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: Mastering Scikit-learn: The Essentials of Machine Learning for Professionals
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Understand the basic concepts of supervised and unsupervised machine learning
- Install and get hands-on with the Scikit-learn library
- Prepare and manipulate your datasets for Scikit-learn models
- Implement, tune, and evaluate predictive models with Scikit-learn
- Use pipelines for automating machine learning tasks
- Optimize hyperparameters using cross-validation
- Interpret results and avoid common overfitting pitfalls
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 mastery of Scikit-learn, your Machine Learning projects multiply modeling errors, wasting up to 40% of development time on unnecessary debugging.
Companies lose an average of 150 000 € per year on erroneous business decisions due to inaccurate predictions, with 85% of ML project failures attributed to poor algorithm implementation.
This gap exposes analysts and data scientists to a major risk of competitive lag, threatening promotions and company survival against agile rivals.
Every quarter without solid Scikit-learn skills widens an irrecoverable gap in data performance.
Program
Module 1Discovering Scikit-learn & Fundamental Principles of Machine Learning
Introduction to machine learning, presentation of Scikit-learn, installation and development environment, exploration of the documentation, library structure. First hands-on with datasets: loading, cleaning, transformation. Introduction to supervised vs. unsupervised tasks. Practical exercises on importing and preprocessing real data.
Module 2Building and Evaluating Predictive Models
Supervised learning with Scikit-learn: classification (Logistic Regression, k-Nearest Neighbors, SVMs), regression (Linear Regression, Decision Trees). Performance metrics: accuracy, recall, ROC curve, RMSE, cross-validation. Hands-on with Scikit-learn pipelines to automate data preparation and model training. Practical case studies for classification and regression. Visualizing results and interpretation. Introduction to unsupervised learning (Clustering, PCA).
Module 3Optimization, Advanced Pipelines, and Best Practices
Hyperparameter optimization with GridSearchCV and RandomizedSearchCV. Preventing overfitting and advanced cross-validation. Using complex pipelines to integrate preprocessing, feature selection, training, and predictions in an automated workflow. Best practices for production projects with Scikit-learn: model saving, reproducibility, version management. Hands-on practice on the full pipeline, from data cleaning to model deployment. Group evaluation on designing and training a complete model from a business dataset.
Evaluation method
- Multiple-choice quiz at the end of the training validating knowledge of Scikit-learn and machine learning
- End-to-end case study running throughout the training
- Individual feedback on hands-on exercises and proposed solutions
Learning method
- Alternating theory and practical workshops on real datasets
- Step-by-step guided exercises with collective review
- Permanent access to training materials, source code, and additional resources
Methods, materials and delivery
The Training: Mastering Scikit-learn: The Essentials of Machine Learning for Professionals 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: Mastering Scikit-learn: The Essentials of Machine Learning for Professionals 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: Mastering Scikit-learn: The Essentials of Machine Learning for Professionals 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: Mastering Scikit-learn: The Essentials of Machine Learning for Professionals training cost?+
The price is $3,675 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training: Mastering Scikit-learn: The Essentials of Machine Learning for Professionals training?+
The training lasts 3 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?+
Mastery of Python fundamentals, basics in statistics and probabilities.
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
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