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).

Code
COMP7002
Year
2 or 3
Prerequisites
None
Term
2
Taught By
Philip Treleaven (Computer Science) with guest lecturers from other UCL departments (Statistical Science, Psychology, CASA, Mathematics, Public Policy) and industry professionals.
Aims
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.

Content

Topics will include:

  • Big Data and MapReduce techniques
  • SAS
  • 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.

Assessment:

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

Resources:

TBC