Bachelor of Science (Honours) in Data Science and Business Analytics (University of London)

Standard Entry Requirements:

General Entrance Requirements (GER) are:

• Applicant must be 17 years or older by 30 November in the year of registration with UOL 
• This degree is recommended only if you have scored well in Mathematics at GCE ‘A’ level or the equivalent. 
• Two approved GCE ‘A’ /H2 level subjects and three approved GCE ‘O’ level subjects, OR 
• Three approved GCE ‘A’ /H2 level subjects and one approved GCE ‘O’ level subject, OR 
• Three H2 passes provided that at least grades D, E, E are obtained, OR 
• Two H2 and two H1 passes provided they are in non-overlapping subjects, OR
• Its equivalent 

The following qualifications^ meet GER for admission into Year 1: 

• Diploma in Accounting, Banking and Finance, International Business and Management Studies awarded by SIM** 
• Diplomas awarded by Nanyang Polytechnic, Ngee Ann Polytechnic, Republic Polytechnic, Singapore Polytechnic or Temasek Polytechnic

^ All listings are not exhaustive and they are subject to annual revision. 

** SIM Diploma graduates are required to take up the SIM Bridging Course for Mathematics and pass the examination (40% to pass) before enrolment. 

Equivalent International Qualifications

• University of London International Foundation Certificate with Merit passes in Mathematics and Statistics 
• University of London Certificate of Higher Education in Social Sciences

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

International students who wish to pursue the BSc Data Science and Business Analytics degree programme are strongly encouraged to apply for the Certificate of Higher Education in Social Sciences (CHESS) (see Option D), as this qualification is equivalent to the first year of the BSc degree programme. After one year of studies in the CHESS (Option D), candidates will articulate into Year 2 of the BSc Data Science and Business Analytics. 

English Language Requirements

• GCE ‘O’ level - C6 or better in English 

Alternatively, candidates should have one of the following qualifications: 

• Cambridge Certificate of Proficiency in English, OR 
• Cambridge English Language 1119 (at grade 6 or better) conducted by University of Cambridge Local Examinations Syndicate OR IGCSE English as a 2nd Language, passed at grade B or above, OR 
• IB Diploma - English at grade 4 or better 

Candidates may also take a Test of Proficiency to meet the English Language course requirement, provided they have been awarded within the past three years. 

• TOEFL - a score of 580 (computerised - 237) plus TWE - 4.5, OR 
• Internet based TOEFL - a score of 87, at least 21 in both the reading and writing skills sub-tests, and at least 19 in both the speaking and listening skills sub-tests, OR 
• IELTS – overall score of at least 6 with a minimum of 5.5 in each of the four sub-tests 

Mathematics Requirements

• GCE ‘A’ Level Maths passed at A - E grade (or its equivalent)
• Local polytechnic diploma in Engineering, Science, Business Information Systems, Information Systems or Computing PLUS grade B or better for ‘O’ Level E Maths and A Maths 
• Local polytechnic diploma with 2 acceptable Maths at grade B or better PLUS grade B or better for ‘O’ Level Elementary Maths and Additional Maths. Acceptable Maths includes the polytechnic modules in Mathematics, Engineering Mathematics, Statistics, Business Statistics and Calculus 
• Malaysia STPM Maths passed at A – C grade (Grade A - E pre 2003) 
• IB Diploma (Mathematics at Higher Level grade 4 or better, or Standard Level grade 5 or better) 
• UEC Maths and Advanced Maths at minimum A2 grade  
• UEC Advanced Maths I and Advanced Maths II at minimum C7 grade 
• NUS High School upon successful completion 
• IFP upon successful completion (Maths & Statistics passes at Merit or above) 
• Pass Mathematics in the SIM Bridging Course for Economics, Mathematics and Accounting (EMA)

Information not available

Structure

• Blended lectures, group discussions, workshops and online study. 
• Duration of each lesson is 3 hours. 
• 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. 
• Minimum class size to commence is 25 students. Students will be informed within 30 days after the application period. 
• 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 
• Visit course webpage to view sample of full-time class schedule

