Bachelor of Science (Honours) in Computer Science (University of London)

Standard Entry Requirements:

General Entrance Requirements (GER) are:

• At least 17 years or older by 30 November in the year of registration with UOL
• At least equivalent to B4 grade for Mathematics at GCE ‘O’ Level OR pass Numerical Maths module in the bridging programme at SIM
• Provide proof of competence in English acceptable to the University, such as a pass (Grade C6 and above) in the GCE ‘O’ Level English Language Examination

PLUS one of the following:

• Possess diploma awarded by SIM or a polytechnic in Singapore (or its equivalent) OR
• Two approved GCE ‘A’ or H2 level subjects and three approved GCE ‘O’ level subjects (at not less than grade C) OR
• Three approved GCE ‘A’ or H2 level subjects and one approved GCE ‘O’ level subject (at not less than grade C) OR
• Three H2 passes provided that at least grades D,E,E OR
• Two H2 and two H1 passes; all are in non-overlapping subjects, OR
• Its equivalent

Equivalent International Qualifications

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

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 

Recognition of Prior Learning (RPL)

RPL is the recognition of previously acquired learning which may be awarded if you have previously studied a similar module in the same depth, and you achieved good marks in the corresponding examination.

The qualification must have been obtained within the five years preceding the application for RPL.

For this programme, RPL for 1 year (2 semesters) is granted automatically to students with approved IT qualifications or diplomas. Selected IT diploma graduates will only be exempted if they complete one or two mathematics modules in the bridging course at SIM.*

*Note: There will be updates in mid-Mar 2024 for automatic RPL granted to students with approved IT qualifications or diplomas. The changes will be applicable for the Oct 2024 intake.

Information not available

Structure

• This programme will run over two semesters each year. Student can study up to four new modules in one semester; or two plus final project. 
• All classes are conducted face to face on SIM campus unless otherwise stated.  
• A blended learning approach is adopted. Besides learning via online resources, SIM prepares students for discussion, coursework or project work; face-to-face sessions emphasize on discussions, case studies, and hands-on exercises. In class, the lecturer facilitates discussion and learning. As such, a large amount of time is spent on a mixture of: 
  • lectures 
  • lab works 
  • computer simulation sessions 
  • online learning through Coursera platform* 
• Local faculty support from SIM and online academic support from Goldsmiths, University of London. 
• Average teacher-student ratio: 1:56 
• Academic materials include:
  • Coursera 
  • Virtual Learning Environment (VLE) 
  • SIMConnect portal 
  • University materials such as subject guides, past exam papers and exam commentaries, reading lists and handbooks on good study strategies 
• 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. 
• Minimum class size to commence is 25 students. Students will be informed within 30 days after the application period. 

 Coursera: The BSc Computer Science (Machine Learning and Artificial Intelligence) programme is fully developed and taught by the same faculty that teaches on-campus at University of London. The University of London leverages Coursera’s online education platform to deliver the programme curriculum, allowing our students to benefit from Coursera features such as interactive video transcription, in-course note taking, and seamless learning across multiple devices. 

At SIM, lecturers guide students to leverage the resources available on Coursera and facilitate the learning that takes place. The supplementary readings, video lectures, assignments, and discussion forums are extensively discussed in class. Students also collaborate on group projects using Zoom and Slack. Students may access all course materials anywhere with the mobile app on Coursera, available on iOS and Android. 

Using the mobile app, learners can: (1) Save a week’s worth of content for offline access with one click (2) Save and submit quizzes offline (3) View text transcripts of lecture videos (4) Take notes directly in the app (5) Set reminder alerts to help you make progress. 

Assessment & Attendance

• Modules: Each module, excluding the Final Project, is assessed either by coursework or a combination of coursework and a two-hour unseen written examination. 
  • Note: Each coursework element may consist of multiple items of assessment. The pass mark for any element of assessment is 40%. 
• Final Project: The summative assessment for the Final Project consists of both coursework and a written examination, weighted in the ratio 80:20. The written examination consisting of questions relating to your project. 
• Each item of coursework, totalling 80% of the overall mark for the Final Project, is weighted as follows:
• Attendance requirement: 
  • Local: 75% 
  • International (Dependent Pass holders/ Long-term Visit Pass holders): 90%

Modules

Year 1 Modules

Learn the fundamentals: how computers work, how to programme, and more about the mathematics that underpins computer science.

• CM1005 Introduction to programming I
• CM1010 Introduction to programming II
• CM1015 Computational mathematics
• CM1020 Discrete mathematics
• CM1025 Fundamentals of computer science
• CM1030 How computers work
• CM1035 Algorithms and data structures I
• CM1040 Web development

Year 2 Modules

Deepen the programming skills to consider software projects and explore specialist topics such as Graphics Programming and Data Science.

• CM2005 Object oriented programming
• CM2010 Software design and development
• CM2015 Programming with data
• CM2020 Agile software projects
• CM2025 Computer security
• CM2030 Graphics programming
• CM2035 Algorithms and data structures II
• CM2040 Databases, networks and the web

Year 3 Modules

Study elective modules then undertake a 30 credit project that combines your knowledge and skills to create a software system.

• CM3005 Data Science
• CM3010 Databases and advanced data techniques
• CM3015 Machine learning and neural networks
• CM3020 Artificial intelligence
• CM3025 Virtual Reality
• CM3030 Games Development
• CM3035 Advanced web development
• CM3040 Physical computing and internet of things
• CM3045 3D graphics and animation
• CM3050 Mobile development
• CM3055 Interaction design
• CM3060 Natural language processing
• CM3065 Intelligent signal processing

PLUS a compulsory project: 

• CM3070 Final project