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Learn Linear Algebra for Data Science (Mini-Course)

Learn Linear Algebra for Data Science (Mini-Course)

Learn Linear Algebra for Data Science (Mini-Course)

Welcome to this mini-course on Linear Algebra for Data Science!

This mini-course is an extra read for the data science specialization track and is designed to be a quick refresher on some of the basic concepts of Linear Algebra. This course was contributed by Samuel Minihane for The Click Reader.

Objectives of the course

The learning objectives of the course are set out as follows:

  • Learn about matrices
  • Learn how to apply numerical operations on matrices
  • Learn how to perform matrix multiplication and find dot products
  • Learn how to find the transpose, determinant as well as the inverse of a matrix

Pre-requisites for the course

If this is your first time learning mathematics, it may be hard for you to effectively grasp all the concepts mentioned in this mini-course. However, this is a completely beginner-friendly course aimed at helping you understand the basics of Linear Algebra needed for the data science specialization track.

A message from the course contributor – Samuel Minihane

“Hi! I’m Sam. I’m in my final year of a masters degree in theoretical physics at a Russel Group university in the UK. My bachelors and masters work are both focused on dark matter direct detection.

I’ve always wanted to pursue a PhD and in the last year or so, my interests have moved away from theoretical physics and more into the realm of data science. I’m fascinated by data and the amount of information contained within data sets if you know where to look. During my time learning, I have fallen in love with the field.

Like a lot of people, I have used free online resources, like The Click Reader, to aid me in the learning process. This free course is my way of getting involved and giving back to the community with the expertise I possess.

I hope you all enjoy the course and learn a lot!”

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Kharpann was founded by a team of mathematicians, programmers and machine learning/artificial engineers with a vision to help businesses find their data science team faster and to help them grow with their own data.
Price Free
Instructor Kharpann
Duration 2 hours
Lectures 6
Enrolled 1 student
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