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Fundamentals of Mathematics and Statistics

An introduction to R, and a broad coverage of mathematics for Data Science and Machine Learning: algebra, linear algebra, calculus, probability and statistics.

This 3-day course is designed for anyone who's going to make a career working in data. It is practical in nature and will take you through the most common mathematical statistical models that you're going to need to thrive as a data scientist or data analyst.

Whether you work with Excel, SQL, Hadoop, or any other data solution, you're going to be able to understand a model more effectively with mathematics. You'll learn to improve existing statistical models and start developing the right skills to ask more advanced questions.

Target Audience:

Aimed at fledging data scientists who wish to have a proper understanding of the underlining mathematics and algorithms behind Machine Learning and data analytics.


Learning Objectives

At the end of this course attendees will know:

  •   Fundamentals of algebra, linear algebra, calculus which are needed for understanding data science and machine learning techniques
  •   Probability and statistics essential for data analytics

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

  •   Apply mathematics and statistical analysis using R
  •   Explore data with R
  •   Perform statistical inference and extract insight from data


  •   GCSE mathematics or above
  •   An interest in mathematical and logical thinking
  •   No prior experience of R is assumed, although prior experience will be an advantage

Course Content

  •   R: Intro
  •   R: Data
  •   R: Containers
  •   R: Higher Dimensions
  •   Introduction to Mathematics
  •   Mathematics: Probability
  •   Mathematics: Statistics
  •   Mathematics: Advanced
  •   Data Science and Exploration in R

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