BSc Computer Science (Data Science)

The University of Greenwich has a long-standing relationship with the British Computer Society (BCS), which accredits our computing degree programmes. As this programme was extensively updated in 2019, it has a current designation of Initial Full Chartered Information Technology Professional (CITP) and Partial Chartered Engineer (CEng) accreditation for the 2019 intake. The accreditation status is expected to be confirmed in autumn 2022 after the first cohort of students graduate. Students will be kept updated on the status of this, in the very unlikely event that this does not progress as expected the university will support students with individual BCS membership applications at the point of graduation.****Study a Computer Science degree for the skills to pursue careers as Computer Science professionals specialising in Data Science. Study in London. Read more.**Throughout this Computer Science degree, you will develop a firm grasp of the science underpinning computer and software systems. The modules you can study as part of this degree include Statistical Techniques with R, Information Visualisation and Big Data and Machine Learning.You will gain practical experience of developing systems using the latest technologies and techniques, plus exposure to the latest trends that will shape the future of computer science. By the end of the course, you will be equipped to work independently and to develop and adapt your skills throughout your future career.**What you should know about this course*** You will learn the core algorithms underpinning data processing and develop analytical skills with statistical technologies to create solutions and applications in big data.* Gain valuable skills and the ability to design intricate algorithms and visualisations from large unstructured data.* Elicit, analyse, and specify requirements and master the mathematical and analytical foundations underpinning data.

Semester – 1

• Data Management
• Introduction to Statistical Data Analysis with R
• Business Analytics Strategy and Practice
• Data Mining and Knowledge Discovery in Data
• Project

Semester – 2

• Data Management
• Introduction to Statistical Data Analysis with R
• Business Analytics Strategy and Practice
• Data Mining and Knowledge Discovery in Data
• Project