Key Information

Tutor: Dr John Pinney
Course Level: Level 1
Course Credit: 1 credit
Prerequisites:
  No prior experience of programming is required.
Class Duration: 3 x 2 hour sessions
Format: 
Teams session with live teaching and hands-on practice

Machine learning is a broad topic, with a wide range of applications in scientific research. 

In this series of lectures, we will introduce the fundamental concepts of unsupervised and supervised learning, including the training, testing and evaluation of models for classification and regression.  We also explore the basic theory of neural networks and discuss their applications to deep learning.

 Examples will be provided using Orange data science environment.  No prior experience of programming is required.

Syllabus:

  • Unsupervised learning
    • Clustering
  • Supervised learning
    • Generalised linear models
    • Logistic regression
    • Decision trees
  • Evaluating performance
    • Cross-validation
    • ROC curves
  • Improving performance
    • Feature selection
    • Ensemble methods
  • Artificial neural networks
    • Multi-layer perceptron
    • Stochastic gradient descent
    • Activation functions
    • Deep learning applications


Learning Outcomes:

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

  • Explain the difference between supervised and unsupervised learning.
  • Select a suitable machine learning method for a given application.
  • Prepare your own training and testing data sets.
  • Evaluate the performance of a machine learning experiment.


Dates & Booking Information

DateTimePlatform/Venue
Monday 11 October 2021 (Part 1)
Wednesday 13 October 2021 (Part 2) &
Friday 15 October 2021 (Part 3)
10:00-12:00
10:00-12:00
10:00-12:00
Microsoft Teams
Monday 22 November 2021 (Part 1)
Wednesday 24 November 2021 (Part 2) &
Friday 26 November 2021 (Part 3)
10:00-12:00
10:00-12:00
10:00-12:00
Microsoft Teams
Monday 24 January 2022 (Part 1)
Wednesday 26 January 2022 (Part 2) &
Friday 28 January 2022 (Part 3)
10:00-12:00
10:00-12:00
10:00-12:00
Microsoft Teams
Tuesday 15 March 2022 (Part 1)
Thursday 17 March 2022 (Part 2) &
Friday 18 March 2022 (Part 3)
14:00-16:00
14:00-16:00
14:00-16:00
South Kensington (Face-to-Face)
Wednesday 04 May 2022 (Part 1)
Thursday 05 May 2022 (Part 2) &
Friday 06 May 2022 (Part 3)
10:00-12:00
10:00-12:00
10:00-12:00
Microsoft Teams
Monday 23 May 2022 (Part 1)
Tuesday 24 May 2022 (Part 2) &
Wednesday 25 May 2022 (Part 3)
10:00-12:00
10:00-12:00
10:00-12:00
Microsoft Teams
Summary of the table's contents

Please select a date and book on via Inkpath using your Imperial Single-Sign-On.