You will learn through a combination of hands-on programming demonstrations in RStudio, video lectures, quizzes, readings and peer discussions.
Introduction to data science
Learn the disruptive business applications of data science including foundational analysis methods; explore a data mining framework; explore popular data science technologies; learn about data organisation for analysis.
Making predictions by classifying outcomes
Compare the classification methods of experts and machines; explore performance of predictive classification models.
Impactful data visualisations
Understand the power of advanced visualisations to persuade and influence audiences for effective communication across diverse sets of stakeholders; explore the physical characteristics of effective visualisations.
Supervised and unsupervised learning
Learn to differentiate between supervised and unsupervised learning as you explore how a model-building contest hosted by Netflix yielded predictive model performance improvements.
Making predictions by characterising relationships
Identify and describe business problems concerned with the strength and relationship among variables. Explore characteristics and evaluate the quality of predictive models to understand how data and models can inform business decisions.
Extracting meaning from text
Explore how and why language analysis can provide near-realtime feedback of customer opinions; learn about natural language processing methods; construct and test a predictive model to examine sentiment of text passages.