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Course Outline
Day One: Language Basics
- Course Introduction
-
About Data Science
- Data Science Definition
- Process of Doing Data Science.
- Introducing R Language
- Variables and Types
- Control Structures (Loops / Conditionals)
-
R Scalars, Vectors, and Matrices
- Defining R Vectors
- Matricies
-
String and Text Manipulation
- Character data type
- File IO
- Lists
-
Functions
- Introducing Functions
- Closures
- lapply/sapply functions
- DataFrames
- Labs for all sections
Day Two: Intermediate R Programming
- DataFrames and File I/O
- Reading data from files
- Data Preparation
- Built-in Datasets
-
Visualization
- Graphics Package
- plot() / barplot() / hist() / boxplot() / scatter plot
- Heat Map
- ggplot2 package (qplot(), ggplot())
- Exploration With Dplyr
- Labs for all sections
Day Three: Advanced Programming With R
-
Statistical Modeling With R
- Statistical Functions
- Dealing With NA
- Distributions (Binomial, Poisson, Normal)
-
Regression
- Introducing Linear Regressions
- Recommendations
- Text Processing (tm package / Wordclouds)
-
Clustering
- Introduction to Clustering
- KMeans
-
Classification
- Introduction to Classification
- Naive Bayes
- Decision Trees
- Training using caret package
- Evaluating Algorithms
-
R and Big Data
- Connecting R to databases
- Big Data Ecosystem
- Labs for all sections
Requirements
- Basic programming background is preferred
Setup
- A modern laptop
- Latest R studio and R environment installed
21 Hours
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*
Contact us for an exact quote and to hear our latest promotions
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
the clarity with which he explained the entire course, as well as the willingness to revisit topics in the syllabus when necessary
Carlos Eloy - AMERICAN EXPRESS COMPANY MEXICO
Course - Data Analytics With R
Machine Translated
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.
