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Mathematics for Data Science and Machine Learning using R

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  • 975 Students
  • Updated 7/2019
  • Certificate Available
4.5
(122 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
10 Hour(s) 40 Minute(s)
Language
English
Taught by
Eduonix Learning Solutions, Eduonix-Tech .
Certificate
  • Available
  • *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
4.5
(122 Ratings)

Course Overview

Mathematics for Data Science and Machine Learning using R

Learn the fundamental mathematics for Data Science, AI &ML using R

With the increase of data by each passing day, Data Science has become one of the most important aspects in most of the fields. From healthcare to business, everywhere data is important. However, it revolves around 3 major aspects i.e. data, foundational concepts and programming languages for interpreting the data.  This course teaches you everything about all the foundational mathematics for Data Science using R programming language, a language developed specifically for performing statistics, data analytics and graphical modules in a better way.

Why Learn Foundational mathematical Concepts for Data Science Using R?

Data Science has become an interdisciplinary field which deals with processes and systems used for extracting knowledge or making predictions from large amounts of data. Today, it has become an integral part of numerous fields resulting in the high demand of professionals of data science. From helping brands to understand their customers, solving complex IT problems, to its usability in almost every other field makes it very important for the functioning and growth of any organizations or companies. Depending upon the location the average salary of data scientist expert can be over $120,000. This course will help you learn the concepts the correct way.

Why You Should Take This Online Tutorial?

Despite the availability of several tutorials on data science, it is one of the online guides containing hand-picked topics on the concepts for foundational mathematics for Data Science using R programming language. It includes myriads of sections (over 9 hours of video content) lectured by Timothy Young, a veteran statistician and data scientists . It explains different concepts in one of the simplest form making the understanding of Foundational mathematics for Data Science very easy and effective.

This Course includes:

  • Overview of Machine Learning and R programming language

  • Linear Algebra- Scalars, vectors & Metrices

  • Vector and Matrix Operations

  • Linear Regression

  • Calculus- Tangents, Derivatives and others

  • Vector Calculus- Vector spaces, Gradient Descent and others

  • So Much More!

This field is constantly become important for both industries as well as developers. If you are one of those who loves data science and are having issues with all the foundational concepts related to it, then it’s the right online tutorial to solve your issues. Start today, in order to become the expert of tomorrow!



Course Content

  • 5 section(s)
  • 65 lecture(s)
  • Section 1 Introduction
  • Section 2 Overview of R
  • Section 3 Linear Algebra
  • Section 4 Section Calculus
  • Section 5 Tying it All Together Vector Calculus

What You’ll Learn

  • Master the fundamental mathematical concepts required for Datas Science and Machine Learning
  • Learn to implement mathematical concepts using R
  • Master Linear alzebra, Calculus and Vector calculus from ground up
  • Master R programming langauge


Reviews

  • A
    Aravinda
    4.0

    Easy to follow lecture, If you have studied Math until 12th grade. Wish there was some sort of final real life project to tie up all the concepts.

  • A
    Abhishek Gupta
    5.0

    Good conceptual understanding of mathematical topics, some reference reads for usage in Machine learning area would have been icing on the cake.

  • D
    Daniel Nilsson
    4.5

    Good explanation of the math behind Linear regression, and optimization algorithms. It's also a good refresher of calculus/linear algebra, and you have the chance to work through some problems to form a good intuition for what behind the hood of some algorithms.

  • R
    Regi Muzio Ponziani
    5.0

    a very good course, but the instructor needs to keep the intonation stable. Overall, i am still satisfied.

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