Topic outline

  • General


    • MODULE OVERVIEW


      A very warm welcome to the Capstone Project 2 Moodle, if you're here then that means you have successfully completed CP1!  Well done.  The 2nd and final part of the capstone project requires you to put your plans into action and do exactly what you said you would do in CP1.   This means putting Chapter 3, Methodology, into practice and implementing your model.  As with CP1, this site provides guidance to help you achieve this end, although you must continue to liaise closely with your supervisor.

      Let's look at the CP2's module synopsis and learning outcomes:

      Module Synopsis

      The capstone project (CP) is the culmination of the student's journey through the MSc DSBA programme and provides an opportunity to demonstrate the skills and knowledge gained. Building on CP1, capstone project 2 requires students to put the proposed research and methodology into effect through the design and development of their intended solution (model). Students are expected to take full ownership of the data science process, from sourcing an appropriate dataset, preprocessing of said data, to the design and validation of their model. This also includes appropriate explorartory data analysis, as well as suitable visualisation for a non-technical audience.

      Module Learning Outcomes

      1. Initiate a data science methodology to address a set of stated objectives (C6, PLO2)
      2. Perform an exploratory investigation of an appropriate dataset (P4, PLO3)
      3. Verify the integrity of the dataset through appropriate preprocessing (A5, PLO6)
      4. Summarise the experimental results with different models to solve a data science related problem (C5, PLO7)
      5. Compare the models in terms of its suitability to address a data science problem (A4, PLO4)
      6. Propose the model to an audience of assessors in a professional manner (A5, PLO11)

  • Project Briefing