Learning by doing
Trainers with practical experience
Detailed course material
Clear content description
Tailormade content possible
Training that proceeds
In the course Data Analysis with R you will learn programming in the R language and how you can use R for data analysis and visualization. R has become a standard platform for data analysis and data visualization and can perform a huge range of statistical procedures. In the course Data Analysis with R a series of coherent R packages are used, known as the tidyverse. These packages share an underlying design philosophy, grammar and data structures and are especially suitable for data science.
The course Data Analysis with R starts with the installation of R and the R Studio development environment. The basic syntax of R and the installation of R packages are also discussed.
Next you will learn how you can quickly gain insight into the data with the ggplot2 package by means of plots. The different plot types, themes and layouts are discussed as well.
Then it is time for the dplyr package with which common data transformation problems such as filtering, sorting, summation and grouping can be solved.
Presenting data with the rmarkdown package is also covered. As well as tidying raw data with the tidyr package, where columns become variables and rows become observations.
Time series occur in many data sets. The processing of these time series is addressed with the lubridate package that has many useful functions for processing dates and time.
Part of the course program is also the import of data from CSV files and file formats from other statistical packages such as SPSS or SAS. Reading from and writing to databases is also treated.
Finally the course Data Analysis with R deals with statistical analysis models such as linear and non-linear models, variable transformations and regressions. All this is supported with many practical examples and can also be applied to cases that are brought along by the students.
The course Data Analysis with R is intended for Big Data analysts and scientists who want to use R to analyze their data and to make static analyzes.
Experience with programming is beneficial to good understanding but is not required.
The theory is discussed on the basis of presentations and examples. The concepts are explained with demos. Then there is time ample to practice with it yourself. R-Studio is used as a development environment. Course times are from 9:30 am to 16:30 pm
After successful completion of the course the participants receive an official certificate R Programming.
Module 1 : Intro R
Module 2 : Graphics and Plots
Module 3 : Transformations
Overview of R
History of R
The R Community
Using R Packages
Graphics Devices and Colors
High-Level Graphics Functions
Low-Level Graphics Functions
Controlling the Layout
Changing Plot Types
Quick Plots and Basic Control
Changing Plot Types
Themes and Layout
Functions for Numeric Data
Module 4 : Presentation
Module 5 : Data Cleaning
Module 6 : Date Times
Family of apply Functions
Time and Date Variables
Setting a datetime
Getting values from a datetime
Time Series Analysis
Module 7 : Data Import
Module 8 : Linear Models
Module 8 : Non-Linear Models
Importing CSV Files
Import from Text Files
Import from Excel
Import from Spss or SAS
Connecting to a database
Connecting to a cluster
Databases and ODBC
What is a model?
Statistical Models in R
How to evaluate a model?
How to use a model?
Simple Linear Models
Optional material :
Interactive dashboards with Shiny
All our courses are classroom courses in which the students are guided through the material on the basis of an experienced trainer with in-depth material knowledge. Theory is always interspersed with exercises.
We also do custom classes and then adjust the course content to your wishes. On request we will also discuss your practical cases.
The course times are from 9.30 to 16.30. But we are flexible in this. Sometimes people have to bring children to the daycare and other times are more convenient for them. In good consultation we can then agree on different course times.
We take care of the computers on which the course can be held. The software required for the course has already been installed on these computers. You do not have to bring a laptop to participate in the course. If you prefer to work on your own laptop, you can take it with you if you wish. The required software is then installed at the start of the course.
Our courses are generally given with Open Source software such as Eclipse, IntelliJ, Tomcat, Pycharm, Anaconda and Netbeans. You will receive the digital course material to take home after the course.
The course includes lunch that we use in a restaurant within walking distance of the course room.
The courses are planned at various places in the country. A course takes place at a location if at least 3 people register for that location. If there are registrations for different locations, the course will take place at our main location, Houten which is just below Utrecht. A course at our main location also takes place with 2 registrations and regularly with 1 registration. And we also do courses at the customer’s location if they appreciate that.
At the end of each course, participants are requested to evaluate the course in terms of course content, course material, trainer and location. The evaluation form can be found at https://www.klantenvertellen.nl/reviews/1039545/spiraltrain?lang=en. The evaluations of previous participants and previous courses can also be found there.
The intellectual property rights of the published course content, also referred to as an information sheet, belong to SpiralTrain. It is not allowed to publish the course information, the information sheet, in written or digital form without the explicit permission of SpiralTrain. The course content is to be understood as the description of the course content in sentences as well as the division of the course into modules and topics in the modules.