We hope to launch our brand new HSMA-λ (HSMA lambda) courses, aimed at leaders and decision makers, in winter 2026/27 – spring 2027, and HSMA 7 in spring/summer 2027.
Want to hear when we open up applications for either of these? Send us an email at penchord@exeter.ac.uk (stating your full name and organisation) to be added to our mailing list.
Session lead: Dr Daniel Chalk
In this session we'll look at some core concepts important for processing text data.
We'll also learn a few little neat things we can do with our data along the way, including wordclouds and a method for assessing the similarity of different bits of text.
This session makes use of the nlp_basics environment
Session lead: Dr Daniel Chalk
In this session we'll continue our journey into Natural Language Processing.
Have you got named entities? Do you need them recognised? Then have we got the session for you! Our session on Named Entity Recognition will talk all about named entities, and recognition of them. Along the way we'll stop by Sesame Street and Fraggle Rock, talk about Transformers, Parsing, Grammar, POS Tagging and more.
This session makes use of the nlp_ner environment
Session lead: Dr Daniel Chalk
In this session we explore the process of sentiment analysis with neural networks, making use of TensorFlow and the Keras API to attempt to classify whether text is positive or negative.
We look at how to process our raw text data ready for use in the process, train these models, and then save our trained model for use on unseen data.
This session makes use of the nlp_sa environment
Session lead: Dr Daniel Chalk
In this session, HSMAs worked in groups to tackle a question of their choosing on some data of their choosing using Natural Language Processing techniques, undertaking miniature projects and practicing those all-important skills needed to tackle their own projects in Phase 2.
The recording contains the brief for the day, as well as 10 presentations of project plans after the initial hour, and 10 presentations of project outputs at the end of the day.