.
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intermediate
€5,250.0035 hours
in-person10 pers. max.advanced€2,100.0014 hoursin-person10 pers. max.expert€4,200.0028 hoursin-person10 pers. max.intermediate€1,050.007 hoursremote10 pers. max.
