Introduction to machine learning in Python

Open to
Government analysts
Training category
Data science
Type of training
3 days
Data Science Campus Faculty
Data Science Campus Faculty


Machine learning is becoming more and more integrated in modern data analysis. Before performing advanced prediction, basic concepts in machine learning modelling must be understood and applied.

In this course you will learn about a range of machine learning topic areas. You will also learn how to perform the modelling operations using the Python programming language and the package ‘scikit-learn’.

This course is typically taught over three to four days. Each of the five chapters will take between two to four hours to work through. There are multiple supplementary case studies to help gain experience applying techniques taught.

Learning outcomes

At the end of the course participants will:

  • understand what machine learning is and important considerations in machine learning workflows
  • be able to process data to be machine learning ready
  • be able to create simple regression models
  • be able to create simple classification models
  • be able to evaluate supervised learning models
  • be able to optimise supervised learning models
  • understand why dimension reduction is used
  • be able to perform dimension reduction techniques

How to book

Please use your Learning Hub account to access the course online.

If you do not have a Learning Hub account, please contact


If you would like more information about this course, please email 

Related courses

Introduction to Python

Machine learning in R