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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
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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
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