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Advanced R: Melbourne, 27–28 August 2018
27 August 2018 @ 9:30 am - 28 August 2018 @ 5:00 pm
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This class builds on the introductory R class, providing students with powerful, modern R tools including pipes; the tidyverse—featuring the powerful dplyr and tidyr packages for data manipulation, along with many other packages that make coding for data analysis easier, more intuitive and more readable; and the tibble data type that makes it possible.
The course will also provide a deeper view of functional programming in R, which also allows cleaner and more powerful coding.
R Markdown and R Notebooks allow the creation of readable and presentable documents as well as a transparent, interactive record of your work.
Finally, the shiny package is introduced as a powerful method for creating browser-based dashboards, interactive applications and graphical user interfaces to R code.
Earlybird pricing is available until 13 August 2018.
Group discounts also apply during the earlybird period: 5% for 2–4 people, 10% for 5–6 people, 15% for 7–8 people, and 20% for 9 or more people. Select your desired quantity of tickets and click “Add to cart” to see the discount calculated before checkout.
Having studied stats at Uni I was surprised how far the field has progressed in the last few years, particularly in the area of big data. The great thing about Eugene’s course is I left with a sense that I was up to date with the latest big data modelling concepts but more importantly could also deploy them with some confidence using R. Eugene also made it clear he was available to answer questions after the course, so you are not left hanging. I would absolutely recommend this!
—Damon Rasheed, CEO, Rate Detective
For someone who does not come from an IT background R is a terrifying program. Before doing the Introduction to R course I had previously done other courses in R but always found myself in over my head because they assumed a high level of program experience (even course that required no prior programming knowledge). This course is not like that at all. It starts at ground zero and teaches you everything you need to know to be able to use R confidently in your everyday workplace. It is a must attend for anyone who wants use R!
Data science can be a challenging topic but Eugene’s “Introduction to Machine Learning” course turns complex statistical models into plain English. The course contents and presentation were accessible and I enjoyed the mixture of hands-on rattle() exercises, the challenge of building multiple models with real life data, and the salient theory whiteboard discussions created many “aha” moments.
It was a great introductory course and it gave me with a better grasp of Machine Learning in general, a great framework for thinking about it and practical hands-on skills that I can put to immediate use. I wish I had done this course sooner.
—Charl Swart, Director of Business Operations, Unisys Credit Services
Courses are taught by Dr Eugene Dubossarsky and his hand-picked team of highly skilled instructors.
Questions and further details
Use email@example.com to email us any questions about the course, including requests for more detail, or for 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 advertised due to demands and learning pace of attendees. Additional material may be presented, along with or in place of advertised.
Cancellations and refunds
You can get a full refund if you cancel 2 weeks or more before the course starts. No refunds will be issued for cancellations made less than 2 weeks before the course starts.
Meals and refreshments
Catered morning tea and lunch are provided on both days of the course. Please notify us at least a week ahead if you have any special dietary requirements.
Frequently asked questions (FAQ)
Do I need to bring my own computer?
There’s no need to bring your own laptop or PC. Our courses take place in modern, professional training facilities that have all the computing equipment you’ll need.
I’m lost! How do I find the venue?
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For any enquiries, please call +61 4 1457 3322.
If you prefer, you can pay by invoice rather than credit card. Just select “Pay by invoice” at the checkout.