Essential Mathematics for Data Science and Machine Learning: Using R

This course is designed to help you get up to speed on the key concepts and notation on which machine learning an AI are based. This course is not a full math curriculum. It’s not designed to replace school or college math education. Instead, it focuses on the key mathematical concepts that you’ll encounter in studies of machine learning.

We’ll start with some basic algebra to get started with equations and functions, then we’ll dive into some differential calculus to explore derivatives and optimisation. We’ll also look at some linear algebra and cover vectors and matrices, before finally getting to grips with some statistics and probability.

On completion of this course, you will be able to:

Apply basic Mathematical principles required in Data Analytics Demonstrate your understanding of Algebra Fundamentals Demonstrate your understanding of Quadratic Equations and Functions Demonstrate understanding of Differential Calculus Foundations Demonstrate understanding of Vectors and Matrices Demonstrate understanding of Statistics and Probability

This course is designed to fill the gaps for students who missed the key concepts as part of their formal education, or who need to refresh their memories after a long break from studying math.

Individuals in the following roles will also find this course useful:

Data Analysts Programmers

This course is designed to fill the gaps for students who missed the key concepts as part of their formal education, or who need to refresh their memories after a long break from studying math.

Individuals in the following roles will also find this course useful:

Data Analysts Programmers

• Applied Familiarity with Equations, Functions, and Graphs
• Calculated Differentiation and Optimization
• Identified Vectors and Matrices
• Described Statistics and Probability