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ECMM443 - Introduction to Data Science (2023)
MODULE TITLE | Introduction to Data Science | CREDIT VALUE | 15 |
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MODULE CODE | ECMM443 | MODULE CONVENER | Dr Rudy Arthur (Coordinator) |
DURATION: TERM | 1 | 2 | 3 |
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DURATION: WEEKS | 11 |
Number of Students Taking Module (anticipated) | 30 |
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In this module, you will learn about the broad and fast-moving field of data science. You will be introduced to the core competencies and application areas associated with data science, including data handling and visualisation, machine learning, statistical modelling, social network analysis, text mining. You will also explore the ways in which data science is transforming business and society, and learn about ethical and governance aspects of data science. Practical exercises, individual study and group work will consolidate your learning and provide the foundations for later study.
Scheduled Learning & Teaching Activities | 36.00 | Guided Independent Study | 114.00 | Placement / Study Abroad | 0.00 |
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Category | Hours of study time | Description |
Scheduled Learning and Teaching | 36 | Lectures, Practicals, Seminars |
Guided Independent Study | 51 | Coursework |
Guided Independent Study | 63 | Self-study and Background Reading |
Form of Assessment | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
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Feedback on practical work | 18 hours | All | Oral |
Feedback in seminar discussions | 6 hours | All | Oral |
Coursework | 60 | Written Exams | 0 | Practical Exams | 40 |
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Form of Assessment | % of Credit | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
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Coursework | 60 | Report and presentation | 1,2,3,4,5,6,7,8,9,10 | Written |
Class Test | 40 | 1 hour | 2,4,5,6,7,8 | Written |
Original Form of Assessment | Form of Re-assessment | ILOs Re-assessed | Time Scale for Re-assessment |
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Coursework | Report and presentation | 1,2,3,4,5,6,7,8,9,10 | Summer reassessment period with an August deadline |
Class test | Class test, 1 hour | 2,4,5,6,7,8 | Summer reassessment period with an August deadline |
Reassessment will be by coursework and/or test in the failed or deferred element only. For referred candidates, the module mark will be capped at 50%. For deferred candidates, the module mark will be uncapped.
information that you are expected to consult. Further guidance will be provided by the Module Convener
Basic reading:
ELE: http://vle.exeter.ac.uk/
Web based and Electronic Resources:
Other Resources:
Reading list for this module:
Type | Author | Title | Edition | Publisher | Year | ISBN | Search |
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Set | Downey, A.B. | Think Stats. | O'Reilly Media. | 2014 | [Library] | ||
Set | Mayer-Schonberger V. & Cukier K. | Big data: a revolution that will transform how we live work and | John Murray | 2013 | [Library] | ||
Set | Marr, B. | Big Data in Practice | Wiley | 2016 | [Library] | ||
Set | Downey, A.B. | Think Python | Green Tea Press/O'Reilly | 2015 | [Library] | ||
Set | Schutt, R. and O’Neill, C. | Doing Data Science: Straight Talk from the Frontline | O'Reilly | 2014 | [Library] |
CREDIT VALUE | 15 | ECTS VALUE | 7.5 |
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PRE-REQUISITE MODULES | None |
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CO-REQUISITE MODULES | None |
NQF LEVEL (FHEQ) | 7 | AVAILABLE AS DISTANCE LEARNING | No |
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ORIGIN DATE | Tuesday 10 July 2018 | LAST REVISION DATE | Wednesday 18 January 2023 |
KEY WORDS SEARCH | data science, machine learning, statistics, data governance, data visualisation, data exploration, social networks, text analysis |
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