This course introduces core concepts and skills in data analysis to those who are absolute beginners in the area. It is accessible for those with no experience of programming, no mathematics since high school, and no experience or training in data analysis.
The course combines basic theoretical and practical components, presented in a gentle, accessible way. The focus is on intuition, simple language, pictures, and experience—rather than formulas, mathematical jargon, and rote learning.
Course outline
Students will learn to input, process, and analyse data with a range of analytical and visualisation tools.
The course begins by covering types of data, data acceptance, input, processing, and transformation. It delivers a foundation in basic statistics, taught in an intuitive, accessible way that simplifies the learning experience. The instructor uses practical examples to give students valuable and engaging hands-on experience, providing a context in which theory is immediately relevant.
Risk analysis and probability theory will be taught using an intuitive, language-based approach that students will find familiar. The intuitive concepts presented will then be translated gently to the numeric domain.
Topics further into the course include key data-analysis techniques such as regression, correlation, spatial statistics, and time series. Practical exercises accompany discussion of each topic, building on the gentle, visual framework established in previous components.
A final core component of the course introduces concepts in business intelligence and reporting, including data summarisation, “slice and dice” analysis, and reporting of key performance and risk indicators.
Optional components, which may be presented depending on class interest and time available, include:
- how to easily create spectacular interactive animations
- social network visualisation and analysis
- geospatial mapping
- advanced time series forecasting and visualisation
Participants will use Microsoft Excel and the world’s most commonly used data analytics tool, R, which is readily available for free download and installation.
Core topics
- Working with numbers
- Time series and forecasting
- Data basics
- Input a dataset
- Data preparation
- Summaries
- Measuring risk
- Reporting: Metrics and KPIs
- Making the numbers come alive: Animation
Equipment
Windows PCs running Excel and R with practical examples from all core components will be provided to attendees.
Prerequisites
This is a course for absolute beginners. There are no prerequisites.
Course instructor
Presciient director Dr Eugene Dubossarsky or another Presciient instructor will lead the course.
Dr Dubossarsky is the head of the Sydney Users of R Forum. He is also Principal Founder of Analyst First, an international analytics industry organisation. He is a founder of the Institute of Analytics Professionals of Australia (IAPA); Director, University of New South Wales School of Mathematics and Statistics Industry Advisory Board; and a recognised industry leader in business analytics. Eugene is an experienced analytics professional with 20 years’ experience programming in R and its parent language, S.
Testimonials
The Introduction to R course provided clear and logical assistance to getting up and running with R. More than that, the real value was in providing guidance on the myriad of online resources and introducing me to a network of passionate and helpful R users. Eugene is a knowledgeable and approachable teacher. I wouldn’t hesitate in recommending the course. I feel that I am now fully on the road to applying R and using data to improve efficiency across my organisation.
—James Orton, Data and IT Manager, UNICEF AustraliaThank you Eugene for advancing my R skills. I especially appreciate the time spent explaining the fundamentals of data manipulation — i.e. the code one needs to know before running any basic or sophisticated analysis. The pace of the workshop was perfect.
—Dr Chelsea Wise, Lecturer, Marketing, UTS Business School
Discounts
Please ask about our discounts for group bookings.
Feedback
Use enquiries@presciient.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.
Variation
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.
Cancellation
The course may be cancelled by the organisers with full refund of fees up to a week in advance of the scheduled commencement date.