Welcome to our training catalog. All courses are provided in-house and the courses listed below can be mixed to meet your needs.

Please contact us to discuss what courses would best match your requirements and if you have any questions on specific courses or course categories.

 

R for Data Science

R for Data Science Image

This full-day in-person, hands-on workshop provides participants with information on using R for Data Science. It is intended for people who already have a programming background. The workshop is structured as follows:

Morning – Theory:
Review of R as a programming language:
History and comparison with other languages (e.g. Python)
Programming environment options – R Studio, R Markdown
Overview of key packages: Statistical Packages, Machine Learning Packages, TidyVerse (data processing + visualization), Shiny
Programming basics – conceptual overview
Brief Review of Relevant Statistical Concepts:
Descriptive Statistics
Statistical Modelling
Comparison between Statistics and Machine Learning

Afternoon – Hands-On:
Quick hands-on walk through of R command-line and R-Studio (e.g. running scripts, installing packages)
Getting into R program – with Pre-Worked Examples in R-Markdown
Practice Exercises and Lab Time

Category:
AI/ML Toolbox
Tags:
Machine Learning and AI 101
Product Code:
AI-5
Course Duration (hours):
6

R for Data Science

R for Data Science Image

This full-day in-person, hands-on workshop provides participants with information on using R for Data Science. It is intended for people who already have a programming background. The workshop is structured as follows:

Morning – Theory:
Review of R as a programming language:
History and comparison with other languages (e.g. Python)
Programming environment options – R Studio, R Markdown
Overview of key packages: Statistical Packages, Machine Learning Packages, TidyVerse (data processing + visualization), Shiny
Programming basics – conceptual overview
Brief Review of Relevant Statistical Concepts:
Descriptive Statistics
Statistical Modelling
Comparison between Statistics and Machine Learning

Afternoon – Hands-On:
Quick hands-on walk through of R command-line and R-Studio (e.g. running scripts, installing packages)
Getting into R program – with Pre-Worked Examples in R-Markdown
Practice Exercises and Lab Time