Computer Science

ECMM433 - Project 1 (2019)

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MODULE TITLEProject 1 CREDIT VALUE30
MODULE CODEECMM433 MODULE CONVENERDr Lorenzo Livi (Coordinator)
DURATION: TERM 1 2 3
DURATION: WEEKS
Number of Students Taking Module (anticipated) 20
DESCRIPTION - summary of the module content

***DATA SCIENCE AND DATA SCIENCE WITH BUSINESS STUDENTS ONLY***

This module will allow you to apply the knowledge learned in other modules in a significant data science project. Projects will in most cases be based within your organisation, and where possible, related to your role at work; alternatively a suitable project topic can be selected from the range of previously taught modules. The module will develop your project planning, management and implementation skills as well as those in independent learning, presentation and writing. This will also be an opportunity to gain experience in the implementation of a data science project within your organisation and to develop your understanding of the business requirements of such projects.

Pre-requisites: None. This project has no specific pre-requisites, but is only offered as a part of the MSc Data Science (Professional).
Co-requisites: None

Note: This module is identical to ECMM435 Data Science Project 2.

This module is a core module for MSc Data Science students.

AIMS - intentions of the module

The module has several aims:

• To develop skills in project specification, planning and management
• To develop an understanding of appropriate data science tools to apply
• To consider the ethical issues associated with collecting, processing and analysing data
• To consolidate skills in the implementation of data science techniques
• To develop skills in the understanding and visualisation of the outputs of data science techniques
• To develop a greater understanding of where data science fits within the organisation
• To develop presentation and writing skills

Most work will be independent study, but you will be supported by a supervisory team through regular meetings and progress reports. The supervisory team will normally consist of a relevant academic faculty member from the MSc Data Science programme and a nominated individual at your employer organisation. The employer organisation will provide guidance on the business relevance of the project and together with the academic supervisor will identify project goals. Alternatively, you may choose an academic data science project based on previously taught module content. In this scenario, the supervisory team will consist solely of an academic supervisory from the MSc Data Science programme.

Work towards project goals will be carried out independently over a 4 month period, supported by regular supervision meetings conducted using online tools (e.g. video conferencing). A number of “project days” will bring all the cohort together on campus to present progress and hold meetings with academic supervisors. Interim and final presentations of project findings will form part of the project assessment, which will be completed with a substantial report.

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. Develop a business plan and specification for a data science project
2. Identify relevant datasets within the organisation
3. Identify and implement the relevant data science tools required
4. Implement appropriate visualisation techniques for data science outputs

Discipline Specific Skills and Knowledge

5. Plan and manage your own work effectively
6. Understand the costs and benefits of the project to the business
7. Communicate with others effectively

Personal and Key Transferable / Employment Skills and Knowledge

8. Work effectively to design and implement data science solutions to challenging business problems
9. Present effectively the work undertaken to a lay audience
10. Write a concise report describing the work involved in the project

 

SYLLABUS PLAN - summary of the structure and academic content of the module

Activities related to this module will include:
• Introduction to the module.
• Identification of suitable projects from within the student’s organisation or based on previous taught content.
• Creation of a project plan and specification with your supervisor team.
• Implementation of the project
• Presentation of progress updates to student and supervisor cohort.
• Meetings with academic supervisor (face-to-face and online).
• Final submission: a report and final presentation in the last week of the year.

LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 14.00 Guided Independent Study 286.00 Placement / Study Abroad 0.00
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category Hours of study time Description
Scheduled Learning Teaching Activities 2 Introductory session
Scheduled Learning Teaching Activities 8 Remote supervisory meetings
Scheduled Learning Teaching Activities 4 On site supervisory meetings
Guided Independent Learning 100 Project work
Guided Independent Learning 186 Background reading and private 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
Supervision meeting discussions 12 hours All Oral
       
       
       
       

 

SUMMATIVE ASSESSMENT (% of credit)
Coursework 0 Written Exams 0 Practical Exams 100
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Interim Presentation 10 15 minutes 7, 9 Oral
Final Presentation 20 25 minutes 1-9 Written
Final Report 70 15-20 pages 2-7, 10 Written

 

 

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
Interim Presentation Presentation 2-7, 10 Within 8 weeks
Final Presentation Presentation 7, 9 Within 8 weeks
Final Report Resubmitted final report 1-9 Within 8 weeks

 

RE-ASSESSMENT NOTES

Re-assessment will be conducted on a single presentation (30%) and final report (70%)

Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 50%) you will be required to re-take some or all parts of the assessment, as decided by the Module Convenor. The final mark given for a module where re-assessment was taken as a result of referral will be capped at 50%.

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

 

Web based and Electronic Resources:

 

Other Resources:

 

Reading list for this module:

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

CREDIT VALUE 30 ECTS VALUE 15
PRE-REQUISITE MODULES None
CO-REQUISITE MODULES None
NQF LEVEL (FHEQ) 7 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Thursday 06 July 2017 LAST REVISION DATE Tuesday 18 December 2018
KEY WORDS SEARCH Research project