Master of Science in Computer Science

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Are you interested in the design, development, and implementation of software-based solutions? With the master’s programme in Computer Science partnered with the University of East London, you could further your education in the industry in a myriad of disciplines.
Master of Science in Computer Science

Key Facts

  • Duration: 12 months (full-time), 12 months (part-time)
  • Class frequency: 4 days/week & 3 hours/day (full-time), 2 days/week & 3 hours/day (part-time)
  • Intake date: Starts in February, June or October
  • Delivery Mode:
    • Live Online
    • On campus
  • Fees: SGD $18,203.00 (Local students), SGD $20,185.19 (International students) (Prices inclusive of GST)

The University of East London (UEL) is a public university in the UK and is recognised as such by the UK government. They are a careers-led university, dedicated to supporting students to develop the skills, emotional intelligence, and creativity needed to thrive in a constantly changing world. It has two campuses in London -  Stratford and London Docklands. Their ambitious but achievable goal is to become the leading careers-focused, enterprising university in the UK, one which both prepares students for jobs of the future and provides the innovation to drive that future sustainably and inclusively. UEL and its predecessor institutions have a number of notable academic staff and alumni, including politicians, business people, authors, actors, musicians, and sportspeople.

  • According to the recently published QS rankings for 2021, UEL ranks 68th amongst UK institutions. 
  • UEL is accredited by the British Computer Society (BCS), the Chartered Institute for IT, so holding a degree from UEL will be recognised worldwide.

This is designed to give students the opportunity to: 

  • Design & develop large-scale service-oriented software systems from requirements to testing and management of its entire development lifecycle.
  • Develop knowledge and research skills in artificial intelligence, computer vision and data analytics to empower Learners/Students as a professional.
  • Gain advanced theoretical and specialist practical knowledge of progressive and emerging topics.
  • Tackle a cutting-edge problem from emerging areas in computer science, including its legal, social, ethical & professional context, resulting in a high-quality research output through the dissertation.
  • Develop the professional skills necessary for a senior career in the IT industry. 


  • Demonstrate a comprehensive and critical understanding of all the concepts and activities for large-scale software development
  • Demonstrate expertise in artificial intelligence, computer vision and data analytics and their business and research applications
  • Have a critical understanding of complex computing application areas and apply skills in advanced topics to find resolution through 
  • Learners/Students dissertation


  • Critical thinking and evidential reasoning
  • Exercise appropriate engineering judgement in the decision-making process
  • Systematically analyse problems and implement effective solutions
  • Reflect on Learners/Students in professional and research practice

Subject-Based Practical skills:

  • Design & develop large-scale software systems by managing its entire Software Development Lifecycle
  • Use diverse artificial intelligence, computer vision and data analytics resources and advanced tools and techniques to solve a defined problem
  • Identify, critically analyse and execute a solution for a cutting-edge research/industrial computing problem
  • Skills for life and work (general skills/transferable skills)
  • Demonstrate an ability to study independently and effectively, and to be able to present and convey complex technical information to other professionals and the public
  • Develop interpersonal skills and be able to contribute and work effectively in a team
  • Integrate research and articulate research results into professional practice

LSBF Singapore students will gain access to Amazon Web Services (AWS) Educate resources as they will study the Cloud Computing module in the curriculum. Here are the advantages: 

  • Organizations require individuals with cloud computing skills to facilitate business transformation and AWS Educate will help build and validate their skill set.
  • Students will be guided to access comprehensive resources from AWS Educate that are relevant for building skills in Cloud Technology, Data Analytics, Security, Networking, and Cloud Architecture
  • Students will have access to the AWS Educate Job Board, to search and apply for cloud entry-level jobs and internship opportunities from Amazon and other companies around the world.
  • Upon completion of the Cloud Computing module, students will have the opportunity to attempt AWS certification exams on their own.
  • Students will be invited to participate in Hackathon Contests or any relevant contests organized by AWS.

Modules are allocated a mark out of 100%. The pass mark for each module is based on an aggregate mark of 50%. The aggregate mark comprises marks from components/modules whose threshold is 40%. Assessment may incorporate one, two, or three components/modules.

The module specifications specify the mode of assessment for each module.

Assessment methods include formal examinations, work, project work, and group exercises.

Learners/Students with disabilities and/or particular learning needs should discuss assessments with the Module Leader to ensure they are able to fully engage with all assessments within the module.

a. Minimum Academic Entry Requirement 

Learners/Students who have successfully completed either of the following:

  • Bachelor's degree in Science or Engineering subjects from a recognised university with a minimum of 2:2 classifications.
  • Learners/Students who have obtained equivalent qualifications in relevant fields (usually professional qualification), will be assessed case-by-case and subjected to university approval.

b. Minimum English Language Requirement 

  • Applicants who have not studied prior qualifications in English require IELTS 6.0 or equivalent in an accepted English language test.

c. Minimum Age Requirement 

  • 21 years or above 

d. Admission Requirement

Accreditation of prior certificated and experiential learning:

  • University of East London’s ACL & AEL – Accreditation of Certificated Learning (ACL)- learning that has been recognised previously by LSBF, and which is demonstrated by formal certification
  • Accreditation of Experiential learning achieved by reflecting on experiences outside formal education and training systems
  • Students, who have obtained equivalent qualifications in relevant fields, will be assessed case-by-case and subjected to university approval


Description Minimum Recommended
Computer and processor 1.6 GHz or faster, 2-core Intel Core i3 or equivalent 1.8 GHz, 2-core Intel Core i3 or equivalent
Memory 4 GB RAM 8 GB RAM
Hard Disk

256 GB disk size

Display 1280 x 768 screen resolution (32-bit requires hardware acceleration for 4K and higher) N/A

An internet connection – broadband wired or wireless

Speakers and a microphone – built-in or USB plug-in or wireless Bluetooth

A webcam or HD webcam - built-in or USB plug-in




This module provides students with conceptual knowledge in the analysis, design, and validation of software systems. The module covers all stages of the software development process from requirements through to modeling, design and testing, and project management techniques for managing this process. The module also provides students with practical experience in designing and developing software using an appropriate methodology.

This module aims to provide students with the core theoretical and practical background required for big data analytics and developing big data systems. It will provide you with an insight into areas of big data management and advanced analytics. You will develop in-depth practical skills through using tools and techniques from the forefront of the emerging field of data analytics.

This module aims to provide students with conceptual knowledge in Artificial Intelligence (AI) and Machine Vision. The module equips the students to develop competencies in digital image analysis and machine learning approaches for the design and development of computing applications.

This module provides students with an overview of the field of Cloud Computing, its enabling technologies, main building blocks, and hands-on experience. The course will introduce this domain and cover the topics of data centres, virtualization, cloud storage, and various Cloud paradigms. Motivating factors, benefits, challenges, and service models will be discussed. Modern data centres enable many of the economic and technological benefits of the cloud paradigm; hence, the module describes several concepts behind data centre design and management.

This module aims to provide an understanding of the tools and techniques needed to protect computers, networks, and internet sites from unauthorised intrusion. This will involve studying possible security risks and the application of appropriate technical, defensive mechanisms/tools to counteract cyber crime.

Conduct a practical project of a Master's level quality related to the scope of the selected MSc programme and develop skills appropriate for senior computing professionals. Students will consider the ethical, legal, social, and professional issues, and the dissertation will require appropriate research, analysis, design, implementation, quality assurance, evaluation and project management. Students will reflect on the success of the strategies that they employed to further develop their reflective skills, self-awareness, 'lifestyle' and self-care approaches and where necessary improve their approaches.

Request More Information

Contact a programme advisor by calling
+65 6580 7700

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