Software engineering UOR bachelors
Bachelor of Science (Honours) in Computer Science (Top Up)
24 months Part-time
Software Engineering
Bachelor’s Degree
University of Roehampton
Course Overview
The “BSc in Computer Science (Top Up)” program aims to equip students with critical knowledge and skills for roles in software engineering, data science, and cyber-security. Graduates develop theoretical and practical computing skill, analytical and problem-solving abilities applicable in complex business scenarios, fostering professionalism and ethical conduct in cross-cultural teams.
The program cultivates reflective practitioners capable of identifying and analyzing system requirements, design, implement, test, and deliver solutions through blended and project-based learning.
Gain deep insight into systems architecture and its integration with computer science principles.
Acquire knowledge of mathematical, statistical, and computational modeling relevant to computer science applications.
Develop proficiency in information modeling, management, and security tools crucial for computer science.
Understand the economic and commercial aspects impacting computer science practices.
Learn effective management techniques essential for overseeing computer science projects and teams.
Master these tech tools
Experiential Learning
108 hours
108 hours
Small group learning
8 hours
Flipped Class/Mentoring
212 hours
Tutorial
96 hours
96 hours
Self paced learning
988 hours
988 hours
Prerequisites
Target Audience
Candidates who have completed Higher Diploma/Advanced Diploma in IT/Computer Science/Software Engineering and its related or Higher National Diploma in Computing related from Pearson or Polytechnic Diploma holders in relevant studies and willing to transitioning their career into IT field, and matured candidates with relevant work experience for minimum 8 years.
Admission Prerequisite
Academic Qualification:
English Proficiency:
- Relevant polytechnic diploma in Computer Science and related subjects (equivalent to Level 4/Year 1 and Level 5/Year 2 of the University Course) with an entry requirement of 10 years of formal education or
- Higher Diploma (Diploma and Advanced Diploma) in Computer Science and related discipline with minimum pass grades (equivalent to Level 4/Year 1 and Level 5/ Year 2 of the University Course) with an entry requirement of 12 years of formal education or
- Higher National Diploma with an overall Merit (60%) or above in a relevant subject area or
- Mature candidate of 30 years and above with 8 years of relevant work experience
IELTS – 6.0 (with no elements lower than 5.5) or C6 in English at GCE “O” level or Letter from College/University clearly stating the Medium of Instruction of the highest qualification to be English or its equivalent.
Graduation Requirements
Minimum attendance of 75% in all the sessions of each module
Minimum pass grade in the summative assessment of each module
Module Summary
Module 1
Module 2
Module 3
Module 4
Module 5
Module 1
Data Visualization
Session Plan Details
Master the art of turning complex data into engaging visual stories. You’ll learn design principles, visual techniques, and how to evaluate visualizations through user studies. Additionally, you’ll gain practical skills in web development to present interactive visualizations, preparing you for impactful data reporting.
What You’ll Learn
- Principles of data visualisation.
- Visualisation design.
- Perceptual and cognitive foundations of visualisation.
- Visualisation of 2D/3D scalar data.
- Visualisation techniques.
- Image processing and colour models.
- Visualisation of tree/graph data.
- Graphing and visualisation algorithms.
- Visualisation of high-dimensional data.
- Conducting user studies – evaluation of visualisation methods.
- Statistical methods for human-computer interaction.
- Combining qualitative and quantitative results.
Module 2
Machine Learning
Session Plan Details
Dive into how machines learn from data to perform tasks intelligently. You’ll explore decision trees, neural networks, and the ethical concerns of biased data. You’ll gain hands-on experience with tools, algorithms, and libraries, preparing you for real-world automation tasks across industries.
What You’ll Learn
- Definition of machine learning.
- Inductive and statistical learning.
- Classifier accuracy.
- Supervised learning.
- Learning neural-networks.
- Unsupervised learning.
- Semi-supervised learning.
- Performance evaluation of machine learning.
- Reinforcement learning.
- Machine learning and data mining.
- Ethical concerns of machine learning.
- Issues with bias in data sets.
Module 3
Data Engineering
Session Plan Details
Learn how to build and manage data pipelines that drive data-driven decisions. You’ll explore concepts like parallelism, distributed data platforms, data warehousing, and cloud solutions. By working in agile teams, you’ll develop sophisticated, scalable data solutions, preparing you for real-world data engineering challenges.
What You’ll Learn
- Introduction to Data Engineering.
- Parallelism Fundamentals.
- Parallel System Architecture.
- Distributed System Architecture.
- Distributed Databases.
- Managing Large Data Volumes.
- Data Sources: Databases, Warehouses, and Lakes.
- Streaming Data.
- Transaction Processing.
- Indexing Data.
- Data Pipeline in the Cloud
- Delivering Data to Data Scientists
Module 4
Cyber-Security
Session Plan Details
Dive into the risks and mitigations related to computer security. You’ll explore privacy from ethical and legal perspectives, learn core security principles like CIA, and examine cryptography, secure design, and human factors. By the end, you’ll be prepared to evaluate systems for vulnerabilities and understand security requirements in real-world contexts.
What You’ll Learn
- Philosophical and legal foundations of privacy.
- Ethical considerations in data collection and storage.
- Technology solutions for privacy.
- Security policies, laws, and computer crime.
- Foundational concepts of security: CIA, authentication, and trust.
