AC53009 Data analysis and visualisation module spec 12-13x

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Oct 24, 2013 (3 years and 7 months ago)

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[ASQ10_Form_2]

School of Computing

Module Specification Form


Code





Module Title

Data analysis and visualisation




College

CASE




School

Computing




Credit rating

Level
SCH M

(SCQF 11)

Credits

20 SCQF credits

10 ECTS credits



Credits

20 SCQF

credits

10 ECTS credits

Aims

This module describes patterns in data, the importance of
statistics and data visualization. It aims to develop a
understanding of data generation and the common mistakes
made when analyzing this data.




Intended learning

outcomes

KNOWLEDGE and UNDERSTANDING






Explain

the
Importance of statistics





Discuss

a number of different

Data mining
techniques





Visualization of data

SKILLS





Select appropriate statistical techniques





Select data mining techniques





Be able to
create data mining algorithms





Select appropriate data visualistaions.




Indicative content

Patterns in data

Interaction of independent variables leading to normal distribution

Mean, mode & median

Continuous & discontinuous values

Categorical, Nominal &

Ordinal Interval

Standard Deviation & Variance

Populations & samples

Sampling

Random sampling

Statistical testing

Data mining

Data Mining vs. Querying

Methodology

Process

Application Areas

Techniques

Example Outputs

Result Validation

Solution Deployment

Cross Industry Standard Process for Data Mining (CRISP
-
DM).

Data mining classifications/descriptions

Decision Trees

Neural Networks

Nearest Neighbour and Clustering

Genetic Algorithms

Rule Induction

Segmentation

Classification

Value Prediction and
Regression




Association

Sequential Pattern Discovery

Similar Time Sequence Discovery

Delivering information

Visualisation of data & information

Importance of good interface design



Modes of delivery and
student participation

Students can study the
module on
-
campus for one week and
thereafter either on
-
campus or by online learning




Teaching, learning
and assessment

Coursework (%)

40

Exam (%)

60

Summative
assessment:

Coursework (%)

Examination (%, no. &
duration of exams)

Coursework: 40%

Exam: 60%




When taught

Summer




Pre
-
requisites or entry
requirements

60 credits Business Intelligence MSc




Corequisites

None




Antirequisites

None




Accessibility for
students with
disability

Students with disabilities are supported on this module
through the University's Disability Support Services
(
http://www.dundee.ac.uk/disabilitysupport/
) and will be
given appropriate aid and guidance consistent with their
disability.

A web site for students with disabilities in the School of
Computing is also available at
http://www.computing.dundee.ac.uk/staff/awaller/disability.a
sp




Further information

http://www.computing.dundee.ac.uk




Date of Approval





Applicability of
Module Specification

2012