16 January 2021 | Published by : Baturi | Views: 51 | Category: Tutorials


Udemy - R Programming for Data Science and Machine Learning (Updated 1/2021)
Created by Sunil Kumar Gupta, DataQrious Academy | Last updated 1/2021
Duration: 12 hours | 13 sections | 71 lectures | Video: 1280x720, 44 KHz | 4.6 GB
Genre: eLearning | Language: English + Sub


Learn R programming to implement Machine Learning & DS algorithms
What you'll learn
Learn to program in R at a good level and how to use R Studio
Learn the core principles of R programming
Learn how to create vectors in R
Learn how to create variables
Learn Data types in R
Decision Making in R
Learn how to build and use matrices in R
Learn how to use Functions in R
Learn to use Factors in R
Learn to use Data Frames in R
Learn how to install packages in R
Learn how to use charts and Graphs in R
Learn to read data from CSV files, Excel files
Learn Data Analysis in R
Learn how to use charts & graphs in R for data visualization
Show more
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Requirements
Basic Understanding of ComputersKeen to learn R
Description
R is one of the most popular and widely used tools for statistical programming.\nIt is a powerful, versatile, and easy to use tool for data analytics, and data visualization.\nIt is the first choice for thousands of data analysts working in both companies and academia.
This course will help you master R programming, as a first step to become a skilled R data scientist.
Got the R knowledge and not sure what to do with it?
This is your chance to finally get your hands dirty with the R and data science.\nEach lecture will you give you the tools to achieve the following two goals:
Analyze your data using R.\nFind the right visualization for your data using various R tools and packages taught in the course.\nDraw some useful visualization and find some useful predictions based on the outcome.\nIt will take just a few lines of code to get you started.
For an added challenge, repeat the same analysis for your own data.\nShare your progress for a chance to receive feedback and suggestions.\nThat way, this feedback can come not just from me but also from other students in the course.
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Who this course is for:Beginner R developers curious about data science and machine learningAnyone who wants to master RAspiring data scientistsCollege StudentsAcademic researchersDoctoral researchers

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