Studying electives will allow you to develop domain expertise in the areas of your interest, and broaden your understanding of how to solve business problems.
Business Analytics electives
Each elective will introduce the main analytical models and questions in the area and you will gain expertise in both the language and tools specific to that business area. Real-world data sets and cutting-edge tools and models will allow you to apply your knowledge directly within your chosen industry.
You will choose six electives from options such as:
This elective aims to teach you basic analytics skills and methodologies for large-scale data analysis. It will focus on the practical use of these skills and methodologies to solve real world problems. You will cover a wide spectrum of technologies and algorithms in machine learning.
This elective considers the problems that arise in digital marketing and the models and business requirements of digital marketing. The elective includes hands-on practical analysis of two to three digital marketing-specific data sets using the methodologies learned earlier in the programme. You will learn to analyse shopping-cart data, sales data and click-stream data for web and e-commerce analytics.
By studying this module you will gain an understanding of the energy industry and the key problems faced by participants in energy markets. You'll be exposed to the challenges arising from changes in energy systems from increasing renewable energy and decarbonisation. Learn about the types of available data for energy markets, and the way that these can be used in energy analytics. You'll also gain an understanding of the metrics and models used in the energy industry, and the way that these can be used by decision makers. Discover how to communicate with business users in the energy domain and answer their questions through data analytics.
This elective looks at the problems and data sets that arise in financial industries and the models and business requirements of financial businesses. It includes hands-on practical analysis of financial industry-specific analytic specific data sets using the methodologies learned earlier in the programme.
Healthcare and medical fields are rich sources of data. This elective includes hands-on practical analysis of healthcare-specific data sets using the methodologies learned earlier in the programme.
This elective considers the problems that arise in logistics and supply chains and the models and business requirements of supply-chain businesses. Efficient routing of vehicles, identification of bottlenecks, same-day delivery and other operational problems are increasingly occupying many delivery and e-commerce industries. Large real-time data sets are used for analysis and control. This elective studies models and analysis of such problems.
When crossed with distribution and social-media data, retail scanner and other sales data has become a very rich source for marketers. This elective uses such data sets and consumer choice and behavioural models to show how retailers and marketers can make better marketing decisions.
Problems that arise in human resources, work flow and performance monitoring and the models and business requirements of human resource departments are increasingly becoming important as software and sensors monitor the workforce. The elective includes hands-on practical analysis of workforce-specific analytic data sets using the methodologies learned earlier in the programme.
Automation and globalisation have profoundly changed manufacturing industries, displacing many jobs and creating turmoil. Until now, service operations were considered relatively safe, but this is soon set to change. We are seeing the beginnings of profound changes in the design and operation of service industries.
This module will concentrate on the management of services for efficiency and quality using big data and analytics. We will cover modern service design and include topics such as the use of automation and sensors to achieve efficiency and total quality. Data on customer reviews, complaints provide valuable information on improving service. Such data can be analysed using modern machine learning tools and procedures.
Electives available and module outlines are subject to change. Imperial College Business School reserves the right to alter modules whenever they need to be amended or improved.