BSc Data Science and Business Analytics
DurationÂ
3 years
Awarding Body
University of London
Academic Direction
The London School of Economics and Political Science
DeliveryÂ
Full time/ PhysicalÂ
Intakes
July/Sep
BSc Data Science and Business Analytics: You’ll study units such as programming for data science, machine learning, statistics, and abstract mathematics. This programme equips you with the skills to analyse large datasets, extract meaningful insights, and make data-driven decisions. Career prospects include data scientist, business analyst, data engineer, and business intelligence analyst
Academic Direction
At RIC, our students benefit from academic direction provided by prestigious institutions such as the London School of Economics and Political Science, University College London, and King’s College London, among others. This collaboration ensures access to top-tier resources, leading experts, and cutting-edge research, enriching their educational experience and enhancing academic outcomes.
- Applicant must hold at least 5 grades A – C at Ordinary Level, and 3 grades A – E at Advanced Level or equivalent
- This should include Ordinary Level Mathematics grade C or equivalent
- Mathematics at Advanced Level grade A-E or equivalent
- Pass the internal Admission Test and interview
Level 100 courses
- EC1002 Introduction to economics
- MT1173 Algebra and MT1174 Calculus
OR
MT1186 Mathematical methods AND MN1178 Business and management in a global context - ST1215 Introduction to mathematical statistics
Level 200 and 300 courses
- ST2195 Programming for data science
OR
IS2184 Information systems management - ST2187 Business analytics, applied modelling and prediction
- ST2133 Advanced statistics: distribution theory (half module) AND ST2134 Advanced statistics: statistical inference (half module)
- MT2116 Abstract Mathematics
OR
S2184 Information systems management
OR
EC2020 Elements of econometrics
Level 6 modules
- ST3188 Statistical methods for market research
- ST3189 Machine learning
- One 300 course (or two half courses) from selection groups E, M or N
- One 100,200 or 300 course (or two half courses) from any selection group
Recommended optional courses
- IS3167 Management and innovation of e-business
- MT3095 Further mathematics for economists
- FN2191 Principles of corporate finance
- MT2176 Further calculus (half course) and MT2175 Further linear algebra (half course)
- EC2065 Macroeconomics
- EC2066 Microeconomics
Graduate entry route comprises 9 full courses (or equivalent)
- Data scientist/Data engineer/ Data analyst
- Artificial Intelligence application developer
- Algorithm specialist
- Big data engineer
- Machine learning scientist/ Machine learning engineer
- Business intelligence developer
- Research scientist
- Security analyst
*This list is non-exhaustive