R language Nexacu

R Programming - Intermediate Course - Manila

Learn to use R more efficiently

 

There are often many ways to achieve a result using R, learn how to run analysis more efficiently:
  • create your own functions
  • control structures
  • loops and loop alternatives
  • tidyverse piping syntax
  • create visualisations with ggplot2
You will work alongside our Data Analytics lead, Tamara Shatar, as you complete exercises throughout the day to cement your understanding of these concepts. The skills you learn on the day will empower you to build your own solutions in R.

Build on your base knowledge of the R language and learn how to run data analysis more efficiently. Remote Courses in Manila.

R Programming - Intermediate Course - Manila

R language Nexacu
Build on your base knowledge of the R language and learn how to run data analysis more efficiently. Remote Courses in Manila.
₱ 25,300
10 max
1 day

Frequently Asked Questions

Meet your Trainer

Trainer Tamara Shatar

Tamara Shatar holds a PhD in Agricultural Data Science. She has extensive experience, including many years working as a research scientist focused on data analysis, modelling using machine learning, simulation and other techniques. While working in both academia and at the Australian CSIRO, part of her role included teaching a variety of data analysis skills. Tamara has designed our first Data Analytics Training Course, Using R, to provide beginners with the fundamental tools necessary to start using R for data analysis. She is consistently well reviewed by her students. 

"The course was really good, Tamara is an excellent trainer and was able to answer my questions, the resources she provided to help after the course are excellent. I was a bit overwhelmed at the beginning trying to learn a new language, but Tamara put me at ease and went through the content at a pace that I could understand." - R Basics Brisbane, Australia 

What is Remote Training?

We offer some of our more specialist courses in a remote format. At Nexacu, this means you will learn the same content as you would in our classrooms and the same trainer will deliver training but all students will log in from their own premises and device. Our Data Scientist, Tamara will host the Data Analytics training sessions, walking you through the basics of R and answering questions and encouraging discussion along the way.


Why Learn R? 

Rather than being a point and click tool, R is a language that is used by writing reusable scripts, enabling automation and repeatable workflows. Because it is a language, it offers a huge amount of flexibility in manipulating data and the ability to write new functions. Even without a background in programming, it is relatively easy to get up and running once you know the basics. 

R Programming Intermediate Manila Course Details

Price
₱ 25,300
Duration
1 day
Times
9am - 4pm ( approx )
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Live Online
Address
Level 40 PBCom Tower
6795 Ayala Avenue Corner V.A.
Rufino Street
Makati City
Makati 1226
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R Programming Course Outlines

  • Machine Learning in R
  • R Programming Certification
  • Machine Learning in R Certification
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Course Rating
R Programming Training Courses

4.72 5 R Programming Training Courses
4.72 out of 5
31197 Student Reviews

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What do I need to know to attend?

  • You should have completed our Fundamentals of R and R Beginner course or have basic familiarity with R.
  • You will not be expected to code unassisted but will learn more and participate more easily if you have at least a fundamental understanding of R syntax.
  • Basic understanding of statistics (mean, median, standard deviation, variance).

R Programming Intermediate Manila Learning Outcomes

You will develop a better understanding of R and be able to:

  • write custom functions
  • write more concise code


  • use functionals, loops and other control structures
  • create graphics with ggplot2.

R Programming Intermediate Manila Course Content

  • Working more efficiently in R
  • How to work more efficiently in R
  • Vectorization
  • Using better functions
  • Concise code
  • Reusable scripts
  • Custom functions
  • Loops and other control structures
  • Loop alternatives
  • Functions to reduce typing
  • Printing objects after creating
  • with and within
  • Inserting multiple quotation marks
  • Create your own functions
  • Why write your own functions?
  • Basics of functions
  • What is a function?
  • Creating your own functions
  • Syntax for writing your own function
  • More complex functions
  • Ellipses and further arguments
  • Scope
  • Loading your functions
  • Loops and control structures in R
  • If and if else
  • Loops for loops
  • Saving results from a loop
  • Improving your code
  • While loops
  • Repeat loops
  • Loop alternatives
  • Functionals
  • apply functions
  • split
  • map functions
  • map variants
  • Returning a vector
  • walk
  • Loop, apply or map?
  • Tidyverse piping syntax
  • Purpose
  • Using the pipe
  • Pipe variants
  • The tee operator
  • The exposition operator
  • Plotting with ggplot2
  • The grammar of graphics
  • Required components
  • Using ggplot()
  • Scatterplot
  • Line chart
  • ggplot2 resources

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