BSc (Hons) Computing with Data Science and Big Data Technology

Data scientists carry out applied research to create innovative data driven solutions to business problems. Usually, they work with large, complex, varied, and unstructured data sets, that are not suitable for using traditional data analysis approaches and techniques. 

Indeed, the demand for data scientists is ever rising and a report suggest that the shortage of data scientists has become a serious constraint (Society, 2019).

According to UK National Data Strategy (Department for Digital, 2020) there is a need in the market for those with qualifications and skills in Data Science technology. This BSc programme can prepare you for a range of careers in Big Data and Data Science including technical, management, and leadership opportunities in this discipline.

Key facts

• Learn to develop and test various data science applications for business intelligence
• Learn to programme with SQL, MySQL, Python, R language or similar and deploy distributed machine learning models using Google Cloud, Microsoft Azure or AWS
• Satisfy the educational requirements of the BCS, The Chartered Institute for IT for professional membership
• Top up your existing qualification to a UK honours degree with direct entry onto Level 5 or 6

What will I study?

• This programme is designed for those, who wish to study a broad-based computing programme with a specialism in data science and big data technology. It is also attractive to learners who have related Data Science or IT work experience and wish to gain an academic qualification in a subject area in which they are familiar. This programme is specifically designed to enable you to develop in depth technical knowledge that will allow you to discover new data driven solutions.
• You will also train and deploy distributed machine learning models using cloud-based platform such as Google Cloud, Microsoft Azure or AWS or similar and machine learning technology. You will additionally be exposed to the in-depth concepts, principles, technologies, and techniques of big data analytics. You will subsequently be able to apply this knowledge and skill in your own context, and subsequently critically analyse the implementation and recommend potential future improvements.

How will I be taught and assessed?

• Teaching is delivered through a mix of lectures, workshops, lab sessions, seminars, tutorials, case studies, guest/expert input, and task-based learning in guided and independent study, totalling between 4-14 hours per week (plus project work on Levels 5 and 6)
• You’re expected to engage in independent study, around 30 hours per week
• Assessments take place through mix of coursework and exams, including quizzes, tests, mock exams, practical lab exercises, presentations, Q&A and discussions, formal exams, critical report writing and in-class tests.
• Taught by experienced lecturers and academics who use their industry experience to demonstrate how theories translate into real-life situations
• Technology-enhanced learning (TEL) is embedded throughout the course to guide your preparation for seminars and independent research
• Benefit from weekly academic support sessions designed to build your ability and confidence as an academic learner
• You will be assigned a guidance tutor at induction who you will meet regularly during your studies

Careers and further study

• After graduating from this programme, you will be equipped to work in a variety of careers in the IT industry, or to progress to academic or research-orientated careers.

The programme will develop your skills and competencies for careers in a range of job roles, such as:

• Data Scientist
• Data Engineer
• Machine Learning Engineer
• Data Analyst
• Data Architect
• Information Security Professional
• Business Analyst
• Business Intelligence Developer, to name but a few

Year 1

• Algorithms and Programming Fundamentals
• Foundations of Computing Technology
• Database Design and Implementation
• Data Communications & Networks
• Web Design and Development
• Software Engineering Principles
• Academic Language Skills for Computing and Technology

Year 2

• Cloud Computing Technologies
• Cyber Security
• Systems and Processes in Business Context
• Academic Language Skills (0 credits)
• Developing Digital and Professional Competence
• Contemporary Issues in Computing and Digital Technologies
• London Campus UG Internship (optional)
• London Campus UG Group Consultancy Project (optional)
• London Campus UG Professional Practice (optional)

Year 3

• Technology Strategy and Leadership for Sustainability
• Academic Language Skills for Northumbria London Campus
• UG Project (40 credits)
• Data Science and Data Analytics
• Big Data Analytics
• Machine Learning on Cloud