Skip to 0 minutes and 6 secondsHi everyone and welcome to our Big Data Analytics collection of courses. My name is Kerrie Mengersen. Why is statistical inference and machine learning approaches important for analysing Big Data? To answer this question, I want to draw your attention to the world’s largest coral reef system, and one of Australia’s biggest natural wonders, the Great Barrier Reef. The Great Barrier Reef is composed of over 2900 reefs and 900 islands, spanning over 2300km, and is one of the most diverse ecosystems on the Earth. However, because of its large size, monitoring and predicting different trends in the reef is really difficult.
Skip to 0 minutes and 50 secondsHere at QUT we’re developing mathematical and statistical models that use Big Data to help better understand environmental impacts and trends in biodiversity on the Great Barrier Reef. Both statistical inference and machine learning play a huge role in modelling information and making predictions using all of this reef data. For example, here at QUT we’re using machine learning approaches to design robots to seek out and control the damaging crown-of-thorns starfish. In this course we show you how to apply certain predictive analysis, dimension reduction, clustering, and machine learning techniques to analyse big data and make informed decisions.
Skip to 1 minute and 37 secondsWe not only explain these concepts, but we also provide a hands on approach that will help you better your programming skills using selected Big Data frameworks. Here we draw from the multi-faceted approach we use at ACEMS to provide you with a unique course on big data that meets the demand for analytics across a variety of different fields. We hope you enjoy the course as much as we have enjoyed creating it.