Assessment & Attendance

• Assessment by the University is made up of examinations and coursework (for selected modules).  
• 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.
• A pass or exemption from at least two Level 100 modules is required before they attempt Level 200/300 modules. 
• 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 (Dependent Pass holders/ Long-term Visit Pass holders): 90% 

Modules

Standard Entry Route

100 modules

• # EC1002 Introduction to economics 
• MT1186 Mathematical methods 
• MN1178 Business and management in a global context 
• ST1215 Introduction to mathematical statistics, or
• ST104A Statistics 1 (half module) and **ST104B Statistics 2 (half module)

200 and 300 modules

• ST2195 Programming for data science 
• ST2187 Business analytics, applied modelling and prediction (ST104A) or (ST1215) + (MT1174 or MT1186) 
• ST2133 Advanced statistics: distribution theory (half module) (ST104A + ST104B) or (ST1215) + (MT1174 or MT1186) and ST2134 Advanced statistics: statistical inference (half module) (ST104A + ST104B) or (ST1215) + (MT1174 or MT1186) 
• ^EC2020 Elements of econometrics (EC1002) + (ST104A) or (ST1215) + (MT1186), or
• • MT2116 Abstract mathematics (MT1186), or
  • IS2184 Information systems management 
• ST3188 Statistical methods for market research (ST104A) or (ST1215)
• ST3189 Machine learning (ST104A + ST104B) or (ST1215) + (MT1174 or MT1186) 
• One 300 module from Selection groups E, M or N 
• * One 100, 200 or 300 module (or two half modules) chosen from any Selection group

# EC1002 Introduction to economics must be taken after or at the same time as MT1186 Mathematical methods and ST104A Statistics 1 

* RPL awarded from one named or unnamed 100 module can be placed here. 

** ST104B Statistics 2 must be taken after or at the same time as ST104A Statistics 1 

^ EC2020 Elements of econometrics can only be taken at the same time as or after ST104B Statistics 2 and MT105B Mathematics 2, not before. You will also need to have passed the prerequisites of EC1002 Introduction to economics, MT105A Mathematics 1 and ST104A Statistics 1. However, if you passed MT1186 Mathematical methods, you do not need to take MT105A Mathematics 1 or MT105B Mathematics 2, but must still meet the other prerequisites and co-requisites. 

Graduate Entry Route

100 modules

• ^EC1002 Introduction to economics 
• MT1186 Mathematical methods 
• ST1215 Introduction to mathematical statistics, or]
• • ST104A Statistics 1 (half module) and ^ST104B Statistics 2 (half module)

200 and 300 modules

• ST2195 Programming for data science 
• ST2187 Business analytics, applied modelling and prediction (ST104A) or (ST1215) + (MT1186) 
• ST2133 Advanced statistics: distribution theory (half module) (ST104A + ST104B) or (ST1215) + (MT1186) and ST2134 Advanced statistics: statistical inference (half module) (ST104A + ST104B) or (ST1215) + (MT1186) 
• OR:
• ^EC2020 Elements of econometrics (EC1002) + (ST104A) or (ST1215) + (MT1186), or 
• • MT2116 Abstract mathematics (MT1186), or 
  • IS2184 Information systems management 
• ST3188 Statistical methods for market research (ST104A) or (ST1215)
• ST3189 Machine learning (ST104A + ST104B) or (ST1215) + (MT1186)

# EC1002 Introduction to economics must be taken after or at the same time as MT1186 Mathematical methods and ST104A Statistics 1 

* RPL awarded from one named or unnamed 100 module can be placed here. 

** ST104B Statistics 2 must be taken after or at the same time as ST104A Statistics 1 

^ EC2020 Elements of econometrics can only be taken at the same time as or after ST104B Statistics 2 and MT105B Mathematics 2, not before. You will also need to have passed the prerequisites of EC1002 Introduction to economics, MT105A Mathematics 1 and ST104A Statistics 1. However, if you passed MT1186 Mathematical methods, you do not need to take MT105A Mathematics 1 or MT105B Mathematics 2, but must still meet the other prerequisites and co-requisites.