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MSc Data Science

MSc Data Science

MSc Data Science

Centres

MSc- Advanced Professional Practice

£770.00

Description

This module is only available for students enrolled on to MSc Data Science.

Please note this is a 60 credit module which has been broken down into 3 payments. This is the 1st payment only, you will need to make a subsequent payment next trimester, and again the following trimester. If you would prefer to purchase this module in full (£2310) please contact globalonlinesupport@napier.ac.uk

This module allows you to develop specialist computing skills in your workplace. You will negotiate, with your line manager and a mentor, a learning agreement which will identify objectives. The objectives you identify, once agreed, will form the basis for a significant piece of work which will be based on a live workplace issue. This module is designed to develop critical reflective practice, specialist computing skills, and act as a focus for your continuous professional development.
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Centres

MSc - Dissertation Data Science

£1540.00

Description

This module is NOT available unless you have successfully completed 120 Credits.
MSc Dissertation

SCQF level 11, 60 credits.

The work for this module comprises the completion of an individual research project. Each student is assigned a personal Supervisor, and an Internal Examiner who monitors progress and feedback, inputs advice, examines the dissertation and takes the lead at the viva.

There are three preliminary deliverables prior to the submission of the final dissertation:

(1) Project proposal
(2) Initial Report including time plan and dissertation outline
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Centres

MSc - Data Wrangling

£770.00

Description

This module is only available for students enrolled on to MSc Data Science.


The challenges of contemporary data acquisition and analysis have been characterised as “the four V’s of Big Data” (volume, variety, velocity and validity). These require the use of specialised data storage, aggregation and processing techniques. This module introduces a range of tools and techniques necessary for working with data in a variety of formats with a view to developing data driven applications. The module focuses primarily on developing applications using the Python scripting language and associated libraries and will also introduce a range of associated data storage and processing technologies and techniques.

The module covers the following topics:

• Data types and formats: numerical and time series, graph, textual, unstructured,
• Data sources and interfaces: open data, APIs, social media, web-based
• NoSQL databases such as document (MongoDB), graph and key value pair
• Techniques for dealing with large data sets, including Map Reduce
• Developing Data Driven Applications in Python

The Benchmark Statement for Computing specifies the range of skills and knowledge that should be incorporated in computing courses. This module encompasses cognitive skills in Computational Thinking, Modelling and Methods and Tools, Requirements Analysis and practical skills in specification, development and testing and the deployment and use of tools and critical evaluation in addition to providing useful generic skills for employment.
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