- Threats and attacks.
- Principles of secure design.
- Basics of cryptography.
- Cipher types.
- Human factors and security.
- Usability design and security.
- Security and governance.
Module 5
Final Year Project
Session Plan Details
You’ll have the opportunity to explore a topic that sparks your interest, with support from an academic supervisor. Choose from four project types: student-defined, academic-defined (research-based), industry-defined, or social enterprise. You’ll research, develop a product, and present it in a final showcase with external partners.
Module 1
Module 2
Module 3
Module 4
Module 5
Module 1
Data Visualization
Session Plan Details
Master the art of turning complex data into engaging visual stories. You’ll learn design principles, visual techniques, and how to evaluate visualizations through user studies. Additionally, you’ll gain practical skills in web development to present interactive visualizations, preparing you for impactful data reporting.
What You’ll Learn
- Principles of data visualisation.
- Visualisation design.
- Perceptual and cognitive foundations of visualisation.
- Visualisation of 2D/3D scalar data.
- Visualisation techniques.
- Image processing and colour models.
- Visualisation of tree/graph data.
- Graphing and visualisation algorithms.
- Visualisation of high-dimensional data.
- Conducting user studies – evaluation of visualisation methods.
- Statistical methods for human-computer interaction.
- Combining qualitative and quantitative results.
Module 2
Machine Learning
Session Plan Details
Dive into how machines learn from data to perform tasks intelligently. You’ll explore decision trees, neural networks, and the ethical concerns of biased data. You’ll gain hands-on experience with tools, algorithms, and libraries, preparing you for real-world automation tasks across industries.
What You’ll Learn
- Definition of machine learning.
- Inductive and statistical learning.
- Classifier accuracy.
- Supervised learning.
- Learning neural-networks.
- Unsupervised learning.
- Semi-supervised learning.
- Performance evaluation of machine learning.
- Reinforcement learning.
- Machine learning and data mining.
- Ethical concerns of machine learning.
- Issues with bias in data sets.
Module 3
Data Engineering
Session Plan Details
Learn how to build and manage data pipelines that drive data-driven decisions. You’ll explore concepts like parallelism, distributed data platforms, data warehousing, and cloud solutions. By working in agile teams, you’ll develop sophisticated, scalable data solutions, preparing you for real-world data engineering challenges.
What You’ll Learn
- Introduction to Data Engineering.
- Parallelism Fundamentals.
- Parallel System Architecture.
- Distributed System Architecture.
- Distributed Databases.
- Managing Large Data Volumes.
- Data Sources: Databases, Warehouses, and Lakes.
- Streaming Data.
- Transaction Processing.
- Indexing Data.
- Data Pipeline in the Cloud
- Delivering Data to Data Scientists
Module 4
Cyber-Security
Session Plan Details
Dive into the risks and mitigations related to computer security. You’ll explore privacy from ethical and legal perspectives, learn core security principles like CIA, and examine cryptography, secure design, and human factors. By the end, you’ll be prepared to evaluate systems for vulnerabilities and understand security requirements in real-world contexts.
What You’ll Learn
- Philosophical and legal foundations of privacy.
- Ethical considerations in data collection and storage.
- Technology solutions for privacy.
- Security policies, laws, and computer crime.
- Foundational concepts of security: CIA, authentication, and trust.
- Threats and attacks.
- Principles of secure design.
- Basics of cryptography.
- Cipher types.
- Human factors and security.
- Usability design and security.
- Security and governance.
Module 5
Final Year Project
Session Plan Details
You’ll have the opportunity to explore a topic that sparks your interest, with support from an academic supervisor. Choose from four project types: student-defined, academic-defined (research-based), industry-defined, or social enterprise. You’ll research, develop a product, and present it in a final showcase with external partners.
Education Pathway
After meeting the graduation requirements, the candidate will be awarded a top-up degree.
Pearson BTEC International Level 3 in Information Technology
Foundation Diploma
Higher Diploma in Software Engineering
Diploma
Bachelor of Science (Honours) in Computer Science (Top Up)
Bachelor’s Degree
Certification(s)
Certification(s) Earned
- BSc Computer Science (Top-Up) awarded by University of Roehampton, United Kingdom
Pricing
Course Fee
USD 3,000
Payment Plan
Tuition fee is available for full payment and installments before the start of class. For more details Contact Us.
| Bachelor of Science (Honours) in Business Management and Marketing (Top-Up) | Installment Plan | Tuition Fees |
|---|---|---|
| Month 1-17 | USD 300 /month | |
| Total | 18 installments | USD 5,400 |
About University of Roehampton
The University of Roehampton, London, has a proud history in higher education stretching back 180 years. While still focused on its pioneering values and teaching heritage from its 19th-century collegiate roots, the University has developed a diverse curriculum that reflects London’s multicultural creative spirit. It offers a high-quality UK education experience to more than 10,000 students from 141 countries.
Known for its commitment to personalized learning and academic excellence, Roehampton offers a range of undergraduate, postgraduate, and research programs across various disciplines. With a focus on preparing students for successful careers and fulfilling lives, the university emphasizes innovative teaching methods, research-led learning, and strong community engagement. Roehampton values diversity, creativity, and critical thinking, shaping global citizens who contribute positively to society.
Learn more roehampton.ac.uk
