With the advent of automation, humans’ role has become to do what computers cannot. Many more white-collar workers—perhaps all of them—will end up “working with data” to some extent.
Using data to provide insights and guidance that computers alone cannot requires “data literacy”, which is doubly important for anyone working alongside, supporting, leading, or hiring a data-science and analytics team.
Data literacy involves a broad range of skills, including:
- an appreciation of the language of data
- understanding uncertainty (expressed as probabilities) and complexity
- interpreting relationships in data (multivariate correlation) and visual representations of them
- reading visual representations of data
It also includes the ability to think rigorously and abstractly about evidence-based decision-making and manipulate data accordingly.
This course introduces a range of skills and applications related to critical thinking in such areas as forecasting, population measurement, set theory and logic, causal impact and attribution, scientific reasoning and the danger of cognitive biases.
It is highly recommended for managers and workers who have not had quantitative work as the basis of their career to date, and for many IT professionals. The main tool used will be Microsoft Excel, and other tools for data manipulation, analysis and visualisation will also be introduced. There are no prerequisites beyond high-school mathematics; this course has been designed to be approachable for everyone.
Computers running R with practical examples from all core components will be provided to attendees. These may not necessarily be configured for the most advanced topics, which may involve demonstrations only, especially if requiring server or cloud functionality.
Courses are taught by Dr Eugene Dubossarsky and his hand-picked team of highly skilled instructors.
There are no prerequisites beyond high-school mathematics; this course has been designed to be approachable for everyone.
Please ask about our discounts for group bookings.
Use email@example.com to email us any questions about the course, including requests for more detail, specific content you would like to see covered, or queries regarding prerequisites and suitability. If you would like to attend but for any reason cannot, please also let us know.
Course material may vary from what is advertised due to the demands and learning pace of attendees. Additional material may be presented along with or in place of what is advertised.
The course may be cancelled by the organisers with full refund of fees.