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
March/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
- MT1174 Calculus OR MT1186 Mathematical Methods
- MT1173 Algebra OR MN1178 Business and Management in a Global Context
- ST1215 Introduction to Mathematical Statistics Second year Modules
Level 200 and 300 courses
- ST2195 Programming for Data Science
- ST2187 Business Analytics, Applied Modelling and Prediction
- ST2133 Advanced Statistics: Distribution Theory AND ST2134 Advanced Statistics: Statistical Inference
- EC2020 Elements of Econometrics OR MT2116 Abstract Mathematics OR IS2184 Information Systems Management
Level 6 modules
- Any 300 level EC, MN, MT or ST course from the Recommended optional courses
- ST3188 Statistical Methods for Market Research
- ST3189 Machine Learning
- Any course from the Recommended optional courses
Recommended optional courses
- EM3000 Dissertation
- MN3141 Marketing Management
- MN3194 Entrepreneurship
- IS2184 Information Systems Management
- MN2032 Management Science Methods
- MT2176 Further calculus (half course) and MT2175
- Further Linear Algebra (half course)
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