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Fundamentals of Machine Learning

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.

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Learning Objectives

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

Pre-Requisites

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

Course Content

  •   Machine Learning: Method
  •   R: Higher Dimensions
  •   Data Preparation in R
  •   Mathematics: Machine Learning
  •   Machine Learning: Regression in R
  •   Machine Learning: Simulation in R
  •   Machine Learning: Validation in R
  •   Mathematics: Algorithms
  •   Machine Learning: Techniques

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Virtual Classroom

Virtual classrooms provide all the benefits of attending a classroom course without the need to arrange travel and accomodation. Please note that virtual courses are attended in real-time, commencing on a specified date.

Virtual Course Dates

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