Course Outline
Day One: Core Language Concepts
- Course Overview
-
Understanding Data Science
- Defining Data Science
- The Data Science Workflow
- Introduction to the R Language
- Variables and Data Types
- Control Structures (Loops and Conditionals)
-
R Scalars, Vectors, and Matrices
- Defining Vectors in R
- Matrices
-
String and Text Manipulation
- Character Data Types
- File Input/Output
- Lists
-
Functions
- Introduction to Functions
- Closures
- lapply/sapply Functions
- DataFrames
- Practical Exercises for All Sections
Day Two: Intermediate R Programming
- DataFrames and File I/O
- Importing Data from Files
- Data Preparation
- Built-in Datasets
-
Data Visualization
- Graphics Package
- plot() / barplot() / hist() / boxplot() / Scatter Plots
- Heat Maps
- ggplot2 Package (qplot(), ggplot())
- Data Exploration with dplyr
- Practical Exercises for All Sections
Day Three: Advanced Programming with R
-
Statistical Modeling in R
- Statistical Functions
- Handling NA Values
- Distributions (Binomial, Poisson, Normal)
-
Regression Analysis
- Introduction to Linear Regression
- Recommendation Systems
- Text Processing (tm package / Word Clouds)
-
Clustering
- Introduction to Clustering
- KMeans
-
Classification
- Introduction to Classification
- Naive Bayes
- Decision Trees
- Training Models using the caret Package
- Algorithm Evaluation
-
R and Big Data
- Connecting R to Databases
- The Big Data Ecosystem
- Practical Exercises for All Sections
Requirements
- A foundational background in programming is recommended
Environment Setup
- A modern laptop
- Installation of the latest R Studio and R environment
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
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Testimonials (7)
I finally understood the idea of the pipes and how to use R in our work context.
Katrin Groth - Senatsverwaltung fur Bildung, Jugend und Familie
Course - Data Analytics With R
The real life applications using Statcan and CER as examples.
Matthew - Natural Resources Canada
Course - Data Analytics With R
His knowledge, and the codes were already written in the files so I could study after the classes and practice on my own.
GLORIA ADANNE - Natural Resources Canada
Course - Data Analytics With R
Lots of R coding provided and good examples
Kasia - Natural Resources Canada
Course - Data Analytics With R
Extensive language and well-developed. Also a wealth of supporting information available online.
Michel - Natural Resources Canada
Course - Data Analytics With R
I liked that the trainer made sure we all understood and were following the lectures. if we had a problem, he stopped and helped us fix it.
Cesar - AMERICAN EXPRESS COMPANY MEXICO
Course - Data Analytics With R
The tool was interesting and I see the use. I would like to learn about more about it.
