Master's modules.
Core and FinTech specialisation papers from the Master of Business Analytics at the University of Auckland.
Analysis of Business Problems
Develops a managerial perspective on small and big data in problem identification, analysis and decision-making. Foundations of statistics and machine learning for business questions.
Business Analytics Tools
Skills in programming and business intelligence tooling for data wrangling, analytical thinking and problem-solving across a range of business settings.
Information Management
Modelling structured data, designing relational databases and OLAP systems, writing SQL and planning ETL flows to make data fit for analytical use.
Data Visualisation for Business
Transforming data for effective visualisation, building analytical narratives, and critiquing visual representations, with a side of unsupervised ML for unlabelled data.
Predictive Business Analytics
Common supervised ML techniques, linear and logistic regression, random forests, neural networks, applied to predict business events in R, with model validation throughout.
Decision Analytics
Decision-making under uncertainty, prescriptive analytics, optimisation and simulation methods to support structured business decisions.
Business Analytics for FinTech
Where finance meets business analytics: improving portfolio performance and valuation accuracy from a trader or fund manager's perspective, detecting fraud, and sharpening financial projections with analytics tools.
FinTech and Financial Intermediation
Emerging FinTech trends in financial intermediation, from digital transformation to responsible innovation, across banking, real estate and insurance.
Advanced Project Management
Project management skills for the final industry project: defining KPIs, assessing risk, monitoring progress, evaluating process and reporting.
Consultancy Practice
Professional skills for consulting: communication, case practice, interviewing, networking and business etiquette, plus teamwork, conflict management and cultural awareness.