Computer Science

COM1012 - Data Science Group Project 1 (2019)

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MODULE TITLEData Science Group Project 1 CREDIT VALUE15
MODULE CODECOM1012 MODULE CONVENERDr Leon Danon
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 introduces you to the practicalities of a real data science project. 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 part of the project will be aspects of “data wrangling” – understanding the data and getting it into a form suitable for machine learning algorithms.

AIMS - intentions of the module

This module aims to give you experience of working on a practical data science project in the round, understanding the problem, selecting data and methods to solve it, wrangling the 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 Understand data, particularly text, representations and encodings;

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

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;

• Data wrangling;

• 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 85 Written Exams 0 Practical Exams 15
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Coursework: Project plan, cost/benefit and data needs analyses 20 6 pages 1,2, 4-6, 8 Written using customised marksheet
Coursework: Final report 65 20 pages All Written using customised marksheet
Presentation and demonstration 15 20 minutes All Written using customised marksheet

Assessment of the final report will include an element of peer assessment, negotiated at the start of the project.

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
All above Coursework (100%) All Completed over summer with a deadline in August

 

RE-ASSESSMENT NOTES

Referred and deferred assessments will normally be by a single assignment together with a demonstration/viva.

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/

There is no standard reading list for this module.

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 COM1011
CO-REQUISITE MODULES
NQF LEVEL (FHEQ) 7 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Friday 12 April 2019 LAST REVISION DATE Friday 09 August 2019
KEY WORDS SEARCH Group Project; Data Science