Assignment Task
Module Learning Outcomes Students will typically…
1. possess deep knowledge of data science algorithms and applications,
2. be able to plan and carry out a data science campaign,
3. be able to find and retrieve data from public sources,
4. master methods for pre-processing and cleaning data,
5. have an understanding of data visualisation principles and apply them in practice,
6. be able to extend their knowledge using publicly available resources,
7. be able to summarize the outcome of a data science campaign
Please note:
• Late submission of coursework will typically attract a lateness penalty. For each day or part thereof for up to five days after the published deadline, coursework submitted late (including deferred coursework, but with the exception of referred coursework), will have the numeric grade reduced by 10 grade points until or unless the numeric grade reaches or is a bare pass (i.e. 40 for undergraduate modules, 50 for postgraduate modules). Where the numeric grade awarded for the assessment is less than the bare pass, no lateness penalty will be applied.
• Late submission of online timed assessments typically will not be accepted.
• Coursework (including deferred coursework) submitted later than five days (five working days in the case of hard copy submission) after the published deadline will be awarded a grade of zero (0).
• Late submission of referred coursework will automatically be awarded a mark of zero.
• You are strongly advised to submit your work one hour before the submission deadline, to give time to resolve difficulties. The application of lateness penalty is automated and therefore any submission after the deadline will attract a lateness penalty
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