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Data Mining
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This module will introduce students to concepts of business intelligence, machine learning and data mining techniques typically used in business applications.

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Module Study Guide

1.1Introduction, aims and summary of content

This module will introduce students to concepts of business intelligence, machine learning and data mining techniques typically used in business applications. Students will develop a toolbox of quantitative analytical techniques and skills from which to construct solutions for various business scenarios. They will appreciate the various complexities arising from business requirements and limitations to data mining techniques.

Content of the module includes:

Data warehousing (star schema, DW architectures, ETL)

  • introduction to Machine Learning and Data Mining (application examples, data mining and knowledge discovery) CRISP_DM

  • Input data preparation (pre-processing, cleaning, transformation, visualisation, exploration)

  • Supervised and unsupervised learning

  • Clustering, Classification, Regression, Association Rules

  • Data Mining in practice (text/web mining, recommendation systems, marketing customer modelling), analysis and exploration of data

  • Big Data – introduction to Big Data, Map-Reduce/Hadoop, Unstructured Data, noSQL databases, Applying Map-Reduce Technique

1.2  Learning outcomes to be assessed

On successful completion of this module students will be able to:

  1. Develop a systematic understanding of common machine learning and data mining techniques used to manipulate data;

  2. Critically evaluate, select and deploy appropriate techniques to develop BI applications for a range of purposes;

  3. Demonstrate an appreciation of current limitations of various tools used to manipulate data when developing data-intensive business applications;

  4. Critically evaluate Big Data technologies and develop business solutions using appropriate Big Data tools;

1.3 Scheduled contact hours

Teaching Contact Hours

48 hours

Independent Study Hours

152 hours

Total Learning Hours

200 hours

 

2.1 Summative assessment grid

Type of Assessment

Word Count or equivalent

Threshold

(if Professional Body-PSRB applies)

Weighting

Pass Mark

Submission due-date & time

Method of Submission & Date of Feedback

Portfolio

n/a

n/a

100%

40%

23:59pm Thursday 19thth December

Online

Feedback within 2 weeks

 

 

 

 

 

 

 

2.2 Assessment brief including criteria mapped to learning outcomes

The assessment consists of weekly seminar tasks and a group presentation, as outlined below.

Full details of each task will be provided at the start of each seminar session.  You will be required to create a portfolio of all practical session exercises which you will be assessed on. The purpose of the portfolio is to show a systematic approach to documenting your work so that you or someone else could easily refer to at a later date, when you are putting together the materials for your group presentation. Ideally, each exercise should be completed by the end of the seminar session, but at the very latest by the end of the week in which it is introduced. In some cases the seminar task may consist of an online test which will be run during the seminar.

Seminar Tasks:

 

Criteria

Issues

Mark

Learning Outcomes

Content

Clear understanding and analysis of the problem/issue.  (80 total)

 

Tasks demonstrate overall understanding of BI/DM fundamentals and key concepts.

 

Are your answers comprehensive, covering all tasks?

 

Have extra examples have been given to help illustrate key concepts/issues?

 

30

 

30

 

20

LO 1

LO2

LO3

LO 4

Evaluation and synthesis

Is the portfolio neat and structured in a way that easy to follow?  Is it presented in a consistent manner?

20

 

Students will work in groups of 4 to produce a presentation evaluating data mining employed within a specific industry sector to showcase their understanding of the subject matter covered in the module. The presentation should aim to provide an overview of the ‘state of the art’ in the given sector and should refer to a range of case studies and specific technologies and techniques currently used, with projections for the future. The presentation will be delivered in class and should be 20 minutes long, followed by 5 minutes for questions from the audience. All members of the group must be present and must take part in the presentation in order to get marks for this element.

Note that your presentation may be recorded. It should be supported by detailed presentation notes containing any extra background information that will allow colleagues who have not seen your presentation to understand the content.Marks will be reduced for any presentation that is significantly shorter or longer than the required 20 minutes.A peer assessment exercise will also be conducted and individual marks may be moderated as a result.

Group Presentation Marking Criteria:

 

Criteria

Issues

Mark

Learning Outcomes

Knowledge and understanding of BI and DM techniques

Does your presentation demonstrate knowledge and understanding of a range of BI and DM techniques and technologies?

 

Are all team members able to answer questions on the materials presented?

15

 

 

LO 1

LO2

LO3

LO 4

Evaluation and synthesis

Does your presentation evaluate a range of DM case studies and effectively synthesise findings for the chosen sector? Does it provide a clear picture of what is currently being achieved and indication of future trends?

20

Group work, delivery &  presentation

Is the presentation professionally delivered, timely, include all team members, well paced and with professional looking slides supported by comprehensive notes?

Is there documented evidence of effective team work?

5

 

5

Research and use of sources

Is there evidence of appropriate research; are sources referenced correctly using Harvard referencing?

5

3.1 Attendance

Attendance is crucial for your success as a student. Over the years, it has become clear that there is a very clear link between students’ attendance levels and their module marks, so please make sure you give yourself the best possible chances for success through attending your classes, seminars and tutorials. You are expected to attend all forms of learning activity associated with your course of study regularly, and to engage in your course as required by the University’s Attendance and Engagement Monitoring Policy. Attendance is monitored using student-card swipe data so please always remember to ‘touch-in’ with your ID card for each class you attend. This may also affect your scholarships, so don’t forget to tap in!

International students on a Tier-4 visa have additional requirements in relation to attendance, which are detailed in the Attendance and Engagement Monitoring Policy.

3.2 If things don’t go to plan

The University recognises that there are times when you may encounter difficulties during your course of study and provisions are made to help you. In all cases, you should speak to your Personal Tutor/Module Leader and seek advice as soon as possible.

If you think you need a little more time past the original deadline, you can approach your Module Leader for a 10-day extension initially.

If you fall below the pass mark or fail to submit to all elements or part of a module’s assessments, you will be required to do a resit, normally at the next opportunity. Resits do not involve re-enrolment and attendance at classes.

Failure of a resit means you are required to retake the module. Retakes involve re-enrolment, attendance, payment of tuition fee and completion of all elements of the module, and the submission of all assessments. If your course is accredited by a Professional, Statutory and Regulatory Body (PSRB) certain rules may apply to you; please check this with your Course/Module Leader.

You are reminded that the University applies penalties to students who commit an academic offence, in which case the Academic Offences Regulations will be used to deal with any cases of academic misconduct including examination offences, plagiarism and other means of cheating to obtain an advantage.

If you have an issue or complaint about the module, you should speak to your Module Leader, Tutor or Course Leader informally in the first instance. Your Course Representative can also raise your concerns at Course Committees, which take place each semester. If you are unable to resolve it informally, you should refer to the Complaints Procedure which is outlined in the Student Handbook and consult the Students’ Union about it. The University aims to ensure that issues are resolved informally as quickly as possible to have minimum impact on your studies.

3.3Getting support for your studies

Throughout your course of study, you will have access to a wide variety of sources of support depending on your individual circumstances and needs. Your first point of call for getting general academic support is your Personal Tutor. As well as approaching your Module Leader with any questions specifically related to your module and your Course Leader with questions on your Course, do contact your Personal Tutor for academic advice in relation your studies and your academic development.

Apart from the University-wide support framework, which encompasses the Module Leaders, Course Leader, the Subject Librarian and your Course Administrator, you will also have at your disposal the UWL Engagement Team. The Engagement Team offers Academic Skills Workshops throughout the year, helping you to develop skills relevant to your degree. Workshops include for instance Essay Planning and Writing; Critical Thinking; Reflective Writing; Group Work and Presentation Skills

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