Key Information

Tutors: Dr John Pinney
Course Level: 
Level 1
Prerequisites: 

  • Introduction to Python (or equivalent prior learning)
  • Introduction to Machine Learning (or equivalent prior learning)

Duration: 3 x 2 hour sessions  
Format: Live online or live face to face with hands-on practice.e

Course Resources

Following on from the Introduction to Machine Learning course, this series of hands-on workshops will get you started with applying supervised and unsupervised machine learning methods in Python, using the popular scikit-learn package.

Learning Outcomes:


After completing this workshop, you will be better able to:

  • Prepare a dataset for machine learning in Python
  • Select a scikit-learn method appropriate for a particular learning task
  • Construct your own workflows for model training and testing
  • Evaluate the performance of a model


Dates & Booking Information

DateTimePlatform/Venue
Monday 31 January 2022 (Part 1)
Monday 07 February 2022 (Part 2) &
Monday 14 February 2022 (Part 3)
10:00-12:00
10:00-12:00
10:00-12:00
Microsoft Teams
Tuesday 22 March 2022 (Part 1)
Tuesday 29 March 2022 (Part 2) &
Tuesday 05 April 2022 (Part 3)
14:00-16:00
14:00-16:00
14:00-16:00
South Kensington (Face-to-Face)
Thursday 12 May 2022 (Part 1)
Thursday 19 May 2022 (Part 2) &
Thursday 26 May 2022 (Part 3) 
15:00-17:00
15:00-17:00
15:00-17:00
South Kensington (Face-to-Face)
Thursday 09 June 2022 (Part 1)
Thursday 16 June 2022 (Part 2) &
Thursday 23 June 2022 (Part 3)
10:00-12:00
10:00-12:00
10:00-12:00
Microsoft Teams
Summary of the table's contents

Please email the Graduate School with your CID number to book your place.