Critical Evaluation in Data Science: Data, the World, and You

Learn how data analytics affects everyone with Adelaide University.

In an increasingly data-centric world, a working understanding of data analytics and quantitative methods is essential for all members of society.

What will you learn?

This six-week course will teach you fundamental data literacy skills and quantitative methods for dealing with data.

Armed with this knowledge, you’ll be able to interpret and critically evaluate claims you encounter in your day-to-day life.

Through case studies, you’ll explore the foundational concepts in data science and statistical thinking. You’ll also discover machine learning and data science methods, and understand both the possibilities and pitfalls of these emerging sciences.

Learn how to identify misleading statistics

When presented with claims in the media that are accompanied by statistics, diagrams, and outputs from technologies like AI and machine learning, how can we learn to not be fooled by these claims?

This course will help you understand misleading statistics and learn how to challenge them when they are presented to you.

Delve into sample, variability, and study design

Next, you’ll explore the different components of research including research questions, sampling, and variability.

Using case studies, you’ll explore how sampling can go wrong as you learn the best practices. You’ll then move on to study design to understand the types of studies you may encounter.

Unpack the rules for analysing data

On the final weeks of the course, you’ll explore how bias can infiltrate surveys. You’ll also discover basic rules for analysing and interpreting data to ensure a fair result is achieved.

Armed with this knowledge, you’ll have the confidence and quantitative reasoning skills to accurately read and interpret the data you are presented with in everyday life.

Who should study this data literacy course?

This course is designed for professionals who work with data to inform business decisions or recommendations and need to communicate insights clearly through reports and presentations. It’s ideal for those without a formal data science background who want to build data literacy and gain a competitive edge in data-driven roles.