Anyone interested in Predictive Machine Learning and wants to obtain a hands-on first introduction.

Aimed at:

Delivery method:

Interactive classroom training combining theory with practical exercises

Prerequisites:

Required preparation:

Introduction to Data Analytics with Python and Pandas

A GitHub account

3-4 hours

Foundation

Duration:

Skill level:

Prefered group size:

+/-10 participants per trainer (for the exercises, one additional trainer for each +/-4 students)

Course description

This course consists of two parts. In part I, participants learn about statistical analysis using logistic regression, focusing on issues such as data manipulation, gauging statistical significance, and interpreting estimation results Part II introduces machine learning using Scikit-learn, discussing such concepts as feature pre-processing, the bias-variance trade-off, and regularization.

Learning objective

Upon completion of this training, participants will be able to: use the available modules in Python to perform out of sample predictions.