R Programming for Data Science | 11 Videos, 11 Hours of Video Content | K2 Analytics | k2analytics.co.in
11 videos • 267 views • by Rajesh Jakhotia For notification of our FREE FREE Instructor-led Online Training Batches, subscribe to our Telegram group: https://t.me/joinchat/S7V-px0BVCpTu7ZK R is the most used programming language by Statisticians and Data Scientist for Data Analysis. People skilled with R Programming and Machine Learning Algorithms are the most sought-after resources in the job market. Many successive surveys have shown the popularity of R Programming in Statistical Analysis. Here comes our small contribution to help you learn R Programming for Data Science. Some important links to datafiles used in the video can be downloaded from our website: https://k2analytics.co.in Blog link: https://k2analytics.co.in/blog Machine Learning Course Link: https://www.k2analytics.co.in/online-... Sample Certificate Link: https://elearning.k2analytics.co.in/C... Connect with us on our Data Science, Mumbai meetup group for free Instructor Led Online sessions. Meetup Link - https://www.meetup.com/ik2analytics/ R Programming for Data Science training video duration: 11 Hours. Our video provides detailed R Programming knowledge. It starts from the Step-by-Step guide on Installation of R and R Studio. The Table of Content of R Programming is given below: 1) Step-by-step instructions for installation of R and R Studio. 2) Basic introduction to the World of R Programming. 3) Efficiently working on R Studio 4) Data Types & Data Structures in R -- Variables -- Scalar -- Vector -- List -- Matrix -- DataFrame -- Factors -- How to get help in R -- c, cbind, rbind, attach, and detach functions 5) Packages -- Importing packages -- Installing new packages 6) Data Import & Export -- Read .csv file -- Read Fixed Width File -- Read Excel File -- Import from Database -- Save and Load R Objects -- Export data to csv file format 7) Programming Structures (Loops & Conditional Statements) -- if, if-else -- For loop, While loop 8) Data Manipulations in R -- drop column / row -- create new columns -- filter -- sort -- merge -- aggregate -- rename columns -- casting 9) Functions -- in-built functions -- user-defined functions -- apply family of functions -- local and global variables 10) Charts & Graphs Subscribe to our YouTube Channel for the latest video updates. Regards, Team K2 Analytics