Scikit-Learn

The Scikit-Learn training is an intensive two-day course where 80% of the time is dedicated to practical workshops and 20% to theory.

Duration

16h · 2 days

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Who it's for

Ideal for teams that…

1 Developers and data engineers who want to expand their skills with Scikit-Learn

2 Data analysts who want to apply Scikit-Learn in their projects

3 AI and machine learning enthusiasts who want to start working with Scikit-Learn

Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

✓

How to install and configure Scikit-Learn in your work environment

✓

How to build, train, and optimize machine learning models with Scikit-Learn

✓

How to implement advanced models such as decision trees and ensemble methods

✓

How to prepare and deploy Scikit-Learn models in a production environment

Requirements

What you should know before we start

Basic knowledge of Python programming
Basic knowledge of machine learning
Ability to work in Jupyter Notebook or Google Colab environments

Program

What we actually do

Day 1: Introduction to Scikit-Learn and Machine Learning Basics

· History and development of Scikit-Learn
· Main functions and modules of the library
· Installing Scikit-Learn and dependencies
· Setting up a working environment (Jupyter Notebook)
· Data operations: loading, preprocessing, and analysis
· Preparing data for machine learning models
· Creating and running basic models (linear regression, classification)
· Implementing a linear regression model
· Training and evaluating the model on real data

Day 2: More Advanced Techniques and Practical Applications

· Decision trees and random forests
· Ensemble models (Boosting, Bagging)
· Hyperparameter optimization techniques (Grid Search, Random Search)
· Cross-validation and model evaluation metrics
· Preparing and processing data for classification
· Implementing and training models
· Exporting models and preparing them for deployment
· Deploying models in a production environment

Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.

How we work

From brief to retro in 30 days.

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

Send a brief. We'll reply within 1 day.

After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.

✓Quote within 48h of the brief

✓First session within 30 days

✓Pilot before the full decision

✓VAT invoice, payment in instalments possible

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