Machine Learning

Machine Learning

Start Date: September 8, 2025

L2D’s machine learning module provides an in-depth look at classical machine learning methods, providing a solid introduction to the core concepts and foundations of modern data prediction techniques. Students will learn to implement a range of classification algorithms, and will refine, measure and interpret their output for optimal results. This module will cover both supervised and unsupervised learning methods: namely the classification and clustering of different biological datasets, including images.

Price: £500 + VAT

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The Machine Learning module of L2D covers both supervised and unsupervised machine learning.

Supervised Machine Learning:

Key areas taught in L2D's exploration of Supervised Machine Learning include:
  • Classification: preparing data for classification, training classifier models
  • State space plot of model predictions
  • Prediction probabilities and feature importance
  • Complex training and testing of data
  • Comparison of different model classes
  • Stratified shuffle split
  • Evaluation of classification using AUC and ROC curves
  • Metrics for model evaluation
  • Permutation scoring and confusion matrices
  • Normalisation and hyperparameter tuning
  • Refinement and progressive adjustment
 

Unsupervised Machine Learning:

Key areas taught in L2D's exploration of Unsupervised Machine Learning include:
  • Gaussian Mixture Models (GMMs) and sci-kit learn
  • Clustering and automated data labelling
  • Quantitative scoring using ground truth
  • Introductions to the concept behind, and pitfalls of, clustering techniques
  • Medical image segmentation and object detection with GMMs
  • Dimensionality reduction (reducing computational workload of large high-dimensionality datasets)
  • PCA (Principal Component Analysis)
Note: L2D's Introduction to Python and Data Handling modules (or their equivalent) are compulsory requirements to taking the Machine Learning course.
Prerequisites: Introduction to Python and Data Handling or equivalent
Location: Online
Start Date: September 8, 2025
Duration: 12 weeks
Commitment: 48 hours
Dr. Adam Lee
Senior Fellow
Prof. Gerold Baier
Academic Lead
Dr. Laurence Blackhurst
Education and Technology Fellow
When does the next course start?

L2D runs two courses per year: one in the Spring and one in the Autumn. For 2025 admission, the Spring course commences on May 12th 2025, and the Autumn course commences on November 3rd 2025.

Are there any prerequisites to taking L2D?

To comfortably enrol in the L2D course, it is recommended that you have a very basic level of proficiency in using a personal computer: and a basic proficiency in using the operating system of your choosing (either Windows, Linux or Mac OS). You will also need a suitable computer of your own and access to a broadband internet connection.

Is the course suitable for beginners and programming novices?

Yes. Our Introduction to Python course – in its earliest modules – takes learners through the basics of setting up Python, and the most basic programming operations and functions. For those individuals who have either not programmed before, or who have limited programming experience, we recommend that you enrol in L2D from the Basic Python stage. Please contact [email protected] for more information on the optimal point at which to join the course.

Is the course suitable for individuals who are already experienced in Python programming?

Yes. For those individuals who have extensive Python programming experience, we recommend they take modules onwards of our Data Handling units: a prerequisite of this and all subsequent modules on our course, is a basic proficiency in the Python programming language. For learners who have this level of experience, we recommend joining from this stage, onwards. Please contact [email protected] to discuss this, and how to join at the appropriate stage of the course.

How is the course assessed?

The L2D course is assessed via topic-wise assignments, together with a Final Project:

  • Assignments: With each lesson release, assignments are set to monitor a learner’s progress, and identify facets of their learning that may require improvement. 
  • Final Project: This is assessed more strictly, upon successful completion of all our modules. The grade awarded for this project is pivotal to learners being awarded their L2D Certificate of Completion. Marks and written feedback are provided by our tutors throughout and are returned directly to students, shortly after submission.