Introduction

Goldsmiths’ Computing Department believes that the critical factor in the study is learning by doing and experimenting. Studying this Postgraduate Diploma, you will learn the mathematical foundations of statistics, data mining and machine learning, and apply these to practical, real world data.

As well as these statistical skills, you will learn the computational techniques needed to efficiently analyse very large data sets. You will apply these skills to a range of real world data, under the guidance of experts in that domain. You will analyse trends in social media, make financial predictions based on the data gathered.

The programme includes:

  • A firm grounding in the theory of data mining, statistics and machine learning
  • Hands-on practical real world applications such as social media, biomedical data and financial data with Hadoop (used by Yahoo!, Facebook, Google, Twitter, LinkedIn, IBM, Amazon, and many others), R and other specialised software
  • The opportunity to work with real-world software such as Apache
Programme Structure

The Postgraduate Diploma in Data Science is a 120 credit programme. A student must complete:

  • Four core modules (60 credits total)
  • Two compulsory modules (30 credits total)
  • Two optional modules (30 credits total)

CORE (must pass all assessment elements)

  • Big Data Analysis 15
  • Data Programming in Python 15
  • Mathematics and Statistics for Data Science 15
  • Machine Learning 15
  • COMPULSORY (subject to the *rules for compensation)
  • Data Science Research Topics 15
  • Data Visualisation 15

OPTIONAL (choose any two and subject to the *rules for compensation)

  • Artificial Intelligence 15
  • Blockchain Programming 15
  • Financial Data Modelling 15
  • Mathematics for Financial Markets 15
  • Natural Language Processing 15
  • Neural Networks 15
  • R for Data Science 15

Rules for Compensation
The university will allow compensation for an assessment element within optional and compulsory modules if:

  • the mark awarded for one of the assessment element is between 45%-49%; AND
  • the mark for the other assessment elements is sufficient to produce an overall combined weighted pass mark for the module

Note: the university will NOT allow compensation for any assessment element within core modules.

Admission Requirements

Entry Route 1
Applicants must have the following:

  • A full UK second class honour degree (or its equivalent) in a *relevant subject from an institution acceptable to the university of London; AND
  • GCE ‘O’ Level, min Grade C6 in English or its equivalent

The subjects that would be considered as relevant are: Computing, Data Science, Computer Science, Business Computing, Games Programming, Physics, Engineering, Mathematics and statistics, Finance, Marketing and Finance.

Entry Route 2
If applicants do not meet the above academic requirements, their applications may be considered based on the following

  • A full UK second class honour degree (or its equivalent) in a any subject from an institution acceptable to the university of London; AND
  • GCE ‘O’ Level, min Grade C6 in English or its equivalent; AND
  • *Complete and pass an online preparatory course, MOOC via Coursera platform. There is no entry test requirement for the MOOC course. However, there will be assessment during and at the end of MOOC course

*students should sign up with Coursera at least 3 months before the intended intake. Do aim to have the results at least one month before the application intake is close. While completing the MOOC course, student may submit an SIM application.

Dates & Fees

Dates
For more information on Application Dates, click here.

Fees
For more information on Fee, Scholarships and Finance matters, click here.

Contact Details

SIM Global Education
SIM HQ
461 Clementi Road
Singapore 599491

Tel: +65 6248 9746                               
Email: study@sim.edu.sg