Statistical Foundations for ML in R

  • Learn the core concepts of statistics for Data Science and learn how to implement them in R

starstarstarstarstar_half 4.8 (41 ratings)    329 Students

Created by Selva Prabhakaran

  • Last updated 05/2021

  • English

  • English captions

What you will learn

01

Central Limit
Theorem

02

Law of large
numbers

03

Univariate
Analyses

04

Normal
Distribution

05

Standard Deviation and
Error

06

Confidence
Interval

07

Bi-variate
analyses

08

Statistical Significance
Tests

Course Curriculum

Requirements

  • Courses Page1 Basics of R Programming
  • Courses Page1 High School Maths

Who should attend this course?

  • Data Science Aspirants

  • Data Science Professionals

  • Software/Data engineers interested in quantitative analysis

  • Professionals working with large datasets

  • Data analysts, economists, researchers

Instructor

Selva Prabhakaran Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I’ve put up the series of courses and projects with detailed explanations – just like an on the job experience. Hope you love it!

  • 4.5+Instructor rating

  • 200+ reviews

  • 10K+students

  • 15+ Courses

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