Machine Learning and Predictive Analytics

Code

BUSI4373

School

Business

Level

4

Credits

20

Semesters

Spring UK

Summary

This module builds on Foundational Business Analytics covering more advanced predictive models and their motivation within business use cases. Students will establish knowledge of state-of-the-art prediction techniques including SVMs, temporal Nearest Neighbour models, Ensembles and Deep Learning. Practical exercises will be set against a range of real world based datasets and time series data. Focusing on the applicability of models to real world problems the module will consider the appropriateness and utility of each method with respect to common "tricky" data properties in real world data that lead to under-performing models. Examples include unbalanced classes, heterogeneous input feature types and detrimentally large number of input features. Within the module methods to unpack the various predictive models to understand why they predict what they do and the utility of this information in various business contexts will be covered.

Target Students

Only available for MSc Business Analytics students. Students must have studiedBUSI4369 Data at Scale and BUSI4371 Foundational Business Analytics and Programming before taking this module. Available to MSc Exchange students.

Co-requisites

Modules you must take in the same academic year, or have taken in a previous year, to enrol in this module:

• Data at Scale: Management, Processing, Visualization (BUSI4369)
• Foundational Business Analytics (BUSI4371)

Classes

• One 1-hour lecture each week for 11 weeks
• One 3-hour computing each week for 11 weeks

This module is taught through a combination of lectures and computing sessions.

Assessment

• 50% Coursework: 3,000 words. Reassessment of the module will be 100% exam (2hrs).
• 50% Exam (2-hour): Written in person exam.

Assessed by end of spring semester

Educational Aims

Learning Outcomes

Knowledge and Understanding

This module develops a knowledge and understanding of:
•    Marketing and sales and different approaches for segmentation, targeting, positioning, generating sales, and the need for innovation in product and service design
•    Customers and stakeholders - customer expectations, service and orientation
•    The management of projects
•    Information systems and business intelligence - the development, management, application and implementation of information systems and their impact upon organisations
•    Tools and techniques for transforming (big) data into useful information for business analysis and decision support
•    Communications and the comprehension and use of relevant communications for application in business and management, including the use of digital tools
•    Digital business and the development of strategic priorities to deliver business at speed in an environment where digital technology is reshaping traditional revenue and business models, associated risk management

Intellectual Skills

This module develops: 
•    Being able to think critically and be creative: manage the creative processes in self and others; organise thoughts, analyse, synthesise and critically appraise. This includes the capability to identify assumptions, evaluate statements in terms of evidence, detect false logic or reasoning, identify implicit values, define terms adequately and generalise appropriately
•    Being able to solve complex problems and make decisions: establish criteria, using appropriate decision-making techniques including identifying, formulating and solving business problems; and the ability to create, identify and evaluate options; the ability to implement and review decisions
•    Using information and knowledge effectively in order to abstract meaning from information and to share knowledge, including the use of quantitative skills

Professional Practical Skills

This module develops:
•    The ability to conduct research and enquiry into business and management issues either individually or as part of a team through research design, the collection and analysis of quantitative data, synthesis and reporting
•    The ability to recognise the need for and initiate change and to be able to manage change
•    The ability to recognise and address ethical dilemmas, corporate social responsibility and sustainability issues, applying ethical and organisational values to situations and choices

Transferable (key) Skills

This module develops:

• Effective communication: networking, listening, oral and written communication of complex ideas and arguments, using a range of media, including the preparation of business reports
• High personal effectiveness: critical self-awareness, self-reflection and self-management time management conflict resolution, displaying commercial acumen, the ability to continue to learn through reflection on practice and experience
• Soft skills: understanding the needs of others and empathy towards them sensitivity to diversity in people and in different situations

Conveners

• Dr Gavin Smith