2 August 2019
Data Mining and Text Analytics
Big data is becoming more and more important in fields from science to marketing, engineering, medicine and government. This module introduces the principles of data mining and text analytics. You will apply these principles in practical exercises with a data mining toolkit and real data. You will compare a range of different techniques and algorithms and evaluate their performance.
The module introduces:
- data mining inputs and outputs, instances, attributes, classes, concepts
- machine learning and data mining with the WEKA toolkit
- real-world data-sets and competitions with Kaggle.com
- CRISP-DM Cross Industry Standard Process for Data Mining
- evaluation of data mining and text analytics results
- text classification
- text search and information retrieval
You will take part in practical team work as part of a data mining and text analytics challenge. You are not expected to have previous expertise in data mining but you should be familiar with using and creating data files. For example, Word documents, Excel spreadsheets, PowerPoint presentations, YouTube videos, Wikipedia web-pages, Twitter/Facebook or other social media data. Please note you are expected to use your own laptop for this module.
You will learn the principles of data mining and text analytics; apply these principles in practical exercises with a data mining toolkit and real data; compare a range of different techniques and algorithms and evaluate their performance.
The module is worth 10 Leeds credits = 5 ECTS. You can transfer the credits earned back to your home degree subject to approval.
GBP 1770: Includes tuition, accommodation, breakfast and lunch, Monday - Friday, academic field trip, weekend cultural excursions, social programme and premium gym membership.
Santander scholarships worth £500 are available for students with good academic standing to help pay your fees. You can apply as part of your application to LISS.