Module Details
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title Big Data Group Project
Code COMP530
Coordinator Dr MK Bane
Computer Science
M.K.Bane@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2019-20 Level 7 FHEQ Second Semester 15

Aims

To provide experience of working and collaborating in a software development team (in the context of HPC and Big Data).
To provide experience of all aspects of the declopment of a HPC solution to a Big Data problem.
To prepare students for their individual end of programme project (COMP702).
To consolidate material from the first semester, specifically material from COMP528 and COMP529.


Learning Outcomes

(LO1) An in depth and critical understanding of the operation of software development teams, the interpersonal skills required and the issues involved in working as part of a team.

(LO2) Knowledge of how to specify and design HPC solutions to Big Data problems.

(LO3) Knowledge of how to implement and test HPC solutions to Big Data problems.

(LO4) An overall understanding of the process of developing HPC solutions to Big Data problems.

(LO5) An ability to demonstrate practical experience in the realisation of HPC solutions to Big Data problems.

(LO6) A critical understanding of the importance of software documentation and its creation.

(S2) Communication (oral, written and visual) - Presentation skills - written

(S3) Time and project management - Project planning

(S4) Critical thinking and problem solving - Critical analysis

(S5) Working in groups and teams - Group action planning

(S6) Working in groups and teams - Time management

(S7) Commercial awareness - Relevant understanding of organisations

Syllabus
 

6 lectures will be given:  
Introduction to the project framework
Overview of available projects
Meeting skills and project planning
Requirements and design specification
Group dynamics and negotiation
Quality and configuration management; document testing; report writing.

Teaching and Learning Strategies

Teaching Method 1 - Lecture
Description:
Attendance Recorded: Not yet decided
Notes: Introductory lectures on the operation of group project module and material on the practical solution to Big Data and HPC problems.

Teaching Method 2 - Tutorial
Description:
Attendance Recorded: Not yet decided
Notes: Project reviews; project surgeries

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 6

   8

       14
Timetable (if known)              
Private Study 136
TOTAL HOURS 150

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
             
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Project Portfolio There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :2  Project portfolio    60       
Demonstration/Presentation of Results Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :2  System demonstration    20       
Specification and Proposed Design Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :2  Requirement specific    20       

Recommended Texts
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.