Program Overview
This BSc Hons degree in Computer Science (Data Science) from the University of Greenwich equips students with the skills to specialize in Data Science. It provides a comprehensive understanding of computer and software systems, focusing on data processing and analysis. Graduates are prepared for careers in IT support, consulting, and internet applications, with the program being accredited by BCS, The Chartered Institute for IT.
Program Outline
Computer Science (Data Science), BSc Hons - University of Greenwich
Degree Overview:
This BSc Hons degree in Computer Science (Data Science) equips students with the skills to pursue careers as Computer Science professionals specializing in Data Science. The program focuses on developing a strong understanding of the science behind computer and software systems, with a particular emphasis on data processing and analysis.
Objectives:
- Develop a firm grasp of the science underpinning computer and software systems.
- Gain practical experience in developing systems using the latest technologies and techniques.
- Master the mathematical and analytical foundations underpinning data.
- Gain valuable skills in designing intricate algorithms and visualisations from large unstructured data.
- Be equipped to work independently and adapt skills throughout their future career.
Outline:
Full-time (3 years):
Year 1:
- Compulsory Modules:
- Computer and Communication Systems (15 credits)
- Paradigms of Programming (30 credits)
- Algorithms and Data Structures (15 credits)
- Introduction to Compilers (15 credits)
- Principles of Software Engineering (15 credits)
- Mathematics for Computer Science (15 credits)
- Advanced Mathematics for Computer Science (15 credits)
Year 2:
- Compulsory Modules:
- Advanced Programming (15 credits)
- Information Security (15 credits)
- Statistical Techniques with R (15 credits)
- Introduction to Artificial Intelligence (15 credits)
- Advanced Algorithms and Data Structures (15 credits)
- Operational Research: Linear Programming (15 credits)
- Computational Methods and Numerical Techniques (30 credits)
Year 3:
- Compulsory Modules:
- Final Year Projects (60 credits)
- Machine Learning (15 credits)
- Artificial Intelligence Applications (15 credits)
- Statistical Techniques and Time Series (15 credits)
Part-time (6 years):
Year 1:
- Compulsory Modules:
- Computer and Communication Systems (15 credits)
- Paradigms of Programming (30 credits)
- Algorithms and Data Structures (15 credits)
- Introduction to Compilers (15 credits)
- Principles of Software Engineering (15 credits)
- Mathematics for Computer Science (15 credits)
- Advanced Mathematics for Computer Science (15 credits)
Year 2:
- Compulsory Modules:
- Computer and Communication Systems (15 credits)
- Paradigms of Programming (30 credits)
- Algorithms and Data Structures (15 credits)
- Introduction to Compilers (15 credits)
- Principles of Software Engineering (15 credits)
- Mathematics for Computer Science (15 credits)
- Advanced Mathematics for Computer Science (15 credits)
Year 3:
- Compulsory Modules:
- Advanced Programming (15 credits)
- Advanced Algorithms and Data Structures (15 credits)
- Computational Methods and Numerical Techniques (30 credits)
Year 4:
- Compulsory Modules:
- Information Security (15 credits)
- Statistical Techniques with R (15 credits)
- Introduction to Artificial Intelligence (15 credits)
- Operational Research: Linear Programming (15 credits)
Year 5:
- Compulsory Modules:
- Machine Learning (15 credits)
- Artificial Intelligence Applications (15 credits)
- Statistical Techniques and Time Series (15 credits)
Year 6:
- Compulsory Modules:
- Final Year Projects (60 credits)
Sandwich (4 years):
Year 1:
- Compulsory Modules:
- Computer and Communication Systems (15 credits)
- Paradigms of Programming (30 credits)
- Algorithms and Data Structures (15 credits)
- Introduction to Compilers (15 credits)
- Principles of Software Engineering (15 credits)
- Mathematics for Computer Science (15 credits)
- Advanced Mathematics for Computer Science (15 credits)
Year 2:
- Compulsory Modules:
- Advanced Programming (15 credits)
- Information Security (15 credits)
- Statistical Techniques with R (15 credits)
- Introduction to Artificial Intelligence (15 credits)
- Advanced Algorithms and Data Structures (15 credits)
- Operational Research: Linear Programming (15 credits)
- Computational Methods and Numerical Techniques (30 credits)
Year 3:
- Compulsory Modules:
- Work Placement Course - CMS
Year 4:
- Compulsory Modules:
- Final Year Projects (60 credits)
- Machine Learning (15 credits)
- Artificial Intelligence Applications (15 credits)
- Statistical Techniques and Time Series (15 credits)
Assessment:
- Assessment methods vary depending on the module.
- Students are assessed through a combination of methods, including:
- Coursework
- Exams
- Presentations
- Projects
Teaching:
- The program employs a range of innovative teaching and learning methods.
- Lectures and laboratories/tutorials are dynamic and interactive.
- Students are taught by an experienced team of lecturers, supported by a team of technical officers.
Careers:
- Graduates are prepared for careers in various computing areas, including:
- IT support
- Consultancy
- Internet and e-commerce applications
- Graduates can work as independent consultants or in teams with other computer professionals to build and support modern computing systems.
- Students are encouraged to take up Summer internships during the Summer holidays.
- The Employability and Careers Service provides support for students preparing to apply for placements and graduate roles, including CV clinics, mock interviews, and employability skills workshops.
Home Fees:
•Full-time: £9,250 •Part-time: £2,312 per 30 credits
International Fees:
•Full-time: £17,000 •Part-time: £4,250 per 30 credits Please note that the above fees are for the academic year 2024/25 and are subject to change. There are no additional compulsory costs beyond your tuition fees, but It is recommended that you purchase a backup device (such as a portable hard drive). Software: The University provides licenses for certain software to use on your own computers, depending on your course. This may include Virtual Desktop access, Tableau Desktop, Microsoft Azure Devtools for Teaching (including Visio, Project, SQL Server, etc). You will also have access to Nvivo, SPSS Modeler and SPSS Amos. Any licenses for software outside of their range will come at your own cost.
