Graduate Diploma in Business Analytics (University of London)

Course Information

Course Type
Full-time
Fees (Local Students)
S$12,640
Fees (Foreign Students)
S$13,030
Other Fees
Application Fee: S$97.20 (local) / Application and International Student Induction Fee: S$918.00
Duration
1 year
Intake Months
Visit course webpage for intake months
Programme Grant
Visit course website for Scholarships & Bursaries
Class Schedule
Information not provided by school.
Assessment Method
Coursework and 2-hour examinations.

Description

Awarded by University of London, UK and Developed by the Member Institution, London School of Economics and Political Science, UK.

This programme discusses statistical software and methods, their merits and limitations. It trains students to perform independent data analysis for managerial decision-making. The focus is on empirical analysis.

It also provides students with the knowledge to build quantitative models to analyse business programme; teaches students the practical skills of applied data analysis to make recommendations.

Entry Requirements

  • A first degree completed in a minimum of three years on a full-time basis (or equivalent) from a university or other institution acceptable to the University of London.

University of London graduates from the same range of degrees under the academic direction of LSE may be considered for the Graduate Diploma on a case to case basis.

Note: Although it is not a formal requirement, students are advised to select the management based course option as opposed to the mathematical based if you do not come from a strong quantitative background.

Equivalent International Qualifications

For information on international qualifications, refer to SIM’s International Student Prospectus.

English Language Requirements

  • You must have a minimum Grade C6 and above in GCE 'O' Level English language examinations or an equivalent qualification to apply to the University of London.

Mathematics Requirements

  • Proof of competence in Mathematics at least equivalent to a pass at GCSE/GCE O Level in a Mathematical subject at Grade C or above.

Career Opportunities

As the world becomes ever more data-driven, many companies are exploiting quantitative techniques for their businesses. Graduates of this programme will be highly sought after by the employers as the race to gain a competitive edge in the data arena intensifies. 

Graduates of this programmes may progress to further postgraduate studies in this field, either locally or overseas. 

Modules

Structure

  • Blended lectures, group discussions, workshops and online study. 
  • Duration of each lesson is 3 hours. 
  • Students will attend classes with those pursuing a Bachelor’s programme at SIM campus. 
  • Classes are taught by local faculty, supplemented by webinars by the London School of Economics on the Virtual Learning Environment. 
  • Academic materials include Virtual Learning Environment, SIMConnect portal, subject guides, past exam papers and exam commentaries, reading lists and handbooks on good study strategies. 
  • Learning support include intensive revision, classes on study skills, academic writing and the Peer-Assisted Learning sessions. 
  • Full time classes are held in three-hour blocks between Monday and Friday, starting at 8.30am, 12pm, or 3.30pm. There are occasional classes on weeknights at 7pm and weekends. 
  • Average teacher-student ratio: 1:79 
  • Minimum class size to commence is 25 students. Students will be informed within 30 days after the application period. 

Assessment & Attendance

  • Assessment for ST2187 and ST3188 is a mixture of coursework and 2-hour examinations.
  • Attendance and Coursework are part of the University's requirements to sit for the examinations every May/June. SIM students may take resits in the Oct/Nov sitting.
  • Students may have a maximum of 3 attempts for each paper prior to classification.
  • Key dates:
    • SIM Preliminary Exams: Feb 2024
    • University Exams: May – Jun 2024
    • Results released: Mid-Aug 2024
  • Attendance requirement:
    • Local: 75%
    • International (Student Pass / Dependent Pass / Long-term Visit Pass): 90%

Modules

The programme is made up of 4 full modules. There are no prerequisites or exemptions for each module.

Compulsory modules

  • ST2187 Business analytics, applied modelling and prediction
  • ST3188 Statistical methods for market research

AND

One full module (or two half modules) from:

Selection groups M or N, and may also include EC2020 Elements of econometrics

Locations

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