Build predictive models with scikit-learn !
With this online course available in English, you will learn the basics of machine learning and how to use the scikit-learn Python library. This Mooc is accessible to anybody with basic Python programming skills.
The training, developed by the scikit-learn team, is mainly practical, focusing on application examples, and based on Python code executed by the participants. Everything is integrated in the Mooc and you don't have to install anything.
At the end of this course, you will be able to:
- Grasp the fundamental concepts of machine learning
- Build a predictive modeling pipeline with scikit-learn
- Develop intuitions behind machine learning models from linear models to gradient-boosted decision trees
- Evaluate the statistical performance of your models
- basic knowledge of Python programming: defining variables, writing functions, importing modules
- previous experience with NumPy, Pandas and Matplotlib libraries is recommended but not mandatory
Schedule and registration
- Resgitration : April 19th - July 13rd 2021
- Courses : May 18th - July 14th 2021
Scikit-learn is our reference tool when it comes to machine learning. We are proud to be a member of the scikit-learn community and to support this leading machine learning software library. Widely used by our teams of data scientists both in France and in a dozen or so countries worldwide, this reference tool ensures a high level of reliability for the predictive models designed using it. Scikit-learn helps us to create innovative services, including the automated and accelerated processing of supporting documents in the event of a loss. It also improves internal processes, such as dispatching incoming mail or risk monitoring. Our goal is to automate 80% of all our processes between now and 2022.
Chief Data Scientist at BNP Paribas