Topic outline

  • General


    • MODULE OVERVIEW


      A very warm welcome to the Capstone Project 1 Moodle site.  Here you will find all the pertinent information you need to start and support your capstone project journey.  To start with, make sure you have successfully completed (and passed) the RMCP module and elicit feedback from your supervisor concerning your RMCP proposal.  This is your starting point and will form the basis of what will go on to become the Capstone Project 1 report - that it unless you plan to change your topic altogether and start over.  You should already be aware of your assigned supervisor, its the same person assigned to you during RMCP.  In the (very) unlikely event that you were not assigned a supervisor or if you have forgotten you can contact the Project Manager, Dr Se Yong via Teams or email.

      Let's start off by running through the module's synopsis and learning outcomes:

      Module Synopsis

      The capstone project is the culmination of the student's journey through the MSc DSBA programme and provides an opportunity to demonstrate the skills and knowledge gained. Part 1 of the capstone project focuses primary on the scoping, design and planning of the project,requiring appropriately scope of the project topic. Students are expected to conduct a thorough critical appraisal of extent literature, analysing appropriate models and their performance, as well as explain and justify their planned methodology. Assessment of the capstone project 1 is facilitated through an oral defence of the intended project in addition to a report. Upon successful completion of this phase students continue on to capstone project part 2, applying their stated methodology and deliver their stated artefact/model with appropriate validation.

      Module Learning Outcomes

      1. Conceive a real-world research problem solvable through a data science based intervention (C2, PLO1)
      2. Appraise potential models, methods and approaches through a critical review of extant literature (A4, PLO5)
      3. Propose a model with real-world applicability which addresses the stated problem (A5, PLO9)
      4. Formulate a robust methodology capable of withstanding close scrutiny .(A4, PLO8)
      5. Defend the applicability of the proposed research to address a real-world problem (A4, PLO10)

  • Project Briefing


    • Overview

      As you've probably gathered from the module synopsis and learning outcomes, this module is all about you!  Its your opportunity to demonstrate your knowledge, understanding, capability and technical competence, not to mention creativity and critical thinking by independently carrying out a data science project to completion.  Don't worry, you're not totally alone!  Your supervisor is here to guide and support you, and the information within this site should help you get off to a good start.  With this in mind, here are our learning outcomes for this module introduction:

      1. Describe the requirements and criteria for Capstone Project 1
      2. Explain the Capstone Project 1 assessment process
      3. Determine whether a project/dataset requires fast-track or full ethical approval


    • Discussion Forum

      Please discuss the project briefing here

  • Supplementary Material