BrightSpace : This module is now available on BrightSpace. Each student needs to self-enrol in the module. Search for ‘Data Mining DATA9900‘, and for my name. The module description will have my name.


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.

Important: The notes are living artifacts. I may make some minor changes to these. The videos are pre-recorded and may not reflect the current version of the notes.

*** Module Introduction & Admin – Notes

Assignment Q&As
Q: Can we use RapidMiner to process the data or for doing the modelling?
A: RapidMiner is not one of the languages or tools listed on the assignment document

Q: We were just wondering whether the assignment should be submitted by one of us on behalf of both of us or whether we each write up the report from our findings separately?
A: Only one submission is necessary. Make sure to clearly state the people who worked on the report.


Week of/begin
 Lecture Topic
16th Sept
No class. Classes start Week 2.
23rd Sept
 Introduction to Data Mining, Machine Learning and Data Science
30th Sept
 Data Mining / Data Science Life-cycle, Why it is different and the challenges
7th Oct
 Descriptive Analytics and Preparing Data
14th Oct
PT students – Exploring Text & Basics of Text Mining Virtual class, follow videos and exercises.

Zoom meeting for topic Q&A. Monday 14th Oct between 20:00-20:40   

FT students –  Association Rule Analysis

21st Oct
PT students – Association Rule Analysis

FT students – Exploring Text & Basics of Text Mining Virtual class, follow videos and exercises.

Zoom meeting for topic Q&A. Thursday 24th Oct, between 16:00-16:40.

28th Oct
Bank Holiday – No Class this week – Catchup week. Complete & Repeat Exercises.
Students should use this week to catch-up on all the lab exercises, repeating them to get a better understanding, and loading new data into the tool to explore.
4th Nov
11th Nov

 Assignment Handout – Groups of max. 2 people or individual.

18th Nov
 Finish Classification – see previous weeks notes

Data Clustering

25th Nov
Deployment issues — Notes are incomplete. Sill work-in-progress

Data Visualisation
Ensemble Models
Automated & Autonomous Data Science

Model Deployment

Other Data Mining/Data Science Project topics

2nd Dec
The EU GDPR and Machine Learning/Data ScienceVirtual Class. Videos, notes and reading are all online.

Work on Assignment.

9nd Dec
Work on Assignment – Assignment Due Monday 9th December @23:00
No Class – Use the class and lab time to work on completing your assignment. You can work from home
16th Dec
Assignment marking. I will endeavor to have assignments marked before Christmas.
Due to the short turn around time, this may not be possible, and results will be available in early January.Assignment feedback sessions. Monday 6th January 12:00-14:00

Locked Diagrams in SAS Enterprise Miner

*** The following is from SAS

In regards to the locked diagram, the fastest way to delete the lock typically is to log into SAS OnDemand for Academics Control Center. When a diagram is opened for editing, a lock file is put in place to indicate the diagram is being used. Sometimes, the lock file will remain even when the user is finished editing the diagram. As a result, the user will get an error in a pop-up window stating that “this diagram is currently locked”. To correct this problem, you should close the diagram if it is open. Then open SAS Studio from the SAS OnDemand for Academics Control Center. Open the “Server Files and Folders” tab. The lock file will generally be in this path:

 /home/(user name)/(project name)/Workspaces/EMWS1 (or similar)/System

 ****The “.lck” file I deleted was found at the following filepath in your Enterprise Miner project files in SAS Studio: /home/basquinsophonie0/Exam1/Workspaces/EMWS1/System

 If your diagram locks up on you again, you can head to that file location and delete the “.lck” file, which should allow you to open the diagram.****

 The lock file will have a name like “wsopen.lck”. (The lock file always has the extension “.lck”. )

 You can remove this file to enable editing of the diagram.

Past Exam Papers

Data Mining 2018-2019

Data Mining 2017-2018

Data Mining 2016-2017