Students are reminded that notes provided on this site are intended to form summary material only and are not intended to be a substitute for attending lectures or further reading on the subject.

My slides are not Lecture Notes

Students should download the notes to your own device. The notes are a living artifact and will evolve from semester to semester. It cannot be guaranteed that the notes will be available after the end of a semester.

Important: You will need to perform additional reading and research (outside of class time) to complete the various lab exercises and to explore the topics covered in more detail.

*** Module Introduction & Admin – Notes

Week of/begin
 Lecture Topic
17th Sept
 Introduction to Data Mining, Machine Learning and Data Science
24th Sept
 Data Mining / Data Science Life-cycle, Why it is different and the challenges
1st Oct
 Descriptive Analytics and Preparing Data
8th Oct
 Exploring Text & Basics of Text Mining
15th Oct
 Association Rule Analysis

DT228A students.  There will be an online Q&A session on Friday 13:00-13:40.

I will be using Zoom for this online session. Check out this software and have installed in advance of the session.

Join from PC, Mac, Linux, iOS or Android:

22nd Oct
No Class this week. Catch up week

Self study, revision, complete all exercises, etc

29th Oct
5th Nov

 Assignment Handout

12th Nov
 Finish Classification – see previous weeks notes

Data Clustering

19th Nov
 The EU GDPR and Machine Learning/Data Science
26th Nov
Deployment issues
   Data Visualisation
Ensemble Models
Automated & Autonomous Data Science
Other Data Mining/Data Science Project topics
3rd Dec
Assignment Due at end of this week.

No Class – Use the class and lab time to work on completing your assignment. You can work from home

I will endeavor to have assignment marks and a short feedback comment entered into WebCourses before Christmas.

If you would like to schedule a face-to-face feedback session in early January, email me.

10th Dec
Study & Revision
No Class
Assignment marking and feedback (by end of this week or end of next week)

Past Exam Papers

Data Mining 2017-2018

Data Mining 2016-2017

Data Mining 2015-2016