Study-Unit Description

Study-Unit Description


TITLE Machine Learning with Python

LEVEL D - Doctoral Workshops/Symposium

ECTS CREDITS Not Applicable

DEPARTMENT Doctoral School

DESCRIPTION Machine learning is the science of training algorithms to learn from data without the use of rules or analytic approaches. The vast amount of data gathered from sources varying from sensors and instrumentation to healthcare, social media and finance often require automated processing in a timely manner to extract information useful for decision-making. In this workshop, doctoral researchers will get the opportunity to “look under the hood” and understand the basics of typical machine learning algorithms related to regression, classification and clustering using Python.


By the end of this workshop, doctoral researchers should be able to:

- fit a model to data using regression techniques;
- understand the basic mathematical foundations of supervised and unsupervised machine learning algorithms;
- train a neural network to perform classification;
- use unsupervised learning techniques to cluster data;
- use Python machine learning libraries, such as keras and scikit-learn.

ADDITIONAL NOTES Only students who followed DOC6024 or else have proven experience with Python are eligible for this workshop.

This workshop is split into two parts – Part 1 and Part 2. Attendance is required in both parts.

Timetable Details - Please click here for further details.


Assessment Component/s Resit Availability Weighting
Attendance No 100%

LECTURER/S Matthew Montebello

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It should be noted that all the information in the description above applies to study-units available during the academic year 2020/1. It may be subject to change in subsequent years.