An introduction to R and data analytics, with a deeper Introduction to Machine Learning.

This 3-day course will enable you to better understand what Machine Learning is, including the fundamental practices and principles. At the end of the course you'll be able to create simple Machine Learning models using Python and R.

Target Audience

Aimed at people with existing technological and mathematical background looking to get a quick exposure to mathematics and techniques of Machine Learning.


Delegates wish to take this course should have already completed 'Fundamentals of Data Science' or have the equivalent level of knowledge.

Learning Outcomes

At the end of this course attendees will know:

  • The fundamentals of Machine Learning methodologies and algorithms
  • The mathematics required for understanding and using Machine Learning algorithms
  • R Machine Learning packages

At the end of this course attendees will be able to:

  • Build Machine Learning models using R
  • Perform regression analysis
  • Perform computer simulations using R
  • Perform validation of Machine Learning models using R to evaluate the quality of models

Course Outline

  • Intro to Science, Data Science and Big Data
  • Intro to Machine Learning
  • Intro to Mathematics
  • Intro to Statistics
  • Intro to Python
  • Intro to Python for Data Science
  • Machine Learning with Python

Azure Learning Paths

Want to boost your career in Azure? Click on the roles below to see QA‘s learning pathways, specially designed to give you the skills to succeed.

= Required
= Certification
Data Scientist
Data Engineer AI Developer
Developer .NET Experience
Architect Enterprise Architecture Experience
Administrator DevOps Windows Administration Experience
Administrator Security Windows Administration Experience
Administrator Architect Windows Administration Experience
Developer Average salary: £57,500*

7 days

Administrator DevOps Average salary: £50,250*

7 days

Administrator Security Average salary: £50,250*

6 days

Key for bundle contents
= Exam Preparation
= Exam
= Practice Exam
= Exam Voucher
= Tutor Support
= Pre Course Work
*This is based on QA research