Course code Title Language Price # Unit Startdate Hour Enddate Location Signup
R001 Getting started with programming in R English €425.00 1 Day(s) 04-12-2017 09u00 04-12-2017 Kontich Subscribe
R001 Getting started with programming in R Dutch €425.00 1 Day(s) 11-06-2018 09u00 11-06-2018 Kontich Subscribe
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Getting started with programming in R

Getting started with programming in R

Overview

Course code: 
R001
Duration: 
1
Time Unit: 
Day(s)
Overview: 

R started as a statistical programming tool, as the open source version of S. Unlike SPSS it requires some programming skills, since it is no drag and drop tool.
The CRAN repository holds numerous R packages where you can find several prepackaged functions which can turn out to be handy in many situations.
Because R requires some programming skills we start with a very basic course, offering you insight in the data types used in R, processing data with R, plotting, writing your own functions and scripts, …
This course is the first part of our R track: for more advanced R programming skills, we refer to the entire track or to the course “Data science and prediction models with R”.

Essentially, this course gives you a head start on programming with R

- Basic data types
- Converting data types
- Reading data online and offline
- Processing data with predefined functions
- Loading packages and using their functions
- All kinds of plotting with R
- Writing your own functions and scripts

Hands on exercises on all topics are offered

Learning objectives:
- Getting to know all data types and when best to use them
- Loading data in to R
- Learn simple data processing techniques and know how to use them with R
- Getting an idea of available plotting techniques in R and how to implement them
- Discover the CRAN repository
- Understand the advantage of user-defined functions and scripts

Topics

Topics: 

CHAPTER 1: Introducing R and RStudio
- What is R?
- An easy-to-use user interface: RStudio
- R support

CHAPTER 2: Data
- Data types available: list, array, matrix, data.frame, …
- Converting data types
- When to use which data type
- Loading data from your own computer
- Loading data from the internet

CHAPTER 3: Data processing
- Descriptive statistics
- Cleaning data
- Sampling

CHAPTER 4: The CRAN repository
- Searching on CRAN
- Loading packages
- Hands on with packages

CHAPTER 5: Plotting
- The plot function
- ggplot2

CHAPTER 6: Re-using code
- Loops
- Loops compared to apply
- Writing UDFs
- Writing Scripts

Prerequisites

Prerequisites: 

R can be regarded as a programming language. No knowledge is required though. We will start slowly with all programming skills, trying to offer a hands on head start for everyone.

Audience

Audience: 

R started as a statistical tool, but many machine learning techniques are available as well. Everyone who is willing to use descriptive statistics, more general statistics and machine learning techniques can benefit from the usage of R. This course offers no insight in these techniques, but if you are willing to use these techniques with R and you have no to limited programming skills, then this course is the right introduction on R before turning to the more fancy stuff.