R Programming Hands-on Specialization for Data Science (Lv1)

An in-depth course on R language with real-world Data Science examples to supercharge your R data analysis skills

Created by: Irfan Elahi
Data Scientist in the world's largest consultancy firm

What Will I Learn?

• Setup and Use Development Environment for R
• Install and Use Packages in R
• Learn and use Atomic Data Types in R
• Learn and apply advanced explicit/Implicit Coercioning in R
• Learn multiple approaches to create vectors in R
• Understand nuances and implications in Vector Coercions
• Understand Vector indexing principles in R
• Understand and leverage Vectors' flatness property
• Understand Vector Labels and Attributes and their practical use-cases
• Learn Matrices and multiple approaches for creation
• Learn how Matrices Dimension Property works
• Learn advanced techniques for Matrices Indexing
• Learn Matrices Operations and Important Functions
• Learn the amazing use-cases of Lists
• Learn to leverage Lists' Recursive Nature
• Learn multiple ways to create Lists (including from other data structures)
• Learn critical nuances in Lists Indexing, Labels and Lists Properties
• Learn multiple approaches to create Data Frames (including from other data structures)
• Learn Data Frames sub-setting (beginner to advanced)
• Learn how to impute missing values in Data Frames for efficient Data Analysis
• Learn R Control Structures (Conditional statements and loops)
• Learn to create and use R Functions
• Understand Web Scraping Process
• Learn R's Apply family of functions for advanced data manipulation
• Learn Multiple ways to perform Web Scraping in R
• Learn how to perform Data Munging, Cleansing and Transformation in R
• Learn HTML and Document Object Model in the context of Web Scraping
• Learn XPath Query Language for Web Scraping
• Learn RSelenium setup and usage for advanced Web Scraping
• Learn Regular Expression Functions in R for advanced analysis
• Learn advanced Data Frames techniques for efficient data analysis
• Learn how to perform statistical analysis and visualisation to derive insights in R

Requirements

• There is only one pre-requisite: Passion and commitment to learn!
• No prior Programming or Data Science experience needed
• All the software/tools are open-source and available for Free!
• A computer (Windows or Linux) with internet connection needed for hands-on exercises

Target audience

• Anyone who wants to get started or advance further in Data Science
• Anyone who wants to develop expertise in R programming based on best-practices
• Anyone who wants to learn how to use R for real-life challenging Data Science projects and applications