Introduction to machine learning in Python

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

Machine learning is becoming 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 modelling operations using the Python programming language and the package “scikit-learn”.

This course is split into 5 chapters, which are usually taught over 3 to 4 days. Each of the  chapters will take between 2 and 4 hours to work through. There are a series of case studies to help you gain experience of applying techniques.

Learning outcomes

On this course you will:

  • learn what machine learning is
  • gain an understanding of important considerations in machine learning workflows
  • learn how to process data to be machine learning ready
  • learn how to create simple regression models
  • learn how to create simple classification models
  • learn how to evaluate supervised learning models
  • learn how to optimise supervised learning models
  • gain an understanding of why dimension reduction is used
  • learn how 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 

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Machine learning in R