COMP7002 - Business Analytics
Note: Whilst every effort is made to keep the syllabus and assessment records correct, the precise details must be checked with the lecturer(s).
- 2 or 3
- Taught By
- Philip Treleaven (Computer Science) with guest lecturers from other UCL departments (Statistical Science, Psychology, CASA, Mathematics, Public Policy) and industry professionals.
- To expose students to the challenges and potential of business analytics in relevant application areas: retail, online, finance, services etc. To explain how we acquire and use analytics, and subsequently process, analyze, and manipulate the data. To famliarise students with handling real data sets.
- Learning Outcomes
Students successfully completing the module should be able to:
- Read about and understand recent advancements in business analytics.
- Have a grasp of the key tools in geometry processing.
- Gain necessary practical skills to work directly with real-world business analytics.
- Be able to formulate and solve problems using the analytical tools they learn as part of the module.
Topics will include:
- Big Data and MapReduce techniques
- Customer analytics
- Computational statistics and machine learning
- Supply chain analytics
- Agent-based modelling and complexity
- Data mining
- Online analytics and recommender systems
- Social media scraping and sentiment analysis
- Geo-locational analysis
- Spatial analysis
- Business psychology and behaviour economics
Method of Instruction:
Lecture presentations and practical work.
The course has the following assessment components:
- Coursework (100%)
To pass this course, students must:
- Obtain an overall pass mark of 40% for all sections combined