COM2013 - Data Science Group Project 2 (2023)

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MODULE TITLEData Science Group Project 2 CREDIT VALUE15
MODULE CODECOM2013 MODULE CONVENERUnknown
DURATION: TERM 1 2 3
DURATION: WEEKS 0 11 0
Number of Students Taking Module (anticipated) 30
DESCRIPTION - summary of the module content

This module gives you further practical experience of real data science projects and an opportunity to apply the techniques you have learned in other modules to solve a real, complicated and messy data science problem. In a team, you will help define and specify a data science problem, understand the client’s requirements and the available data sources. Your team, guided by a supervisor, will then use methods from other modules and new techniques to solve the problem and report your findings. An important aspect of the project will be coping with the common problem of missing and erroneous data.

AIMS - intentions of the module

This module aims to equip you to work on practical data science projects from start to finish: understanding the problem, selecting data and methods to solve it, wrangling the data, dealing with missing and erroneous data and reporting your results. It also aims to develop your soft skills in the areas of problem definition and presentation skills.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

On successful completion of this module, you should be able to:

Module Specific Skills and Knowledge:

1 Capture requirements from an external “customer”;

2 ”Wrangle” data into a form suitable for machine learning algorithms;

3 Understand mechanisms of missing data and be able to compensate appropriately;

4 Select and apply suitable machine learning algorithms;

Discipline Specific Skills and Knowledge:

5 Choose and use an appropriate research and development process;

6 Read and understand new technical methods;

7 Work as a member of a research and development team, participating in self-evaluation and peer review;

Personal and Key Transferable / Employment Skills and Knowledge:

8 Understand and apply legal, social and ethical principles;

9 Present your work to specialist and non-specialist audiences;

10 Tackle a technical problem in a new area.

SYLLABUS PLAN - summary of the structure and academic content of the module
  • Students will work in teams, meeting their Supervisor weekly;
  • The initial weeks will include lectures on the following topics, as appropriate:
    • Introduction to the project;
    • Missing data mechanisms and methods to cope with it;
    • Technical material related to the project;
    • Presentation skills;
    • Writing effective reports.
LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 23.00 Guided Independent Study 127.00 Placement / Study Abroad 0.00
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category Hours of study time Description
Scheduled Learning and Teaching Activities 8 Introductory Lectures 
Scheduled Learning and Teaching Activities 12 Weekly Project Review Meetings
Scheduled Learning and Teaching Activities  3 Project Presentations
Guided Independent Study 127 Independent Study

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
Form of Assessment Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Not Applicable      

 

SUMMATIVE ASSESSMENT (% of credit)
Coursework 100 Written Exams 0 Practical Exams 0
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Presentation of project plan and preliminary data analysis 40 5-minute Pitch-Deck presentation  1,2,4-8 Written, using customised Marksheet
Coursework: Final Report 60 15-page group project + 3-page personal essay outlining individual work on data and evaluating project impact All Written, using customised Marksheet
         

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-assessment

Presentation of project plan

Pre-recorded presentation of project plan

1,2, 4-8

 August ref/def period
Final Report Final Report All August ref/def period

 

RE-ASSESSMENT NOTES

Reassessment will be by coursework in the failed or deferred element only. For referred candidates, the module mark will be capped at 40%. For deferred candidates, the module mark will be uncapped.

RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

Basic Reading:

ELE: http://vle.exeter.ac.uk/

 

Reading list for this module:

There are currently no reading list entries found for this module.

CREDIT VALUE 15 ECTS VALUE 7.5
PRE-REQUISITE MODULES COM1012
CO-REQUISITE MODULES
NQF LEVEL (FHEQ) 7 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Friday 12 April 2019 LAST REVISION DATE Monday 05 February 2024
KEY WORDS SEARCH Group Project; Data Science