Programming in R - Virtual Classroom

Date: Tuesday 15 September 2020 9.00AM - Friday 18 September 2020 1.00PM
Location: Online
CPD: 12.0 hours
RSS Training
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This tutor lead virtual course is delivered over four mornings and is an intensive course on programming principles in R. During the course participants will gain experience of writing their own functions and scripts for undertaking bespoke data analysis tasks in R. Consideration of memory allocation, code profiling and leveraging parallel computation will also be explored to guide participants in the principles of efficient R programming.

All the required software is provided online.

 

Course Outline

This tutor lead virtual course is delivered over four mornings and is an intensive course on programming principles in R. During the course participants will gain experience of writing their own functions and scripts for undertaking bespoke data analysis tasks in R. Consideration of memory allocation, code profiling and leveraging parallel computation will also be explored to guide participants in the principles of efficient R programming.

All the required software is provided online.

 

Learning Outcomes

By attending the course participants will gain experience in writing their own functions and scripts for data analysis in the R programming language. They will improve on their data manipulation skills. Further, attendees will also gain an understanding of how to make code more efficient and to extend their workflow to leverage the power of parallel computing.
 

Topics Covered

  • Data manipulation and aggregation using dplyr
  • Control flow: conditional expressions, functional composition, for loops
  • The 'apply' family of functions
  • Efficient data structures
  • Code Profiling
  • Avoiding loops
  • Parallel computing
 

Target Audience

This course is idea for anyone who would like to extend their basic familiarity with using R, and using R to write their own bespoke functions or optimizing their code.
 

Assumed Knowledge

Basic prior experience with the R programming language is assumed. Namely that participants have some experience of R data structures, such as vectors, data frames, and experience in using pre-made functions from R packages.

The course is aimed as a follow up the 'Introduction to R and Regression Modelling in R' training course.
Whilst no statistical knowledge will be assumed, some of the examples will be statistical in nature.
 

The course tutor will be one of the following:

Dr Colin Gillespie

Colin is a statistics lecturer at Newcastle University and is often employed as an R consultant by Jumping Rivers. He has been using R since 1999 and teaching R programming for the last eight years. Colin has authored a number of R packages and regularly answers R questions and is a top contributor on stackoverflow.
 

Dr Jamie Owen

Jamie has a PhD in statistics and has since worked as a trainer and consultant at Jumping Rivers. He has approximately 10 years of experience programming in R and has developed and delivered training courses ranging from introductory to advanced topics in R programming to a variety of audiences spanning undergraduates, postgraduates and industry professionals from 2 to 200 people.

 

Fees

   

Registration before
15 August 2020

 

Registration on/after
 15 August 2020

                                  

Non Member 

RSS Fellow 

RSS CStat/Gradstat also MIS & FIS

 

£611.00+vat 

£520.00+vat 

£490.00+vat

£680.00+vat 

£577.00+vat 

£543.00+vat

 
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