Course Outline
Day One: Foundational Language Concepts
- Course Overview
-
Introduction to Data Science
- Defining Data Science
- The Data Science Workflow
- Introduction to the R Language
- Variables and Data Types
- Control Flow (Loops and Conditional Statements)
-
R Scalars, Vectors, and Matrices
- Creating R Vectors
- Working with Matrices
-
String and Text Manipulation
- Character Data Types
- File Input/Output
- Lists
-
Functions
- Introduction to Functions
- Closures
- Using lapply/sapply functions
- DataFrames
- Practical Exercises for all sections
Day Two: Intermediate R Programming
- DataFrames and File I/O
- Importing data from external files
- Data Cleaning and Preparation
- Utilizing Built-in Datasets
-
Data Visualization
- Base Graphics Package
- Functions: plot(), barplot(), hist(), boxplot(), and scatter plots
- Heatmaps
- The ggplot2 package (qplot(), ggplot())
- Data Exploration with dplyr
- Practical Exercises for all sections
Day Three: Advanced Programming in R
-
Statistical Modelling with R
- Statistical Functions
- Handling Missing Values (NA)
- Probability Distributions (Binomial, Poisson, Normal)
-
Regression Analysis
- Introduction to Linear Regression
- Recommendation Systems
- Text Processing (tm package and Word Clouds)
-
Clustering
- Overview of Clustering Techniques
- K-Means Clustering
-
Classification
- Overview of Classification Methods
- Naive Bayes
- Decision Trees
- Model Training with the caret package
- Evaluating Algorithm Performance
-
R and Big Data
- Connecting R to Databases
- The Big Data Ecosystem
- Practical Exercises for all sections
Requirements
- A foundational understanding of programming concepts is recommended
Environment Setup
- A compatible, up-to-date laptop
- Installation of the latest RStudio and the 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 3900 € + VAT*
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Testimonials (7)
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.
- Teleperformance
Course - Data Analytics With R
New tool which is “R” and I find it interesting to know the existence of such tool for data analysis.
