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2021/22 Undergraduate Module Catalogue

COMP2121 Data Mining

10 creditsClass Size: 200

Module manager: Prof Eric Atwell
Email: e.s.atwell@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2021/22

Pre-requisites

COMP1121Databases

This module is not approved as a discovery module

Module summary

This module explores the knowledge discovery process and its application in different domains such as text and web mining. You will learn the principles of data mining; compare a range of different techniques and algorithms and learn how to evaluate their performance.

Objectives

On completion of this module, students should be able to:
-Identify all of the data, information, and knowledge elements, for a computational science application.
-understand the components of the knowledge discovery process
-understand and use algorithms, resources and techniques for implementing data mining systems;
-understand techniques for evaluating different methodologies
-demonstrate familiarity with some of the main application areas;
-demonstrate familiarity with data mining and text analytics tools.

Learning outcomes
On completion of this module, students should be able to:
understand data mining terminology and components of the data mining process; Data warehouses; Tools and techniques for data cleansing and aggregation; Use of machine learning classifiers for data classification; Meta data; Use of clustering and association tools for data mining; Open-source and commercial text mining and text analytics toolkits; Web-based text analytics; Case studies of current commercial applications.


Syllabus

Introduction to data mining terminology and components of the data mining process. Data warehouses; Tools and techniques for data cleansing and aggregation. Use of machine learning classifiers for data classification. Meta data. Use of clustering and association tools for data mining. Open-source and commercial text mining and text analytics toolkits. Web-based text analytics. Case studies of current commercial applications.

Teaching methods

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

Delivery typeNumberLength hoursStudent hours
Laboratory121.0012.00
Class tests, exams and assessment22.004.00
Lecture81.008.00
Private study hours76.00
Total Contact hours24.00
Total hours (100hr per 10 credits)100.00

Opportunities for Formative Feedback

Coursework and labs.

Methods of assessment

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information


Coursework
Assessment typeNotes% of formal assessment
Online AssessmentMid-term Test1, end-of-term Test 240.00
AssignmentLab based60.00
Total percentage (Assessment Coursework)100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 28/07/2021 13:59:13

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