Current courses
Sydney
5–13 November 2015
Introduction to R and data visualisation
Tuesday 10–Wednesday 11 November 2015
R is the world’s most popular data mining and statistics package. It’s also free, and easy to use, with a range of intuitive graphical interfaces. This two-day course will introduce you to the R programming language, teaching you to create functions and customise code so you can manipulate data and begin to use R self-sufficiently in your work.
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Predictive analytics and data science for big data
Thursday 12–Friday 13 November 2015
Data science, predictive modelling and big data skills are of vital and growing importance in commercial, government, and not-for-profit contexts, particularly for managers and those in risk, customer and IT functions. Learn the fundamentals of predictive modelling, including coverage of generalised linear models, support vector machines, decision trees, gradient boosting machines and neural networks. This course also covers a range of other key data mining tools including principal components analysis, cluster analysis, and more.
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Data analytics for fraud and anomaly detection, security and forensics
Tuesday 3–Wednesday 4 November 2015
This course introduces attendees to a range of data analysis methods for the detection of fraud, abuse and suspicious behaviour. It provides key concepts and hands on practice with a range of readily available and free tools, including Microsoft Excel and R, a powerful open source data analysis tool. Suitable for all practitioners in fraud detection, law enforcement, security, compliance, insurance, audit and the finance function who are seeking an introduction and hands-on experience with data analysis techniques.
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Advanced R
Thursday 5–Friday 6 November 2015
This course is for R users, already applying the tool in real-world applications, who are looking for more efficient and powerful ways to: manipulate data and automate their analysis and research, develop R applications, speed up their R application, and make use of wider memory stores. It introduces attendees to a range of methods for advanced data processing, speeding up R code, scaling R to hard disk memory, and advanced programming.
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